RYR1. Patients carrying recessive RYR1 mutations usually present from birth and are generally more severely affected, showing preferential involvement of fast twitch muscles as well as extraocular and facial muscles. In order to gain more insight into the pathophysiology of recessive RYR1-congential myopathies, we performed relative and absolute quantitative proteomic analysis of skeletal muscles from wild-type and transgenic mice carrying p.Q1970fsX16 and p.A4329D RyR1 mutations which were identified in a child with a severe congenital myopathy. Our in-depth proteomic analysis shows that recessive RYR1 mutations not only decrease the content of RyR1 protein in muscle, but change the expression of 1130, 753, and 967 proteins EDL, soleus and extraocular muscles, respectively. Specifically, recessive RYR1 mutations affect the expression level of proteins involved in calcium signaling, extracellular matrix, metabolism and ER protein quality control. This study also reveals the stoichiometry of major proteins involved in excitation contraction coupling and identifies novel potential pharmacological targets to treat RyR1-related congenital myopathies.Skeletal muscles are a highly structured tissue responsible for movement and metabolic regulation, which can be broadly subdivided into fast and slow twitch muscles with each type expressing common as well as specific sets of proteins. Congenital myopathies are a group of muscle diseases leading to a weak muscle phenotype caused by mutations in a number of genes including  Skeletal muscles constitute the largest organ, accounting for approximately 60% of the total body mass; they are responsible for movement and posture and additionally, play a fundamental role in regulating metabolism. Furthermore, skeletal muscles are plastic and can respond to physiological stimuli such as increased workload and exercise by undergoing hypertrophy. Broadly speaking muscles can be subdivided into different types depending on their speed of contraction, namely slow twitch muscles are characterized by level of oxidative activity, while fast twitch muscles show high content of enzymes involved in glycolytic activity. Fast- and slow-twitch muscle can be also identified based on the expression of specific myosin heavy chain (MyHC) isoforms . Fast twAlthough such a general classification based on MyHC isoform expression was used for many years by biochemists and physiologists, it has been recently improved thanks to the implementation of ‘omic’ approaches which have helped refine the phenotypic signature at the single fiber level. A great deal of data has shown that type 2 A fast fibers display a protein profile similar to type I fibers, namely a remarkable level of enzymes involved in oxidative metabolism. Interestingly, type 2 X fibers apparently encode proteins annotated to both oxidative and glycolytic pathways .RYR1 myopathies carrying a hypomorphic or null allele , jaw muscles and inner ear muscles that have a different embryonic origin and are made up of atypical fiber types . For exal allele .RYR1, the gene encoding the ryanodine receptor 1 (RyR1) calcium channel of the sarcoplasmic reticulum, are found in approximately 30% of all CM patients, making it the most commonly mutated gene in human CM  are a genetically heterogeneous group of early onset, non-dystrophic diseases preferentially affecting proximal and axial muscles. More than 20 genes have been implicated in CM, the most commonly affected being those encoding proteins involved in calcium homeostasis and excitation contraction coupling (ECC) and thin-thick filaments . Mutatiohuman CM . Within  and EOM . A commo and EOM  which cor allele . The musfunction . Interesfunction . Such reRyr1 mutations differentially impinge on the expression and function of proteins specific for different muscle types, we performed qualitative and quantitative proteomic analysis of EDL, soleus and EOMs from wild-type and dHT mice.In order to establish how and if Mus musculus , Myh2 and Myh13 from Trembl, the six calibration mix proteins  versus fast (condition 1) muscles. Reactome pathway analysis  versus fast EDL (condition 1) muscles. Interestingly, Reactome pathway analysis  versus slow soleus (condition 1) muscles. Reactome pathway analysis (Myh7) are enriched between 32 and 197-fold in soleus muscles, whereas α-actinin 3 and 4 and myomesin 1 are more abundant in EDL muscles and desmin is enriched in soleus muscles , as well as more cardiac muscle specific protein isoforms. For example, within the contractile and sarcomeric protein category, compared to EDL muscles, EOMs are particularly enriched in MyHC-slow (24-fold), MyHC-EO (29-fold) and Troponin C1 , whereas they contain very low amounts of α-actinin 3 (0.02-fold), MyHC 2b (0.07-fold) and MyHC 2 X (0.61-fold). Within the ECC coupling category, EOMs are enriched in calsequestrin 2 (21-fold), SERCA2 (3.6-fold) and junctin/junctate/aspartyl-ß-hydroxylase (3.5-fold) whereas their content of RyR1, the α-1 subunit of the dihydropyridine receptor (DHPRα1s), calsequestrin 1, Stac3, junctophilin-1 and triadin is significantly reduced by more than 50% compared to EDL muscles , MyHC-EO (20-fold) and cardiac troponin T (3.10-fold), whereas compared to soleus muscles they contain very low amounts of slow- MyHC (0.0096-fold), myosin light chain 2 (0.01-fold), myozenin-2 (0.017-fold) and α-actinin 2 (0.017-fold). In the ECC category, EOMs are enriched in a number of proteins including SERCA1 (eightfold) and SERCA3 (sevenfold), Stim1 (fourfold), Junctin/junctate/Aspartyl-ß-hydroxylase (threefold), DHPRα1s (1.4-fold) and junctophilin-1 (1.4-fold), whereas they contain very low amounts of SERCA2 and >50% lower amounts of Mitsugumin 53  and Hspa12a (7-fold higher in EOM vs soleus). Hspb6 has been implicated in protection against atrophy, ischemia, hypertensive stress, and metabolic dysfunction (RYR1 mutations show fiber type 1 predominance (Trim72), a protein involved in muscle membrane repair  of congenital muscle disorders carrying the p.Q1970fsX16 mutation in one allele and the mis-sense p.A4329D mutation in the other allele  increases 1.34-fold in EDLs from dHT mice. Additionally, the expression of type 2 fibers is impacted since MyHC 2 X and 2B as well asα-actinin 3   content between the two mouse genotypes.  fibers)  are decrWe applied a similar approach as described above (i.e. proteins showing significantly different (q<0.05)≥0.2-fold change in content between the two mouse genotypes) to identify important components differing between dHT and WT soleus muscles . In the In EOMs, the proteins showing the greatest fold change (aside those involved in ECC and muscle contraction), are heat shock proteins, ribosomal proteins and proteins of the ECM, a variety of heat shock proteins and calcium/calmodulin-dependent protein kinases IIβ and IIδ and S100 family proteins .Ryr1 mutations on the protein composition of muscles is more prominent in fast twitch muscles such as EOMs and EDLs compared to the slow twitch soleus muscle and the proteomic approach revealed that the content of many proteins differs between dHT and WT EDL, soleus and EOM muscles. We next refined our analysis and searched for protein whose content variation is most strongly associated with the dHT genotype. In particular, we searched for proteins which show significant changes in content in all three muscle types, namely EDL, Sol, and EOM. The Venn diagram (Hspb6) are increased only in EDL and EOMs. Interestingly, the content of 39 proteins including Kelch-like protein 41, two annotated to calcium signaling such as calmodulin kinase 2δ and aspartyl-ß -hydroxylase are increased in all three muscle types from dHT mice , some ribosomal proteins and calmodulin kinase 2 delta. EDL and EOMs that are more severely affected, also share changes in the content of other proteins, including collagens, heat shock proteins, and CamK2b as well as additional ribosomal proteins. We believe that the reduced RyR1 calcium channel content has a domino effect leading to changes in content of many proteins, particularly in EDL and EOMs.To understand in greater detail the changes in skeletal muscle function in congenital myopathies caused by recessive STIM1 and ORAI1 are the underlying feature of several genetic diseases associated with muscle weakness , a severe congenital myopathy resulting in