SMN1 gene and a variable number of SMN2 , inversely related to the severity. The amazing results of the available treatments have made compelling the need of prognostic biomarkers to predict the progression trajectories of patients. Besides the SMN2 products, few other biomarkers have been evaluated so far, including some miRs.Spinal muscular atrophy (SMA) is a neuromuscular disorder characterized by the degeneration of the second motor neuron. The phenotype ranges from very severe to very mild forms. All patients have the homozygous loss of the SMN2 copies, SMN2 full-length transcript levels in blood and age (SMA-score).We performed whole miRNome analysis of muscle samples of patients and controls (14 biopsies and 9 cultures). The levels of muscle differentially expressed miRs were evaluated in serum samples (51 patients and 37 controls) and integrated with -5).Over 100 miRs were differentially expressed in SMA muscle; 3 of them  were significantly upregulated in the serum of patients. The severity predicted by the SMA-score was related to that of the clinical classification at a correlation coefficient of 0.87 . Spinal muscular atrophy (SMA) is an autosomal-recessive neuromuscular disorder, characterized by the degeneration of the α-motor neurons of the ventral horns of the spinal cord. The severity of the infantile forms is classically ranked into types I–III, according to the age of onset and the maximum motor milestone achieved . AccordiSMN1 gene, located in 5q13 (SMN1 is present (SMN2), which produces insufficient levels of the SMN protein. Due to an alternative splicing, SMN2 is mainly transcribed into an isoform lacking exon 7 (SMN-del7) and then translated into an unstable protein , more commonly found in the less severely affected patients , 20-22mers non-coding RNAs. miRs are involved in most cellular processes: these regulate gene expression through mRNA degradation or translational inhibition, mainly by binding cis-regulatory elements present in the 3′UTR of mRNAs . Among mSMN2 products, either transcripts or protein,  transcript levels, SMN2 copy number and age at sampling, markedly improving the phenotypic predictive value of SMN2 copy number assessment alone.We identified three deregulated miRs  that have been integrated in a composite score (SMA-score), including Muscle biopsies from seven SMA patients  were obtained from the Italian Telethon Network of Genetic Biobanks, held at Istituto Neurologico Carlo Besta in Milan. The characteristics of subjects are specified in SMN1; the latter was a type I subject, compound heterozygote for the c.439_443delGAAGT (p.Glu147SerfsTer2) variant.Muscle cell cultures (five from SMA patients and four from controls) were obtained from the Telethon Biobank or set in-house, as previously reported . Four paSMN2 copy number assessment and SNP (rs121909192 and rs1454173648) genotyping; whole blood samples were collected from 45 patients for total RNA extraction, and 51 serum samples were available for small RNA extraction.51 SMA patients were enrolled  and age .This study was approved by the Ethics Committee of Fondazione Policlinico Universitario IRCCS “A. Gemelli” .For SMA mice, the original breeding pairs of SMNΔ7 mice were purchased from Jackson Laboratory (stock number 005025). The colony was maintained by interbreeding carrier mice, and the offspring were genotyped by PCR assays on tail DNA according to the protocols provided by Jackson Laboratory. According to the ARRIVE guidelines, procedures were carried out to minimize discomfort and pain in compliance with national (D.L. 116 Suppl 40/1992 and D.L. 26/2014) and international guidelines and laws . The experimental protocols were approved by the Ethics Committee of the Fondazione IRCCS Istituto Neurologico C. Besta and by the Italian Ministry of Health (protocol numbers: 962/2016-PR and 1039/2020-PR).2 atmosphere. For myotube differentiation, we have used a standard protocol of serum deprivation (5% FBS) for 2 weeks.Myoblasts (passages from 5 to 15) were cultured in high-glucose Dulbecco Modified Eagle’s Medium (DMEM), 20% fetal bovine serum (FBS), 100 u/ml of penicillin, 100 mg/ml of streptomycin, 2 mM L-glutamine, 10 ng/ml of epidermal growth factor (EGF), and 10 µg/ml of bovine insulin in 5% COSH-SY5Y (human neuroblastoma) were already present in-house for previous studies and were tested for mycoplasma contamination. We verified the identity of SH-SY5Y cell line by evaluation of neuronal phenotype, following differentiation with 10 pM retinoic acid for 7 days. Cells were cultured in 1:1 DMEM/Ham’s F12 nutrient medium with 20% FBS, 100 u/ml of penicillin, 100 mg/ml of streptomycin, and 2 mM L-glutamine.The patients included in the present study were in routine clinical follow-up in the four participating Italian referral neuromuscular centers . Subjects were evaluated by expert neurologists/pediatric neurologists/physiotherapists: SMA type was first attributed to each patient, according to the usual classification (types I–IV). Three of us  were requested to assign each patient to a SMA subtype, based on the clinical data, according to the decimal classification for types I and II . For typTruSeq Small RNA Sample Preparation kit (Illumina). Next-generation sequencing (NGS) miRNome analysis was performed by Illumina Genome Analyzer (GAIIX) platform.Total RNA from muscle biopsies and myoblast/myotube cultures was extracted by TRIzol Reagent (Life Technologies) as specified in the manufacturer’s protocol. Libraries were obtained through the For miRNome analysis, we have used the following pipeline. The sequencing raw data (.bcl files) were processed by the Illumina Casava software (v1.8.0) to convert the data into fastq files . The fastq files (31-base single-end reads) were first filtered by quality using the FASTX-toolkit  and then trimmed to remove the