muscle weakness and skeleton alteration  and indeed the content of collagen I, II, IV, V, and XI was significantly reduced. The ECM plays an important role in muscle force transmission, maintenance and repair and collagen fibers account for 1–10% muscle dry weight, forming a highly ordered network surrounding individual muscle fibers and muscle bundles  suffer from Ulrich and Bethlem myopathies . Patients also exhibit joint laxity that may lead to dislocation of the patella, or, more rarely abnormal tightening of certain joints, resulting in contractures especially of the Achilles tendon  that are involved in protein folding, prevention of aggregation. In skeletal muscle, these small proteins have been shown to be involved in the maintenance of the cytoskeletal network and contractile elements and play a role in myogenic differentiation . Large HRyr1 mutations evoke a global adaptive response aimed at (i) preserving the integrity of intracellular protein compartments and (ii) increasing muscle protein turnover.An interesting observation of the present study is that the content of ribosomal proteins constituting the 40 S and 60 S subunits is significantly increased in the three muscle types from the dHT compared to WT. In skeletal muscle, up-regulation of ribosomal proteins accompanies hypertrophy and training, whereas ribosomal proteins decrease with age . Thus, oKLH41) have been identified in patients with nemaline myopathy . All experiments were performed in accordance with relevant guidelines and regulations.EDL, soleus and EOM muscles from 5 male WT and 5 male dHT, 12 weeks old mice were excised, weighed, snap frozen in liquid nitrogen and mechanically grinded. Approximately 10 mg of EDL, 8 mg for of Soleus and 6 mg of EOM muscle tissue was grinded and subsequently lysed in 200 µl of lysis buffer containing 100 mM TRIS, 1% sodium deoxycholate (SDC), 10 mM TCEP and 15 mM chloroacetamide, followed by sonication  and heating to 95 °C for 10 min. After cooling, protein samples were digested by incubated overnight at 37 °C with sequencing-grade modified trypsin . Samples were acidified using 5% TFA and peptides cleaned up using the Phoenix 96 x kit  following the manufacturer’s instructions. After drying the peptides in a SpeedVac, samples were stored at –80 °C.Dried peptides were dissolved in 100 µl of 0.1% formic acid and the peptide concentration determined by UV-nanodrop analysis. Sample aliquots containing 25 µg of peptides were dried and labeled with tandem mass isobaric tags  according to the manufacturer’s instructions. To control for ratio distortion during quantification, a peptide calibration mixture consisting of six digested standard proteins mixed in different amounts were added to each sample before TMT labeling as recently described . After pThe generated 12 peptide samples fractions were analyzed by LC-MS as described previously . ChromatMus musculus , Myh2 and Myh13 from Trembl, the six calibration mix proteins  assays  were genPeptide samples for PRM analysis were resuspended in 0.1% aqueous formic acid, spiked with iRT peptides and the heavy reference peptide mix at a concentration of 10 fmol of heavy reference peptides per 1 µg of total endogenous peptide mass and subjected to LC–MS/MS analysis on the same LC-MS system described above using the following settings: The resolution of the orbitrap was set to 140,000 FWHM (at 200 m/z), the fill time was set to 500ms to reach an AGC target of 3e6, the normalized collision energy was set to 27%, ion isolation window was set to 0.4 m/z and the first mass was fixed to 100 m/z. A MS1 scan at 35,000 resolution (FWHM at 200 m/z), AGC target 3e6 and fill time of 50ms was included in each MS cycle. All raw-files were imported into SpectroDive for protein / peptide quantification. To control for variation in injected sample amounts, the total ion chromatogram (only comprising ions with two to five charges) of each sample was determined and used for normalization. To this end, the generated raw files were imported into the Progenesis QI software (Nonlinear Dynamics (Waters), Version 2.0), the intensity of all precursor ions with a charge of +2 to+5 were extracted, summed for each sample and used for normalization. Normalized ratios were transformed from the linear to the log-scale, normalized relative to the control condition and the median ratio among peptides corresponding to one protein was used for protein quantification.Total homogenates of EDL, soleus and EOM muscles from WT mice were prepared in cracking buffer as previously described . Proteinhttps://string-db.org/; Version 11.5).Matlab 2021b (Mathworks)  was used This is a fundamental study reporting a comprehensive proteomic analysis in three skeletal muscle types from wild-type and RYR1-related myopathy mice. It adds quantitative stoichiometry of several excitation-contraction coupling-related proteins. This valuable work compares the disease-related proteomes of the different skeletal muscle groups. public reviews designed to be posted alongside the preprint for the benefit of readers; (ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.Our editorial process produces two outputs: (i) Decision letter after peer review:Ryr1 mutations linked to congenital myopathies" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by Mone Zaidi as the Senior Editor.Thank you for submitting your article "Quantitative proteomic analysis of skeletal muscles from wild type and transgenic mice carrying recessive The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission. Reviewers (1) and (2) were enthusiastic about the work; reviewer (3) had reservations. Nevertheless we would like to offer you the opportunity to submit a revised version addressing the comments particularly of reviewers (2) and (3). I have worked through all the comments and hope the notes to follow may be useful in connection with this.Essential revisions:Reviewer (2) makes the following broad comments that may merit addressing:a) The main limitation of this study is that the results are primarily descriptive in nature, and thus, do not provide mechanistic insight into how Ryr1 disease mutations lead to the muscle-specific changes observed in the EDL, soleus and EOM proteomes.b) Results comparing fast twitch (EDL) and slow twitch (soleus) muscles from WT mice confirmed several known differences between the two muscle types. Similar analyses between EOM/EDL and EOM/soleus muscles from WT mice were not conducted.c) While a reactome pathway analysis for proteins changes observed in EDL is shown in Supplemental Figure 1, the authors do not fully discuss the nature of the proteins and corresponding pathways impacted in the other two muscle groups analyzed.Specific requestsReviewer (2) also makes the following specific requests:a) This study would be strengthened by inclusion of tables that summarize relative protein changes between EOM/EDL muscles and EOM/soleus muscles from WT mice as was done in Table 1 for soleus/EDL muscles from WT mice.b) As there are reliable antibodies for many of the selected proteins found to be significantly increased or decreased in muscle from dHT mice, it would seem important and feasible to validate at least a subset of the proteomic findings in western blot experiments. For example, the proteome studies found JP-1 levels to be reduced in both EDL and soleus, but not in EOM; Hspa5 (BIP) levels to be increased in EDL and EOM, but unaltered in soleus; collagen levels to be reduced in EDL, but unaltered in both soleus and EOM. Such findings could readily be validated in quantitative western blot experiments.c) Beyond the author-selected muscle-related processes shown in Tables 2-4, limited non-biased information is provided regarding other potential proteins and pathways altered in the different muscles evaluated from dHT mice. A more robust unbiased evaluation of all of the significantly increased/decreased proteins and the underlying pathways involved could be informative. A reactome pathway analysis comparison is shown for EDL muscles from WT and dHT mice in Supplemental Figure 1. It would be helpful if the authors could include similar reactome pathway analyses for the proteins found to be significantly increased/decreased in soleus and EOM of WT and dHT mice.d) The authors provide a Venn diagram in Supplemental Figure 2 to highlight overlap between