adapter from their 3′ end . Only reads longer than 15 bases were retained and mapped on the miR-precursor sequences annotated in the miRBase repository (v19). The Bowtie2 algorithm was used for the alignment, allowing no more than two mismatches. Quantification, TMM normalization, and significant differential expression test of the known mature miRs were performed using the edgeR package (v2.4.1). Only miRs with >1 count per million (cpm) in at least one condition and in a minimum number of samples (depending on group size) were retained. Multiplicity correction was performed by applying the Benjamini–Hochberg method on the p-values to control the false discovery rate (FDR). The significantly up- and downregulated miRs were selected at FDR < 0.05.SMN2 copy number and RNA analyses were carried out as previously reported , according to the manufacturer’s protocol. RT-PCR was performed by the High Capacity cDNA Reverse Transcription Kit (Thermo Fisher Scientific). SMN2 transcript levels were assessed as previously reported (Whole blood was collected in PAXgene blood RNA tubes (BD Biosciences) and total RNA extracted by the reported .miRCURY RNA Isolation Kit – Biofluids (Exiqon). RT-PCR was performed by Universal cDNA synthesis kit II (Exiqon). For both protocols, manufacturer’s instructions were followed.miRs were extracted from serum by Pick-&-Mix miRNA PCR Panel 96-well); UniSp6 was used as calibrator (miRCURY LNA primers). miRs with Ct <34 were considered as expressed.Commercial relative qPCR assays were purchased at Exiqon  of primers was established by the OligoAnalyzer 3.1 tool . In case of forward oligo Tm <60°C, the latter was optimized by adding a (GACT)n tail at the 5′ end. For external standard construction, we proceeded as previously described . For in vivo experiments, antagomiRs were resuspended in artificial cerebrospinal fluid .miR-181a-5p, miR-324-5p, miR-451a mimics and scramble, and the respective antagomiRs were purchased at Exiqon (miRvana Paris RNA extraction kit (Ambion). RT-PCR was performed by High Capacity cDNA Reverse Transcription Kit (Applied Biosystems) or Universal cDNA synthesis kit II (Exiqon) for mRNAs or miRs, respectively. miR-181a-5p, miR324-5p, miR-451a, and SMN2 transcript  levels were quantified as described above.SH-SY5Y cells were transfected with three different concentrations (50–100–200 nM) of miR-181a-5p, miR-324-5p, miR-451a mimics or scramble. Transient transfections were performed through Lipofectamine 2000 (Invitrogen), according to the manufacturer’s protocols. Both total and small RNAs were extracted by the SMN2 genes.At postnatal day 1 (P1), SMA-like pups  were cryo-anesthetized and injected with 5 μl of 0.1 nmol of each specific antagomiR, into the cerebral lateral ventricle. Injections were performed with a pulled capillary needle under the guidance of a transilluminator as reported  All the Sequencing Analysis Software 6 (Applied Biosystems).We have amplified the genomic regions of interest by PCR in a final volume of 12.5 µl using the 2X GoTaq Hot Start Colorless Mastermix (Promega) and 0.4 µM of each primer pair . The ampRelative qPCR data were analyzed using RealTime StatMinerVersion 4.1 software and Benjamini–Hochberg FDR method. Grubbs’ test was employed to exclude the outliers. miR levels in patients and controls were compared by non-parametric tests (Wilcoxon test); miRs were identified as significantly differentially expressed at FDR <0.05.Absolute qPCR data were analyzed by Statgraphics Centurion XV software (StatPoint Inc). miR levels in patients and controls were compared by Mann–Whitney U test, setting α value at 0.05. While in relative qPCR a large number of miRs were analyzed simultaneously, in absolute qPCR experiments the levels of each miR were evaluated separately; for this reason, the FDR threshold was not applied. To rule out possible false-positive results, we opted for increasing the number of samples in each group only for significant miRs (p<0.05) or showing a trend of significance.SMN2 transcripts, SMN2 copy number), setting SMA type as dependent variable. Receiver operating characteristic (ROC) curves were constructed by SPSS 18.0 software; the cutoff value of single miR or their sum was identified according to the highest values of sensitivity and specificity.For clinical and molecular correlations, continuous variables were compared by linear regression models. Multiple regression analysis was used to correlate clinical severity and molecular parameters  and 37 age- and sex-matched controls . Most mi–4, –4, We evaluated sensitivity and specificity of the quantification of the SMA-miRs by using the ROC curves: the highest predictive value was found for miR-181a-5p, with 75% and 61% of sensitivity and specificity, respectively .Some miRs were previously reported to be differentially expressed in serum samples of SMA patients  . We evalSMN2 copy number determination alone provided a moderate accuracy when related to SMA type . When including also SMN2-fl levels and the sum of SMA-miRs as covariates, R2 further raised up to 67.04% ; more importantly, when considering only patients < 6 years, R2 raised to 72.17% . The equations describing the multivariate models were as follows.We evaluated whether SMA-miR levels in serum could improve the accuracy of phenotype prediction with respect to the available molecular biomarkers. All ages:SMN2-fl + 0.5417 * #SMN2 +0.00002 * SMA-miRs.SMA type = 0.2473 + 0.0013 * age (months) + 0.0013 * <6 years:Age SMN2-fl + 0.4398 * #SMN2 +0.00001 * SMA-miRs.SMA type = –0.0700 + 0.0175 * age (months) + 0.0021 * < 6 years; the correlation coefficient was 0.90, and R2 80.31  for the whole group and 0.87  for patients < 6 years  the treatment of patients has uncovered novel phenotypes that do not fall in any of the classical forms ; (2) theSMN2 copy number, alongside two alternative splicing-modulating variants , four belonged to the myomiRs: miR-1 and miR-133 family levels inversely correlate with myogenic differentiation/proliferation status ; miR-208SMN1  and has SMN1  and muriSMN1 . AdditioSMN1 , suggestSMN1 . How miRSMN1 ; conversSMN1  indicateSMN2, may exert a loco-regional effect in muscle and have, at the same time, an at-distance-effect following secretion.In this study, we used the unbiased dataset above to identify candidate SMN-independent biomarkers. We first tested >100 miRs in a small cohort of patients and controls to get the shortlist of potential biomarkers. Most miRs were not detectable in serum, indicating the integrity of the sarcolemma in SMA, differently from other neuromuscular conditions such as Duchenne muscular dystrophy . Only thRegarding the possible pathophysiological function of the SMA-miRs, to our knowledge, few data are available on the role of miR-324-5p in skeletal muscle: a single study reported the upregulation in human CD56+ myoblasts, during differentiation , again sMore information is available regarding the role of miR-451a: an increase was found in aged muscle , whereasIf confirmed in other studies with more therapeutic or pathogenic purposes, our data suggest that systemic therapeutic approaches increasing SMN levels also in skeletal muscle may provide additional benefits to SMA patients, and that miR-181a-5p (and/or miR324-5p) modulation might be a potential target for combinatorial treatments in addition to SMN modulation.SMN2 mRNAs  . Of thesN2 mRNAs , the resSMN2 copy number assessment, which is roughly predictive of the clinical severity in individual patients. Even more critical are patients with three SMN2 copies whose severity may range from type I to type III (1.9 to 3b in our cohort).One of the most relevant results of our study is the development of the SMA-score. The global spreading of newborn screening programs for SMA has made compelling the identification of tools with good predictive power of the clinical severity . So far,SMN2 variants (rs121909192 and rs1454173648) modulate the inclusion efficiency of exon 7 into mature mRNA, .Thank you for submitting your article "SMA-miRs  are overexpressed in spinal muscular atrophy skeletal muscle and serum samples" for consideration by The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.Essential revisions:General comments:1. Data that is listed as 'available on request' or 'data not shown', should be provided in a Supplementary file either with the journal or a 3rd party repository (figshare or similar). In this age of almost unlimited file space, all data reported should be directly presented to the reader.2. Figures should be redone with open boxes so that all of the data points can be easily seen.3. This Italian cohort of authors should be commended for their preparation of the manuscript in English. However, there are many sections (such as paragraph 4 of the introduction) that would be greatly improved by a careful proofread by a native English speaker.4. One abbreviation of microRNA, either miR or miRNA, should be used throughout the paper.5. Background information on what miRNA are and their biological affect would be useful.6. It is unclear what 51 serum/RNA/DNA samples means. Does it simply mean the authors collected 51 samples, then isolated RNA and DNA from it? Or were samples received with both RNA and DNA already isolated?7. Exact p values should be listed uniformly throughout the paper (some figures have asterisks or section have p<0.05).Specific CommentsAbstract8. Under results, add that the SMA-score improved prediction to > 80% for those under age 6.9. Under Discussion – it seems premature to speculate that the role of the differentially altered miRs was in programs of satellite cell differentiation. Keep in mind that the muscle biopsies sampled primarily muscle fibers and that satellite cells in those biopsies were quiescent, rather than the active proliferating form they take as myoblasts. Is it not also possible that these miRs target other key genes in mature myofibers? In addition, the paper really did not delve into role(s) of SMA in muscle per se, and did not try to link SMA1/2 levels to expression of the miRs identified. Thus, to me at least, any comment about function of SMA in muscle seems inappropriate for the abstract for this paper.Introduction10. The authors do not describe what SMN1/2 encodes, what its biological function is, and why genetic disruption of its expression is so detrimental to muscle function. A brief paragraph providing some general background on SMN would be appreciated for readers not familiar with SMA. Additional notes of onset, severity and phenotype differences between SMA I-III would also be useful to provide some additional background for the disease.11. Paragraph #2 of the introduction should be removed or worked into other portions of the paper.Methods12. If possible, a more clear definition of what the authors mean by 'first stages' using, for example, clinical staging criteria, would improve the manuscript.13. What passage numbers were use for cell cultures? How were the primary myoblasts isolated and stored (i.e. was CD56+ screening used)? These are important for people that may wish to try to replicate your study.14. Please list the exact local ethics committee  and approval number.15. Under 'Samples', add a reason that those controls were selected for the studies. Under discussion, review whether selection of these controls could be a confound.16. Please provide a method for isolating/freezing myoblasts or cite your prior work if you have published these techniques.17. Under 'Patients', were the authors involved in assigning SMA types blinded to the patient's diagnosis?18. Under 'Whole miRome Sequencing', what filters were used . Are the raw read