proteins that are increased and decreased across all three muscles. Interestingly, for all three muscles evaluated , more proteins were found to be increased than decreased in dHT mice (e.g. 560 proteins are increased in EOM and only 117 are decreased). In addition, while only one protein (Ryr1) was found to be decreased across all muscles, 40 proteins were found to be increased in all three muscles. It would be helpful if the authors could provide a summary table that lists these 40 proteins that are upregulated in all three muscles. Does a GO pathway analysis of these 40 proteins provide any common theme that extends across all three types muscles? Are there any common themes to come out of separate GO pathway analyses of the 848 protein differences observed in EDL, 509 protein differences observed in soleus, and 677 protein differences observed in EOM? What about the union of common proteins changes observed between EDL and EOM (144 proteins), EDL and soleus (98 proteins), and EOM and soleus (106 proteins)?Reviewer (3) Broad comments:a) it would be useful to determine whether changes in protein levels correlated with changes in mRNA levels and whether or not the protein present was functional, and whether Stac3 was in fact stoichiometrically depleted in relation to Cacna1s.b) In the abstract, the authors stated that skeletal muscle is responsible for voluntary movement. It is also responsible for non-voluntary. The abstract needs to be refocused on the mutation and on what we learn from this study. Please avoid vague statements like "we provide important insights to the pathophysiological mechanisms…" mainly when the study is descriptive and not mechanistic.c) The author should bring up the mutation name, location and phenotype early in the introduction.d) This reviewer also suggests that the authors refocus the introduction on the mutation location in the 3D RyR1 structure (available cryo-EM structure), if there is any nearby ligand binding site, protomers junction or any other known interacting protein partners. This will help the reader to understand how this mutation could be important for the channel's functionReviewer 3 raised the following specific critiques:a) The mass spec results were filtered based on very low confidence criteria: fold change 0.25 and q<0.05. which allows detection of a large number of proteins potentially irrelevant to the study. The authors should change their filtering threshold to a fold change of 0.58 (at least 50% change in the expression levels), q<0.05, and at least two unique peptides per protein.b) In the Results section (page 6), the authors compared the protein expression profiles between EDL and soleus in wild-type mice. It is unclear why this analysis was performed. It is expected to see differences in protein expression levels when comparing a glycolytic and oxidative muscle in wild type. This is due to the properties of each muscle type.c) The authors did not validate any of the detected changes, and whether these changes are contributing to the phenotype. Moreover, the phenotype of these mice has not been evaluated at this age. Do these mice have muscle weakness or muscle atrophy? Is there any detected protein that can be targeted by a drug?d) The fact that RyR1 expression is decreased in all muscle types could be simply explained by the decreased muscle content for all proteins of the contractile apparatus. The histopathology of these mice needs to be evaluated for markers of atrophy, autophagy, apoptosis, and necrosis.e) In addition to reconsidering the filtering criteria for the proteomic analysis, it is highly recommended to change the color of the heatmap to light colors to improve the readability of the figures (red and blue are very common color codes that could be used).f) The authors could perform a GSEA analysis to have a better understanding of the enriched pathways and maybe focus on the most relevant ones. The GO pathway analysis seems to not be very informative here and the changes are subtle considering that the filter threshold was set at 0.25.g) The discussion should be more organized and should address the pathological mechanism of the mutation and how the current study improves our understanding of the disease. For example, the section about the implication of the mutation in bone formation and remodeling is irrelevant to the current study and is an over-interpretation of the results found in skeletal muscle.Reviewer #1 (Recommendations for the authors):The subject matter is of clear scientific interest justifying full review. The objectives of the paper are clearly introduced, and the methods logically described and appropriate. The proteomic findings are striking and clear. There is a clear comparison between WT and mutant for the different muscle types. There is extensive and potentially useful reference information in the Tables and supplemental data. Subject to the detailed technical comments of the expert referee, this should be a potentially appropriate contribution for publication.Reviewer #2 (Recommendations for the authors):This study would be strengthened by inclusion of tables that summarize relative protein changes between EOM/EDL muscles and EOM/soleus muscles from WT mice as was done in Table 1 for soleus/EDL muscles from WT mice.As there are reliable antibodies for many of the selected proteins found to be significantly increased or decreased in muscle from dHT mice, it would seem important and feasible to validate at least a subset of the proteomic findings in western blot experiments. For example, the proteome studies found JP-1 levels to be reduced in both EDL and soleus, but not in EOM; Hspa5 (BIP) levels to be increased in EDL and EOM, but unaltered in soleus; collagen levels to be reduced in EDL, but unaltered in both soleus and EOM. Such findings could readily be validated in quantitative western blot experiments.Beyond the author-selected muscle-related processes shown in Tables 2-4, limited non-biased information is provided regarding other potential proteins and pathways altered in the different muscles evaluated from dHT mice. A more robust unbiased evaluation of all of the significantly increased/decreased proteins and the underlying pathways involved could be informative. A reactome pathway analysis comparison is shown for EDL muscles from WT and dHT mice in Supplemental Figure 1. It would be helpful if the authors could include similar reactome pathway analyses for the proteins found to be significantly increased/decreased in soleus and EOM of WT and dHT mice.The authors provide a Venn diagram in Supplemental Figure 2 to highlight overlap between proteins that are increased and decreased across all three muscles. Interestingly, for all three muscles evaluated , more proteins were found to be increased than decreased in dHT mice (e.g. 560 proteins are increased in EOM and only 117 are decreased). In addition, while only one protein (Ryr1) was found to be decreased across all muscles, 40 proteins were found to be increased in all three muscles. It would be helpful if the authors could provide a summary table that lists these 40 proteins that are upregulated in all three muscles. Does a GO pathway analysis of these 40 proteins provide any common theme that extends across all three types muscles? Are there any common themes to come out of separate GO pathway analyses of the 848 protein differences observed in EDL, 509 protein differences observed in soleus, and 677 protein differences observed in EOM? What about the union of common proteins changes observed between EDL and EOM (144 proteins), EDL and soleus (98 proteins), and EOM and soleus (106 proteins)?Reviewer #3 (Recommendations for the authors):1) The mass spec results were filtered based on very low confidence criteria: fold change 0.25 and q<0.05. which allows detection of a large number of proteins potentially irrelevant to the study. The authors should change their filtering threshold to a fold change of 0.58 (at least 50% change in the expression levels), q<0.05, and at least two unique peptides per protein.2) In the Results section (page 6), the authors compared the protein expression profiles between EDL and soleus in wild-type mice. It is unclear why this analysis was performed. It is expected to see differences in protein expression levels when comparing a glycolytic and oxidative muscle