data available? Were they deposited in NIH GEO or other databases?19. Under 'Statistical Tests' please clarify if an FDR threshold was applied for non-parametric tests (Mann-Whitney U-test). Also, please expand on how the multivariate analysis was performed in sufficient detail that others could use the sama analysis technique.Results and Discussion20. p values reported for miR-324 and 451 in Results section for Figure 3 do not match those listed on the figures for Figure 3 .21. A significant weakness of the manuscript is that the experiments with injection of miRs into ventricles of the brain did not include controls to confirm that the miRs influenced mRNA or protein levels in the central nervous system. The most logical place to look for this disease of lower motor neurons would be spinal cord. Also unclear is why the miR were delivered to the central nervous system rather than skeletal muscle where they arose. Conceptually, any effects of the miRs identified in muscle and the circulation would be most likely to be evident in muscle or, possibly, at the nerve terminal; alternatively, circulating miRs could influence gene expression at any location in the body. I do not know if miRs cross the blood brain barrier.22. It is quite difficult to figure out whether muscle or serum levels of miRs were used in the multivariable regression. The text of the results and discussion should be revised accordingly.23. Relative abundance is one key parameter to consider when evaluating biological significance of miR expression. A comment regarding which of the differentially expressed miRs are highly expressed would be appropriate. The myoMirs are generally highly expressed in muscle and would be expected to be included among the highly expressed miRs in this dataset.Reviewer #1 (Recommendations for the authors):In this manuscript, the authors aimed to define a set of micro-RNAs (miRs) that were differentially expressed in patients with spinal muscular atrophy (SMA), to determine whether any of these miRs had roles in the disease, to validate prior data on altered miR expression in muscle of SMA patients with mutations of SMA 1, and to use information on miR levels in serum as a biomarker to improve the accuracy with which disease severity was predicted.Strengths of the study include examination of miRs as a potential disease modifier in muscle biopsy samples and serum from a relatively large number of participants studied for relatively rare condition, properly controlled analysis to identify differentially expressed miRs, well controlled cell cultures studie of effects of those miRs on SMA 1 expression and an interesting algorithm for increasing disease severity prediction.Experiments testing effects of injection into cerebral ventricles showed no effect of miRs on survival of SMA δ-7 mice, but did not report levels of these miRs in spinal cord or effects of the injection on known targets in spinal cord tissues thus limiting interpretation of the data.If independently validated using a separate cohort, these findings may improve counseling and personalized treatment of patients with SMA.The manuscript would be considerably improved if the following points were addressed.General comments:The authors refer to multiple sets of data that has not been included in the manuscript. These data should be added as supplemental material.Figures should be redone with open boxes so that all of the data points can be easily seen.The manuscript would benefit from careful editing for English, typographical errors and punctuation.Overall, while the data from the manuscript are very interesting, it is a bit unfocused and includes experiments that address several different questions such as which miRs are differentially expressed in muscle, whether these changes are observed in serum, whether changing expression of these miRs in the nervous system influences disease progression, and whether circulating miRs could be a clinically useful biomarker for disease severity.Specific CommentsAbstractUnder results, add that the SMA-score improved prediction to > 80% for those under age 6.Under Discussion – it seems premature to speculate that the role of the differentially altered miRs was in programs of satellite cell differentiation. Keep in mind that the muscle biopsies sampled primarily muscle fibers and that satellite cells in those biopsies were quiescent, rather than the active proliferating form they take as myoblasts. Is it not also possible that these miRs target other key genes in mature myofibers? In addition, the paper really did not delve into role(s) of SMA in muscle per se, and did not try to link SMA1/2 levels to expression of the miRs identified. Thus, to me at least, any comment about function of SMA in muscle seems inappropriate for the abstract for this paper.MethodsUnder 'Samples', add a reason that those controls were selected for the studies. Under discussion, review whether selection of these controls could be a confound.Please provide a method for isolating/freezing myoblasts or cite your prior work if you have published these techniques.Under 'Patients', were the authors involved in assigning SMA types blinded to the patient's diagnosis?Under 'Whole miRome Sequencing', what filters were used . Are the raw read data available? Were they deposited in NIH GEO or other databases?Under 'Statistical Tests' please clarify if an FDR threshold was applied for non-parametric tests (Mann-Whitney U-test).Results and DiscussionA significant weakness of the manuscript is that the experiments with injection of miRs into ventricles of the brain did not include controls to confirm that the miRs influenced mRNA or protein levels in the central nervous system. The most logical place to look for this disease of lower motor neurons would be spinal cord. Also unclear is why the miR were delivered to the central nervous system rather than skeletal muscle where they arose. Conceptually, any effects of the miRs identified in muscle and the circulation would be most likely to be evident in muscle or, possibly, at the nerve terminal; alternatively, circulating miRs could influence gene expression at any location in the body. I do not know if miRs cross the blood brain barrier.It is quite difficult to figure out whether muscle or serum levels of miRs were used in the multivariable regression. The text of the results and discussion should be revised accordingly.Relative abundance is one key parameter to consider when evaluating biological significance of miR expression. A comment regarding which of the differentially expressed miRs are highly expressed would be appropriate. The myoMirs are generally highly expressed in muscle and would be expected to be included among the highly expressed miRs in this dataset.Reviewer #2 (Recommendations for the authors):Abiusi et al., describe a novel pipeline for predicting severity of infantile spinal muscular atrophy (SMA). They use muscle biopsies and primary cell cultures as well as serum from individuals with SMA. For additional studies, they use an SMA mouse model with miRNA anti-sense injections. They conclude their new model was able to improve prediction of phenotypic severity when related to patient subtype and stratified by age. While the paper has a solid base, I think there are areas that need to be clarified, strengthened or carefully considered. I thank the authors for doing this work and putting together the manuscript. I hope the following will help solidify and improve aspects of the paper.Strengths– SMA is a deleterious genetic disease and the ability to improve prediction of severity would be an important clinical outcome.– Use of miRNA sequencing to find biomarkers is a solid experimental approach.– Coupling biomarkers with genetic outcomes is a logical predictive strategy.– Follow-up testing on previously proposed biomarkers.Weaknesses– There is a disparity in FDRs used for various miRNA analyses. Reasons for differences in the accepted FDR should be explained and also may have affected downstream analyses. FDRs listed for miRNome was said to be selected at p<0.01 in the methods, with muscle having 99, myoblasts having 20 and myotubes having 19 DE miRNA. However, using their stated FDR of p<0.01, two of their selected predictors, miR-181 and miR-324 do not meet that threshold for being differentially expressed. Then there is a switch to accepting an FDR of p<0.05. Uniformity of data analyses is crucial for biomarker studies and this is a major oversight.– For the first tier round of qPCR follow up, how and why where those individuals selected out of the complete cohort? Having 1 SMA1 and 9 SMA II seems like a very oddly weighted group breakdown.– How was type I error limited for the absolute qPCR? FDRs of relative qPCR were stated to be an FDR but nothing is mentioned for absolute qPCR. This is important considering 50 assays were completed for these outcomes.– A table showing all the outcomes of the relative and absolute qPCR would provide a great deal of information and transparency. For example, the miRNA selected as 'predictors' for SMA were upregulated, but biomarkers can also be down-regulated.– The link of SMN being depleted in muscle having primary effects is intriguing, but should be interpreted with caution. The importance of having a tonic motor connection with a healthy motor neuron cannot be underestimated. Changes in differentiation factors in proliferating myoblasts and forming myotubes related to myomiR are often seen in other pathological conditions that result from denervation . Additionally, only these factors were considered and not any phenotypic measurements of differentiating myotubes. The data are intriguing, but directed and focused studies are needed to investigate how muscle may or may not be regulated by global SMN1 reductions.– There is no description of when the biopsies of the SMA patients were taken. As they say they were taken from the quadriceps during the first stages of the disease, this could be quite variable depending on fiber type of the muscle group the biopsy was taken from, time diagnosis was confirmed and the age at the time of biopsy. Clarification of these points, as well as for the primary tissue cultures, is important.– It is not listed where the serum from individuals with SMA came from. Please explain if these were obtained from a repository similar to the muscle tissues or if separate process was conducted.– The disparity in group sizes from type I to type II and III is unfortunate. It is understood the difference in disease disparity causes this, but it is a limitation in the search for prognostic biomarkers to have such unbalanced group differences.– Assignment of patients to the SMA subgroup is vague and likely difficult to understand for non-clinicians. Explicit descriptions of how each individual used the clinical data available to stratify patients would be appreciated.– The authors do not describe what SMN1/2 encodes, what its biological function is, and why genetic disruption of its expression is so detrimental to muscle function. A brief paragraph providing some general background on SMN would be appreciated for readers not familiar with SMA. Additional notes of onset, severity and phenotype differences between SMA I-III would also be useful to provide some additional background for the disease.– Data that is listed as 'available on request' or 'data not shown', should be provided in a Supplementary file either with the journal or 3rd party repository (figshare or similar). In this age of almost unlimited file space, all data reported should be directly presented to the reader.– Paragraph #2 of the introduction should be removed or worked into other portions of the paper.