in wild type. This is due to the properties of each muscle type.3) The authors did not validate any of the detected changes, and whether these changes are contributing to the phenotype. Moreover, the phenotype of these mice has not been evaluated at this age. Do these mice have muscle weakness or muscle atrophy? Is there any detected protein that can be targeted by a drug?4) The fact that RyR1 expression is decreased in all muscle types could be simply explained by the decreased muscle content for all proteins of the contractile apparatus. The histopathology of these mice needs to be evaluated for markers of atrophy, autophagy, apoptosis, and necrosis.5) In addition to reconsidering the filtering criteria for the proteomic analysis, it is highly recommended to change the color of the heatmap to light colors to improve the readability of the figures (red and blue are very common color codes that could be used).6) The authors could perform a GSEA analysis to have a better understanding of the enriched pathways and maybe focus on the most relevant ones. The GO pathway analysis seems to not be very informative here and the changes are subtle considering that the filter threshold was set at 0.25.7) The discussion should be more organized and should address the pathological mechanism of the mutation and how the current study improves our understanding of the disease. For example, the section about the implication of the mutation in bone formation and remodeling is irrelevant to the current study and is an over-interpretation of the results found in skeletal muscle. Essential revisions:Reviewer (2) makes the following broad comments that may merit addressing:a) The main limitation of this study is that the results are primarily descriptive in nature, and thus, do not provide mechanistic insight into how Ryr1 disease mutations lead to the muscle-specific changes observed in the EDL, soleus and EOM proteomes.Ryr1 mutation are consistent with the high expression level of heat shock proteins in slow twitch muscles. However, as suggested by Reviewer 3, we have removed "vague statements" from the text of the revised manuscript, concerning major insights into pathophysiological mechanisms, since we are aware that the mechanistic information, if any, that we can extract from the data set, cannot go over the intrinsic limitation of the high-throughput proteomic technology.An intrinsic feature of the high-throughput proteomic analysis technology is the generation of lists of differentially expressed proteins (DEP) in different muscles from WT and mutated mice. Although the definition of mechanistic insights related to changes of dozens of proteins is very interesting, it is a difficult task to accomplish and goes beyond the goal of the high-throughput proteomic analysis presented here. Nevertheless, the analysis of DEPs may indeed provide arguments to speculate on the pathogenesis of the phenotype linked to recessive RyR1 mutations. In the unrevised manuscript, we pointed out that the fiber type I predominance observed in congenital myopathies linked to recessive b) Results comparing fast twitch (EDL) and slow twitch (soleus) muscles from WT mice confirmed several known differences between the two muscle types. Similar analyses between EOM/EDL and EOM/soleus muscles from WT mice were not conducted.We agree with the point raised by the Reviewer. In the revised manuscript we have changed figure 2. The new figure 2 shows the analysis of differentially expressed proteins in EDL, soleus and EOMs from WT mice. We have also added 2 new Tables (new supplementary 1b and 1c) and have inserted our findings in the revised Results section .c) While a reactome pathway analysis for proteins changes observed in EDL is shown in Supplemental Figure 1, the authors do not fully discuss the nature of the proteins and corresponding pathways impacted in the other two muscle groups analyzed.We have now included in the revised manuscript a new figure 2 which includes the Reactome pathway analysis comparing EDL with soleus, EDL with EOM and soleus with EOM . We have also inserted into the revised manuscript a brief description of the pathways showing the greatest changes in protein content . We agree that the data showing changes in protein content between the 3 muscle groups of the WT mice are important also because they validate the results of the proteomic approach. Indeed, the present results confirm that many proteins including MyHCIIb, calsequestrin 1, SERCA1, parvalbumin etc are more abundantly expressed in fast twitch EDL muscles compared to soleus. Similarly, our results confirm that EOMs are enriched in MyHC-EO as well as cardiac isoforms of ECC proteins. This point has been clarified in the revised version of the manuscript . Nevertheless, we would like to point out that the main focus of our study is to compare the changes of protein content induced by the presence of recessive RyR1 mutations.Specific requestsa) This study would be strengthened by inclusion of tables that summarize relative protein changes between EOM/EDL muscles and EOM/soleus muscles from WT mice as was done in Table 1 for soleus/EDL muscles from WT mice.In the revised version of the manuscript, we now include summary tables of relative protein changes between EDL/Soleus, EOM/EDL and EOM/Soleus .b) As there are reliable antibodies for many of the selected proteins found to be significantly increased or decreased in muscle from dHT mice, it would seem important and feasible to validate at least a subset of the proteomic findings in western blot experiments. For example, the proteome studies found JP-1 levels to be reduced in both EDL and soleus, but not in EOM; Hspa5 (BIP) levels to be increased in EDL and EOM, but unaltered in soleus; collagen levels to be reduced in EDL, but unaltered in both soleus and EOM. Such findings could readily be validated in quantitative western blot experiments.The unrevised manuscript and previous manuscripts  validate the proteomic data, namely Western blot analysis with Ab against Stim1, RyR1, Casequestrin 1, DHPRa1 are consistent with the proteomic data of this study. Nevertheless, to comply with the reviewer’s request we have performed Western blot analysis to validate the differential expression of JPH1 and Col1a1 in the different muscles. As can be seen in c) Beyond the author-selected muscle-related processes shown in Tables 2-4, limited non-biased information is provided regarding other potential proteins and pathways altered in the different muscles evaluated from dHT mice. A more robust unbiased evaluation of all of the significantly increased/decreased proteins and the underlying pathways involved could be informative. A reactome pathway analysis comparison is shown for EDL muscles from WT and dHT mice in Supplemental Figure 1. It would be helpful if the authors could include similar reactome pathway analyses for the proteins found to be significantly increased/decreased in soleus and EOM of WT and dHT mice.As stated above in our answer to broad comments, the revised manuscript now includes the Reactome analysis comparison of EDL, EOM and Soleus muscles from WT mice. Figure 2 panels C, F and I of the revised manuscript now includes the Reactome pathway comparison between WT EDL, soleus and EOM muscles. Whereas Figure 3—figure supplement 1 of the revised manuscript shows the Reactome pathway analysis of EDL and EOM from WT and dHT mice. Since the number of proteins changing between WT and dHT soleus muscles is relatively small it does not generate a Reactome pathway. We have nevertheless analyzed in more depth differences between WT and dHT EDL, soleus and EOM applying GO analysis of proteins annotated to Biological process and GO Cellular Compartments. The new data is shown in Figure 4—figure supplement 1A and Figure 4B, C and E of the revised manuscript.d) The authors provide a Venn diagram in Supplemental Figure 2 to highlight overlap between proteins that are increased and decreased across all three muscles. Interestingly, for all three muscles evaluated , more proteins were found to be increased than decreased in dHT mice (e.g. 560 proteins are increased in EOM and only 117 are decreased).In Figure 4—figure supplement 1 of the revised manuscript, we now analyze GO genes annotated to biological processes of up- and downregulated proteins in each muscles