– This Italian cohort of authors should be commended for their preparation of the manuscript in English. However, there are many sections (such as paragraph 4 of the introduction) that would be greatly improved by a careful proofread by a native English speaker.– One abbreviation of microRNA, either miR or miRNA, should be used throughout the paper.– Background information on what miRNA are and their biological affect would be useful.– It is unclear what 51 serum/RNA/DNA samples means. Does it simply mean the authors collected 51 samples, then isolated RNA and DNA from it? Or were samples received with both RNA and DNA already isolated?– Exact p values should be listed uniformly throughout the paper (some figures have asterisks or section have p<0.05).– What passage numbers were use for cell cultures? How were the primary myoblasts isolated and stored (i.e. was CD56+ screening used)? These are important for people that may wish to try to replicate your study.– Please list the exact local ethics committee  and approval number.– p values reported for miR-324 and 451 in Results section for Figure 3 do not match those listed on the figures for Figure 3 .–Related to figures, improved opacity to allow the reader to see the individual data points would be appreciated.Reviewer #3 (Recommendations for the authors):The manuscript by Abiusi E, Infante P and co-workers describes a study to discover and validate miRNAs in muscle of mice models of SMA and biopsies and cultures of SMA patients. Furthermore, the authors study their presence in serum of 51 patients and report an attempt to correlate results in serum miRNAs with SMN2 copy number, FL transcripts and age of the SMA patients under study. The resulting correlation is named SMA-score.The authors managed to develop an appropriate streamline to detect and validate candidate miRNAs. Data of specific miRNAs is interesting but at present there is lack of longitudinal analysis or trajectories to ascribe them a value as dynamic biomarkers. These issues should be investigated to ascribe a potential role of miRNAs as biomarkers and to further validate the utility of the SMA-score.SMN2 analysis of these patients was appropriate including the variants rs121909192 and rs1454173648 as positive modifiers (that were discarded in the cases under study) strengthen the accuracy of this variable to include into the score. Further investigation of the entire sequence of the SMN2 of patients may provide additional information about prediction of severity and would be a next step to help improving accuracy of SMA prediction and possibly will be included in the score.1) Title. I would edit the title to reflect a more realistic scenario of this investigation that is the discovering and validation of miRNAs. The application of the SMA-score is in my opinion preliminary (see below further comments).2) Abstract. Edits are also necessary in the abstract. i.e. there is incomplete information given that a part of these studies were performed in mice models; wording: "evaluate its controversial pathogenic role" is not addressed in this work and the conclusion that "may provide additional benefit to SMA patients" is not new; also "the SMA-score could be crucial for the prognostic assessment of pre-symptomatic patients" is rather speculative given the lack of data in pre-symptomatic patients regarding the candidates miRNAs and the score application. In summary, the abstract should be more focused in the issues of the study.3) Methods. The authors should clarify the meaning of "first stages", does mean that all the samples were taken at the beginning of manifestations? Perhaps a Table  can be included with a summary of the samples studied with additional information of first stages.4) Discovering and data of specific miRNAs is interesting and the analysis is adequate. The lack of longitudinal analysis or trajectories to ascribe them a value as dynamic biomarkers should be commented.5) The cohort of type I patients is small in my opinion to establish a correlation (only four patients). But it could be interesting to try a correlation between the values of type II versus type III cases to determine if patients with three copies acquire (type III) or not (type II) the ability for autonomous walking.6) There are four patients in the list of type II and III disease with two SMN2 copies. In absence of positive modifier variants (both nomenclatures can be included for clarity in the paper) these "outliers" may influence the final score? i.e. PT11 2.70 vs. PT 38 2.12 >6 years (according to data set). Values should be with period not commas, the same applies to the equation.7) What explanation is feasible to explain the correlation differences in > or < 6 years? Can the authors clarify scores >6 years or < 6 years from the same patient?8) Discussion: neurofilament should be referenced :932-944. doi: 10.1002/acn3.779. PMID: 31139691; PMCID: PMC6530526.9) The authors provide additional evidence that muscle is involved in SMA but as they said in Discussion, there is some heterogeneity in the samples. The statement "Taken together, these data suggest that systemic therapeutic approaches increasing SMN levels also in skeletal muscle tissues may provide additional benefits to SMA patients" remains speculative according to what is discussed below this statement about miR-324-5p, miR-451a and miR-181a-5p. I would try to elaborate a statement after the discussion of the role in muscle of the miRNAs detected with a more realistic conclusion.10) "More information is (are) available".11) Please clarify some aspects of the multivariate analysis performed. Selection of variables that are introduced in the multivariate analysis can be done by a full model  or selection of only those variables with significant value in the bivariate linear