type, i.e. EDL, Soleus and EOM.In addition, while only one protein (Ryr1) was found to be decreased across all muscles, 40 proteins were found to be increased in all three muscles. It would be helpful if the authors could provide a summary table that lists these 40 proteins that are upregulated in all three muscles. Does a GO pathway analysis of these 40 proteins provide any common theme that extends across all three types muscles? Are there any common themes to come out of separate GO pathway analyses of the 848 protein differences observed in EDL, 509 protein differences observed in soleus, and 677 protein differences observed in EOM? What about the union of common proteins changes observed between EDL and EOM (144 proteins), EDL and soleus (98 proteins), and EOM and soleus (106 proteins)?In the revised version of the manuscript, we now provide a list of the shared up-regulated proteins in the three muscle types from dHT mice (figure 4D of the revised manuscript). We also complied with the Reviewer’s request and provide GO pathways of differentially expressed protein intersects of the Venn diagram in dHT EDL, Soleus and EOM .Reviewer (3) Broad comments:a) it would be useful to determine whether changes in protein levels correlated with changes in mRNA levelsStac3 and Cacna1s in EDL, Soleus and EOM from WT mice  the expression level of both transcripts and proteins is higher EDL compared to EOM and soleus muscles, respectively, (ii) the expression level of transcripts encoding Stac3 correlate with those encoding Cacan1s and confirm proteomic data. In addition, the level of Stac3 transcript does not changes between WT and dHT, confirming our proteomic data which show that Stac3 protein content in muscles from dHT is similar to that found in WT littermates. Altogether these results support the concept that the differences in Stac3 content between EDL and soleus occur at both the protein and transcript levels, namely high Stac3 mRNA level correlates with higher protein content (EDL) and low mRNA levels correlated with low Stac3 protein content in Soleus muscles .b) In the abstract, the authors stated that skeletal muscle is responsible for voluntary movement. It is also responsible for non-voluntary. The abstract needs to be refocused on the mutation and on what we learn from this study. Please avoid vague statements like "we provide important insights to the pathophysiological mechanisms…" mainly when the study is descriptive and not mechanistic.The abstract of the revised manuscript has been rewritten. In particular, we removed statements referring to important “pathophysiological mechanistic insight”.c) The author should bring up the mutation name, location and phenotype early in the introduction.In the revised manuscript we provide the information requested by the Reviewer .d) This reviewer also suggests that the authors refocus the introduction on the mutation location in the 3D RyR1 structure (available cryo-EM structure), if there is any nearby ligand binding site, protomers junction or any other known interacting protein partners. This will help the reader to understand how this mutation could be important for the channel's functionThe residue Ala4329 is present inside the TMx (Auxiliary transmembrane helices) domain which spans from residue 4322 to 4370 and interposes structurally . Although the structural resolution of the region has been improved , parts of the domain still remain with no defined atomic coordinates, especially the region encompassing a.a. E4253 – F4540. Because of such undefined atomic coordinates of the region E4253-F4540, we are not able to determine the real orientation and the disposition of the amino acids in this region, including the A4329 residue. As reference, structure PDB: 5TAL of des Georges et al., 2016 was analyzed with UCSF Chimera (production version 1.16) .Reviewer 3 raised the following specific critiques:a) The mass spec results were filtered based on very low confidence criteria: fold change 0.25 and q<0.05. which allows detection of a large number of proteins potentially irrelevant to the study. The authors should change their filtering threshold to a fold change of 0.58 (at least 50% change in the expression levels), q<0.05, and at least two unique peptides per protein.We chose to filter our data with the FDR q<0.05, since it is the parameter most commonly adopted by the proteomic community to statistically validate changes in protein expression. The q<0.05 filter provides statistical confidence on the statistical validity of observed changes regardless of the extent of the fold change , Quantitative Methods in Proteomics, Methods in Molecular Biology, vol. 2228, https://doi.org/10.1007/978-1-0716-1024-4_1).The reviewer proposes to set a fold change of 0.5 to detect proteins relevant to the study. We think that such a filter will miss relevant proteins. One example for all: if we set the filter for fold change of protein expression level to 0.5 we will filter out the RyR1 in the comparison between Soleus WT and Soleus from dHT mice. This result would be inconsistent with a set of data obtained by different experimental approaches including western blot analysis and qPCR  showing that the muscle phenotype of the soleus from dHT mice is in agreement with a decrease of the RyR1 protein and transcript expression level, even though it does not reach the threshold of 0.5. For this reason, we think that filtering the fold changed to 0.5 has the plausible risk of missing proteins which might be relevant to this study.b) In the Results section (page 6), the authors compared the protein expression profiles between EDL and soleus in wild-type mice. It is unclear why this analysis was performed. It is expected to see differences in protein expression levels when comparing a glycolytic and oxidative muscle in wild type. This is due to the properties of each muscle type.We performed the comparison of the proteome of EDL and soleus muscles, to validate the procedure of the proteomic analysis. As shows in figure 2 and Table 1 of the unrevised manuscript, our proteomic analysis indeed picked up not only the major molecular signatures of each muscle type, but also its relevance for the functional phenotype of fast and slow twitch muscles. Figure 2 and Table 1 of the unrevised manuscript confirm the molecular signatures of fast and slow twitch muscles, thus validating the functional sub-specialization of these muscle types. Therefore, we are confident of our proteomic approach results and further proceeded to analyze the proteome of EDL vs EOM, soleus vs EOM as well as the muscles from dHT mice.c) The authors did not validate any of the detected changes, and whether these changes are contributing to the phenotype. Moreover, the phenotype of these mice has not been evaluated at this age. Do these mice have muscle weakness or muscle atrophy?The proteomic analysis of the dHT mice is validated by published data  concerning the skeletal muscle phenotype of dHT mice. In these publications, we showed that the decrease of the RyR1protein content is consistent with the decrease of force developed both in vivo and in vitro and with the smaller electrically evoked calcium transients. EDL from dHT showed a 10% decrease of wet weight, suggesting a small degree of muscle atrophy, which does not correlate with the much larger decrease of RyR1 content in the skeletal muscle homogenate. The muscle weakness is mostly explained mostly by reduction of RyR1 expression and in part by the small degree of muscle atrophy. In Elbaz et al., 2019 and Eckhardt et al., 2020 papers, mice having an age range between 8-12 weeks were characterized and in the present paper, muscles were harvested from 12 weeks old mice . See also reply to Reviewer 2, point b.Is there any detected protein that can be targeted by a drug?We interrogate the Drug Gene Interaction Database to analyze the differentially expressed proteins in EDL, Soleus and EOM (dHT vs WT). For example, the DGID list indicates CamKIId as potential target in EDL, Soleus and EOM. Although there are available inhibitors of this potential pharmacological target, we believe that addressing this issue goes beyond the scope of this manuscript.d) The fact that RyR1 expression is decreased in all muscle types could be simply explained by the decreased muscle content for all proteins of the contractile apparatus. The histopathology of these mice needs to be evaluated for markers of atrophy, autophagy, apoptosis, and necrosis.The proteomic analysis of the dHT mice is validated by data  concerning the skeletal muscle phenotype of the dHT mice. Elbaz et al. (2019) showed that in EDL and Soleus muscle from dHT mice there are ultrastructural changes referable to core-like structures, but no major signatures of atrophy and or necrosis . We woule) In addition to reconsidering the filtering criteria for the proteomic analysis, it is highly recommended to change the color of the heatmap to light colors to improve the readability of the figures (red and blue are very common color codes that could be used).We used yellow blue for the heat maps because such colors are more compatible for people with impaired color vision .f) The authors could perform a GSEA analysis to have a better understanding of the enriched pathways and maybe focus on the most relevant ones. The GO pathway analysis seems to not be very informative here and the changes are subtle considering that the filter threshold was set at 0.25.The reviewer suggests to use the GSEA tool to explore enrichment pathway since GO pathway was not informative. We believe that the use of the GSEA tool and other tools will face the same problem, i.e. the enrichment terms are not informative for EC coupling and other muscle physiology terms because most of the annotated terms in these tools are related to cancer or immunological pathways regardless of the filter threshold relative to fold changes. We did use GSEA tool and we did not pick up significant terms relating to EC coupling and neuromuscular disorders linked to RyR1 mutationsg) The discussion should be more organized and should address the pathological mechanism of the mutation and how the current study improves our understanding of the disease. For example, the section about the implication of the mutation in bone formation and remodeling is irrelevant to the current study and is an over-interpretation of the results found in skeletal muscle.The discussion of the revised manuscript has been reorganized with new paragraphs. In addition, in the revised manuscript we removed the sentence referring to the effects of RyR1 mutations on bone formation and remodeling.


Researchers in the Netherlands proposed the Pillars for Positive Health (PPH) as a broadly encompassing health definition to support more realistic and meaningful care planning for people living with chronic disease and other life-long health conditions. The PPH was subsequently converted to the My Positive Health (MPH) spider web visualization tool. This study sought to identify opportunities for more person-centred care planning at the point of care in home care, using the MPH tool as a framework to link comprehensive assessment and dialogue-based goal-setting.A modified eDelphi method was used to conduct domain mapping with a purposively sampled expert panel (n = 25). The panel consisted of researchers, health care providers, older adults and caregivers. A two-stage eDelphi process was conducted, with each stage consisting of three survey rounds. In the first stage, participants were asked to map 201 elements of the interRAI Home Care (interRAI HC) comprehensive assessment tool to the six MPH domains or “No pillar of best fit”. The second stage focused on identifying opportunities to adapt or expand comprehensive assessment as it relates to the MPH domains.In Stage 1, 189 of 201 elements reached consensus in domain mapping. These included: 80 elements for Bodily Functions, 32 for Daily Functioning, 32 for Mental Wellbeing, 24 for Quality of Life, 10 for Participation, and 1 for Meaningfulness. Ten elements were identified to have no pillar of best fit. The 12 elements that did not reach consensus in Stage 1 formed the basis for Stage 2, where expert panel participants proposed four new assessment elements in Meaningfulness and Participation and 11 additional descriptors across the six MPH domains. Of these, two elements and nine of the 11 descriptors reached consensus.Findings show that elements of the interRAI HC are oriented toward the physical, functional, and mental health domains. Consequently, complementary assessment elements and/or tools may be needed to support comprehensive assessment of ‘Meaningfulness’ and ‘Participation’ in person-centred home and community care. Additional descriptors may also be needed to aid communication regarding the understanding and application of MPH domains.The online version contains supplementary material available at 10.1186/s12913-023-10203-5. How we define health has significant ramifications for care delivery across different settings . The WorRecognizing the limitations of the WHO’s health definition, a multidisciplinary group of international healthcare experts attending a two-day conference in the Netherlands explicated a new vision of health that acknowledges its dynamic nature and underscores the individual’s ability to adapt to changing health states . Health Home and community-based care provides an optimal backdrop for the implementation of a broader conceptualization of health. Persons receiving home care services have complex needs, often having multiple chronic medical conditions complicated by functional impairments and social frailty , 10. AvaComprehensive assessment of client needs has been demonstrated to be an integral part of the care planning process in home care, as it supports the collation of health information which is used to develop individualized, person-centred plan aimed at improving overall health outcomes . A recenAn evidence-based approach to the successful integration of comprehensive assessment tools in the care planning process in home care is through the process of dialogue-based goal setting –22. In aThe overall goal of this study was to identify opportunities to facilitate more person-centred care planning at the point-of-care using the MPH tool as a framework to link comprehensive assessment and dialogue-based goal setting in home care. Specifically, the study aimed to: (1) map the elements of a standardized comprehensive assessment tool mandated for use in Ontario home care onto the six domains of the MPH tool, (2) identify opportunities to adapt or expand the MPH tool based on unmapped items from the comprehensive assessment, and (3) identify opportunities to adapt or expand comprehensive assessment to support life care, as defined by the MPH domains.We used a modified eDelphi method for this study. The Delphi method was developed by the Rand Corporation and first described in a paper by Dalkey and Helmer (1963) . The metTwo modifications to the traditional Delphi method were employed for this study. First, due to the geographical spread of the prospective expert panel as well as considerations for social distancing during the pandemic, the survey was conducted online using an eDelphi approach. Additionally, because the initial idea generation phase was replaced with pre-existing information , this study was considered a modified eDelphi study. We conducted the eDelphi study over two stages. Stage 1 addressed objective 1, and Stage 2 addressed objectives 2 and 3.Non-probability purposive sampling combined with snowball sampling  was adopThe first stage consisted of three survey rounds and sought to address the first study objective—to map the elements of a standardized comprehensive assessment tool mandated for use in Ontario home care  onto the six domains of the MPH tool. All surveys were conducted online using Qualtrics software .www.interRAI.org) is a not-for-profit network of more than 135 researchers, clinicians, and policy experts from over 35 countries focused on the development and application of comprehensive assessment, screening, and care planning systems that identify and respond to the needs of vulnerable persons of all ages across the continuum of care. With over three decades of research experience resulting in over 1400 scientific publications, interRAI has developed assessment systems that have been adopted on a large-scale basis internationally across multiple settings including home and community care, long-term care and both community and in-patient mental health [interRAI  . ParticiThe second stage focused on identifying opportunities to adapt or expand the MPH tool based on unmapped items