regression (one by one). The authors state: "Continuous variables were compared by linear correlations. Multivariate analysis was used to correlate severity and molecular parameters ". Which variables were significant if compared one by one?12) Please clarify in Table 1 the meaning of P in the column of absolute qPCR.13) The statement "The inclusion of SMA-miRs, age and SMN2-fl levels has almost doubled the accuracy of the severity prediction of SMN2 copy number alone, from about 43% to 82%." should be better discussed. Data of calculations on SMN2 alone (according to the authors apparently is 43%) should be provided because is confusing. Looking at the data set Table, in type III there are 13 with 4 copies (54%), 9 with 3 copies (37%) and 2 with 2 copies (8%). In a total of 18 type II patients the score was calculated and 15 (83%) had 3 SMN2 copies as expected in these type of patients. Adding the 4 type I patients the total number of patients with calculated score is 46 .14) I found 7/24 (30%) cases with type III disease with an insufficient SMA-score (less than 2.5 assuming in type II disease according to the score). It is possible to discuss these results?15) As the authors mentioned in the last paragraphs, data in newborns (control and SMA) and trajectories with longitudinal data and evolution of the miRNAS should be investigated to ascribe a potential role as a biomarker and to validate the utility of the score.16) Even though the variants rs121909192 and rs1454173648 were discarded, a sentence may be included mentioning that investigation of the entire sequence of the SMN2 of patients (perhaps with a reference) may provide additional information about prediction of severity and would be a next step to help improving accuracy of prediction. Essential revisions:General comments:1. Data that is listed as 'available on request' or 'data not shown', should be provided in a Supplementary file either with the journal or a 3rd party repository (figshare or similar). In this age of almost unlimited file space, all data reported should be directly presented to the reader.Data previously indicated as “not shown” have been included in the manuscript, mainly as supplementary information (see supplementary figures 1-6 and tables).2. Figures should be redone with open boxes so that all of the data points can be easily seen.As requested, figures have been re-drawn. In order to better appreciate the whole distribution of miRNA levels in patients and controls, we have changed the Y-axis scale of figure 3 from linear to exponential. The same approach has been used for the novel supplementary figures 2 and 3.3. This Italian cohort of authors should be commended for their preparation of the manuscript in English. However, there are many sections (such as paragraph 4 of the introduction) that would be greatly improved by a careful proofread by a native English speaker.We have extensively revised the manuscript both for the form and possible typos.4. One abbreviation of microRNA, either miR or miRNA, should be used throughout the paper.As requested, we opted for miR as a unique abbreviation for miRNA.5. Background information on what miRNA are and their biological affect would be useful.As requested, we added some sentences and references regarding this matter.6. It is unclear what 51 serum/RNA/DNA samples means. Does it simply mean the authors collected 51 samples, then isolated RNA and DNA from it? Or were samples received with both RNA and DNA already isolated?We have specified the number of each specimen available in the Method section.7. Exact p values should be listed uniformly throughout the paper (some figures have asterisks or section have p<0.05).We have uniformly listed the p values throughout the paper.Specific CommentsAbstract8. Under results, add that the SMA-score improved prediction to > 80% for those under age 6.9. Under Discussion – it seems premature to speculate that the role of the differentially altered miRs was in programs of satellite cell differentiation. Keep in mind that the muscle biopsies sampled primarily muscle fibers and that satellite cells in those biopsies were quiescent, rather than the active proliferating form they take as myoblasts. Is it not also possible that these miRs target other key genes in mature myofibers? In addition, the paper really did not delve into role(s) of SMA in muscle per se, and did not try to link SMA1/2 levels to expression of the miRs identified. Thus, to me at least, any comment about function of SMA in muscle seems inappropriate for the abstract for this paper.The abstract has been almost completely rephrased.Introduction10. The authors do not describe what SMN1/2 encodes, what its biological function is, and why genetic disruption of its expression is so detrimental to muscle function. A brief paragraph providing some general background on SMN would be appreciated for readers not familiar with SMA. Additional notes of onset, severity and phenotype differences between SMA I-III would also be useful to provide some additional background for the disease.This point has been addressed in the Introduction section. We agree with the reviewer that further information on SMN function in muscle would be appreciable but, unfortunately, most detrimental mechanisms induced by SMN reduction are unknown, in particular in skeletal muscle but also in motor neurons.11. Paragraph #2 of the introduction should be removed or worked into other portions of the paper.This point has been addressed in the Introduction section.Methods12. If possible, a more clear definition of what the authors mean by 'first stages' using, for example, clinical staging criteria, would improve the manuscript.This point has been addressed, by adding Supplementary table 1. “First stages of disease” were defined as “as onset of the first clinical signs that