from the comprehensive assessment and identifying opportunities to adapt or expand comprehensive assessment to support life care, as defined by the MPH domains. This stage was also conducted over three survey rounds.In round 1 of the second stage, MPH domains that were considered underrepresented by interRAI HC elements  and interRAI HC elements that did not reach consensus after stage 1 were considered. Participants were asked to propose suggestions for additional assessment elements and/or domain ideas. Panel responses on proposed new MPH domain ideas and assessment elements were then compiled and in survey round 2 participants were asked to rate their agreement with their inclusion using a 5-point Likert scale . As in Stage 1, consensus was defined as proposed MPH domain ideas or assessment elements rated 4 or greater by 70% or more of the Delphi participants. In round 3, after removing elements that reached consensus in round 2, participants were invited to respond to the survey again. To facilitate consensus-building, participants were provided a summary of findings from the previous rounds to inform their decision.In both stages, the link to the survey was sent individually to each participant by email. Participants had three weeks to complete each survey. A reminder was provided to each participant who had not completed the survey after every seven days . Individuals who did not complete the survey after the three-week period were considered to have opted out of the process and were not invited to participate in subsequent rounds.Descriptive statistics  were used to describe the demographic characteristics of eDelphi participants. To compare the demographic characteristics of eDelphi starters and completers, independent t-tests for continuous variables and chi-square analyses for categorical variables were conducted.After each survey round in Stage 1, descriptive statistics (percentages) were used to summarize the distribution of responses for each assessment element matched to the MPH domains, and to identify elements that reached consensus after each survey round. Modes were used to identify the most frequently occurring response option for each interRAI HC assessment element.Qualitative data from survey 1 of Stage 2 regarding expert panel suggestions for additional assessment elements and additional MPH domain ideas were categorized thematically using Microsoft Excel for Microsoft 365 MSO version 2202. To enhance the reliability of this exercise, this process was conducted by AF and independently verified by all co-authors, first through asynchronous review, and then in a consensus-building meeting.For surveys 2 and 3 of Stage 2, descriptive statistics (modes and percentages) were used to summarize panel members agreement ratings for additional assessment elements and MPH domain ideas and to identify suggestions that reached consensus after each round.Forty-seven experts responded to the study recruitment email and were sent the link to survey 1 of the eDelphi study. Of those, 39 expert panel members completed the first survey and provided demographic information. In total, 25 expert panel members completed all six rounds (two stages) of the eDelphi study  individuals who agreed to be part of the expert panel by email completed the first survey. In round 1 there was consensus on 84 (41.8%) of the 201 interRAI HC assessment elements among the expert panel members. Of these, 46 (54.8%) interRAI elements reached consensus in the Bodily Functions domain, 15 (17.9%) in Daily Functioning, 10 (11.9%) in Mental Wellbeing, 7 (8.3%) in Quality of Life, and 6 (7.1%) in Participation. No interRAI HC assessment elements reached consensus in the Meaningfulness domain or in No Pillar of Best Fit.In round 2, expert panel members were presented with 117 non-consensus interRAI HC assessment elements from survey 1. Thirty-six out of 39 (92% response rate) expert panel members completed survey 2. Forty-nine (41.9%) of 117 assessment elements reached consensus across expert panel members. Of these, 18 (36.7%) elements reached consensus in the Bodily Functions domain, 13 (26.5%) in Mental Wellbeing, 6 (12.2%) in Quality of Life, 5 (10.2%) in Daily Functioning, and 2 (4.1%) in Participation. Five (10.2%) elements reached consensus in No Pillar of Best Fit. No assessment elements reached consensus in the Meaningfulness domain.In round 3, the expert panel were presented with the remaining 68 interRAI HC assessment elements which had not yet reached consensus. Twenty-eight of thirty-six (78% response rate) expert panel members completed survey 3. Fifty-three (77.9%) of the 68 assessment elements were found to reach consensus. Of these, 16 (30.2%) reached consensus in Bodily Functions, 12 (22.6%) in Daily Functioning, 11 (20.8%) in Quality of Life, 9 (17.0%) in Mental Wellbeing, 2 (3.8%) in Participation and 1 (1.9%) in Meaningfulness. Five elements (7.4%) reached consensus in No Pillar of Best Fit.Over the course of the three surveys conducted in Stage 1 of the eDelphi, 189 of 201 assessment elements reached consensus. Of these, 80 (39.8%) reached consensus in the Bodily Functions domain, 32 (15.9%) in Daily Functioning, 32 (15.9%) in Mental Wellbeing, 24 (11.9%) in Quality of Life, 10 (5.0%) in Participation, and 1 in Meaningfulness  considered underrepresented by interRAI HC elements. After coding, four main themes for each domain were identified from the suggestions provided by the expert panel. For Meaningfulness, the following additional areas for assessment were identified: “person has thriving social support networks or feels included as part of a community”, “person’s ability to volunteer, make positive impact in their communities, or feels part of something bigger”, “person practices mindfulness, is self-aware, or has a spiritual life”, and “person has goals and purpose ”. For Participation, the following additional areas for assessment were identified: “person’s social and demographic information”, “person has thriving social support networks or feels included as part of a community”, “person’s ability to engage in activities of interest”, and “person’s emotional health and wellbeing”. Notably, one theme, “person has thriving social support networks or feels included as part of a community” was identified in both underrepresented MPH domains. Upon deliberation, the study team agreed to let the expert panel decide through the process of consensus in subsequent surveys, as to which MPH domain the duplicated theme best fit into. Detailed information on suggestions provided by expert panel in each theme is included in Supplemental File The expert panel also provided a range of suggestions about potential new MPH domain ideas for the interRAI HC elements that did not reach consensus in Stage 1 of the eDelphi study. Upon detailed review and categorization by the study team, the suggestions provided appeared to be additional descriptors ” fit in Meaningfulness. Additionally, the panel agreed that “person has thriving social support networks or feels included as part of a community” and “person’s ability to engage in activities of interest” fit in Participation.For the proposed additional descriptors, a total of 9 out of the 11 reached consensus for describing at least one of interRAI HC elements that were the subject of Stage 2.At the end of survey 3, one additional proposed assessment element reached consensus in Meaningfulness, while no assessment elements reached consensus in Participation. The duplicated assessment item, which previously reached consensus in Participation in round 2  also reached consensus in Meaningfulness in round 3.At the end of round 3, 9 of the 11 proposed additional descriptors in Stage 2 reached consensus. This information was subsequently used to recreate the MPH figure to incorporate the consensus additional descriptors Fig. . A detaiThis study explored opportunities to improve person-centred goal setting at the point-of-care in home care, using the MPH as a framework to link comprehensive assessment and dialogue-based goal setting. Through a modified eDelphi process, investigators mapped the items from a comprehensive assessment tool mandated for use in Ontario home care to the six domains of the MPH and explored opportunities to adapt or expand comprehensive assessment elements and/or MPH domains. Findings from this study showed that 189 of the 201 interRAI HC elements successfully mapped to the six MPH domains, with Bodily Functions, Daily Functioning and Mental Wellbeing being the most represented of all six domains. A total of 10 elements reached consensus in No Pillar of Best Fit, while the remaining 12 elements did not reach consensus. Similarly, additional assessment elements and MPH descriptors, considered important to health assessment and useful in clarifying the underlying aspect of each MPH domain, were proposed. Taken together, these findings provide valuable insight into the potential for integration of the MPH framework with the interRAI HC comprehensive assessment tool to support more individualized and holistic care planning at the point-of-care in home care.The expert panel reached agreement on mapping 94% of the assessment elements drawn from the interRAI HC to the six domains of the MPH. Furthermore, the panel did not identify any additional domains which should be added to the framework. This level of agreement highlights the potential use of this framework to help structure comprehensive and person-centred assessment conversations around a broader definition of health, while building on existing international best practices in standardized assessment of home care client needs. Taking advantage of the MPH or comparable frameworks to provide a clear structure to guide a conversational assessment, care planning and goal setting approach, may facilitate the delivery of more individualized care which addresses the range of care needs across population groups. An approach like this is aligned with the intended assessment approach outlined by interRAI in their assessment manuals but is not always seen in practice , 43.There was a disproportionate mapping of assessment elements to the Bodily Functions, Daily Functioning and Mental Wellbeing domains, leaving MPH domains of Meaningfulness and Participation underrepresented. Participants were asked to suggest supplementary assessment elements to address potential gaps in the Meaningfulness and Participation domains. While the expert panel members proposed a range of suggestions, only two additional elements achieved consensus in both these domains. This may suggest that expert panel members found it challenging to propose assessment elements in these domains or that members did not have a unified understanding or definition of Meaningfulness and Participation, making it difficult to come to consensus. This is particularly evident given the duplicative assessment item which was proposed and reached consensus in both domains. These findings may also be reflective of the entrenched nature of the conventional bio-medical model of health across health and social care settings, thus placing limits on one’s ability to visualize health outside of known medically focused health domains . The resOur findings are consistent with other comparable studies conducted in the older adult population. In a systematic review that sought to map the domains of 67 commonly used assessment tools to evaluate frailty in older adults, it was observed that while all the tools included assessment elements in the biological domains, only nine tools included elements assessing social connections and social support, despite known links on the importance of these factors towards the conceptualizations of frailty . In anotThis study has implications for comprehensive care planning in home and community care. As demand rises for models of care that support more integrated health and social care service delivery , comprehNext steps for this research will involve co-designing tools and resources to support dialogue-based comprehensive assessment and goal setting around ‘life care’ needs. The co-design work will be completed in partnership with home care clinicians, leveraging study findings to integrate the interRAI HC, MPH domains, additional descriptors and complementary assessment tools into a person-centred care planning process at the point-of-care in home care.While the MPH allowed us to categorize the interRAI assessment elements within holistic health domains, it should be noted that the MPH was developed in the Netherlands using the Dutch language and later translated to English. It is possible that aspects of the Dutch language could contain words that cannot be adequately translated into the English language leading to potential biases. While we sought to recruit participants with firsthand experience of the interRAI HC and/or MPH framework, there were no formal inclusion criteria to ensure all participants were starting with the same knowledge base, which may have influenced the study findings. As the majority of our expert panel members were from a single Canadian province, the generalizability of study findings may be limited, given differences in how care is delivered across provinces and across countries. However, as the interRAI HC is used across Canada and in several countries, there is potential to validate this mapping exercise in other jurisdictions using similar methods. The strengths of this study include use of the Delphi method, which allowed for the engagement of a diverse group of experts across a range of perspectives critical to person-centred care planning in home care – older adults and caregiver, health and social care providers, and researchers. Another strength of this study is that the findings can be adopted to potentially expand the clinical utility of the interRAI HC at the point-of-care, building on existing and mandated standardized comprehensive assessment practices in Ontario and elsewhere.Using an eDelphi approach which included experts with a range of perspectives, we found that most interRAI HC assessment elements mapped onto MPH domains representing physical and mental health, with domains representing social needs like participation and meaningfulness agreed on to be underrepresented by assessment elements. This led to the proposal of new assessment elements and domain descriptors to expand the scope of comprehensive assessment and provide greater clarity between the domains representing ‘life care’ needs through an expanded definition of health. These findings will be used to co-design a dialogue-based approach to comprehensive assessment and goal setting around ‘life care’ needs that has the potential to optimize the care planning process for older adult clients, caregivers and home care providers through a more person-centred lens.Below is the link to the electronic supplementary material.Supplemental File 1: Sample Stage 1 ReportSupplemental File 2: Summary of Proposed Assessment Elements for Underrepresented My  Positive Health Pillars *note top bolded row is summary statement of all similar grouped suggestions belowSupplemental File 3: List of Proposed Assessment Elements and Proposed Additional Descriptors for Underrepresented My Positive Health domains and non-consensus assessment elements, respectively


Adolescents with emotional dysregulation are at risk for self-injury. Antipsychotics are often used to manage these symptoms.The aim of the present case is to show the use of cariprazine as an effective drug for emotional dysregulation and impulsivity in a 17-year-old adolescent girlCase reportThe patient was a 17-year-old female admitted to in patient psychiatric unit for a self-harm attempt due to sertraline overdose. She was being followed up for self-injury, anxiety and eating disorder symptoms. Her treatment was sertraline 200 mg, diazepam 20 mg per day and olanzapine 15 mg per day. With this medication she had gained up to 7 kgs in 4 months. A progressive change was made with cariprazine up to 3 mg and olanzapine was reduced to 2.5 mg at night. With this adjustment the patient did not present worsening in anxiety levels, with adequate impulse control and being able to perform emotional regulation strategies.1A receptors and an antagonist at the 5-HT2B receptors, with moderate affinity for adrenergic, histaminergic, and cholinergic receptors reducing the likelihood of side effectsAlthough it has no indication in patients under 18 years of age, it shows a case of good tolerance and efficacy for the management of impulsivity by improving emotional regulation. Cariprazine is an atypical antipsychotic that works through partial agonism on dopaminergic receptors, serotonin 5-HTNone Declared