prompted the diagnostic workflow”. Unfortunately, to the best of our knowledge, no clinical staging criteria are available, besides the usual classification of SMA.13. What passage numbers were use for cell cultures? How were the primary myoblasts isolated and stored (i.e. was CD56+ screening used)? These are important for people that may wish to try to replicate your study.Passages of cell cultures were between 5 and 15. For isolation of myoblasts, we used CD56 selection, as indicated in the ref Zanotti et al., 2007. These aspects were specified in the Methods.14. Please list the exact local ethics committee  and approval number.This information has been specified as requested in the Methods section.15. Under 'Samples', add a reason that those controls were selected for the studies. Under discussion, review whether selection of these controls could be a confound.This point has been addressed in the Methods section.16. Please provide a method for isolating/freezing myoblasts or cite your prior work if you have published these techniques.As reported above (point 13.) we have included our ref Zanotti et al., where experimental details were specified.17. Under 'Patients', were the authors involved in assigning SMA types blinded to the patient's diagnosis?Data on the clinical performance of patients, evaluated by functional scale scores and motor ability, are sufficient to assign a decimal SMA subtype, even if the gross classification (type I-III) is unknown. In this sense, the utility of molecular tests is very limited, due to the finding of the same genotype at the SMN locus, in patients with markedly different phenotypes.18. Under 'Whole miRome Sequencing', what filters were used . Are the raw read data available? Were they deposited in NIH GEO or other databases?The pipeline analysis has been specified in Methods. Raw data of miRSeq have been deposited at NCBI-SRA database (BioProject PRJNA748014). The significantly up- and down-regulated microRNAs were selected at False Discovery Rate (FDR) <0.0519. Under 'Statistical Tests' please clarify if an FDR threshold was applied for non-parametric tests (Mann-Whitney U-test). Also, please expand on how the multivariate analysis was performed in sufficient detail that others could use the sama analysis technique.Due to the analytical workflow we used for absolute qPCR, i.e. a progressive increase in the number of samples tested, in case of first tier significant results, we established an α-value at 0.05, without applying an FDR threshold. The rationale behind this strategy was that the number of miRNAs that were selected for the second tier absolute qPCR was small, thus minimizing the risk of false positive results, due to the number of variables. This aspect has been detailed in Methods section.Results and Discussion20. p values reported for miR-324 and 451 in Results section for Figure 3 do not match those listed on the figures for Figure 3 .Figure 3 has been replaced with a new version, as requested. Indeed, the proper p-values are those indicated in the text. Those indicated in the figures were originated in a previous version of the graphs. We apologize.21. A significant weakness of the manuscript is that the experiments with injection of miRs into ventricles of the brain did not include controls to confirm that the miRs influenced mRNA or protein levels in the central nervous system. The most logical place to look for this disease of lower motor neurons would be spinal cord.We agree with the reviewer that the putative mode of action of the SMA-miRs/antagomiRs has not been explored at all in our study. These aspects were, in our opinion, out of focus with respect to the main aim of our project that was essentially aimed at identifying SMN-independent biomarkers. For similar reasons, we did not check whether miR level modulation could affect SMN levels in CNS or namely in spinal cord. Additionally, two lines of evidences were in support of this strategy: (1) as shown in the present study, SMA-miRs do not modulate SMN levels in human cells of neuronal origin; (2) since the survival of treated mice is not affected by antagomiRs, we think unlikely a direct effect on SMN levels that, based on preclinical and clinical data, would have led to a positive effect on mice phenotype.Also unclear is why the miR were delivered to the central nervous system rather than skeletal muscle where they arose. Conceptually, any effects of the miRs identified in muscle and the circulation would be most likely to be evident in muscle or, possibly, at the nerve terminal; alternatively, circulating miRs could influence gene expression at any location in the body. I do not know if miRs cross the blood brain barrier.With our preliminary experiments (but more detailed studies on miR/antagomiR system are ongoing) we aimed at evaluating a specific hypothesis, that is the retrograde effect of SMA-miRs on CNS. We agree with the reviewer that it is conceivable that, based on the finding of secreted miRs in serum, these molecules are likely exert a systemic effect: to reduce possible confounding variables, we decided to restrict miR modulation to a specific target tissue, namely the CNS, rather than evaluating the loco-regional effect in skeletal muscle. However, several studies report the ability of extra-cellular vesicles to cross the blood brain barrier and to deliver their content to the CNS .22. It is quite difficult to figure out whether muscle or serum levels of miRs were used in the multivariable regression. The text of the results and discussion should be revised accordingly.This point has been addressed as requested23. Relative abundance is one key parameter to consider when evaluating biological significance of miR expression. A comment regarding which of the differentially expressed miRs are highly expressed would be appropriate. The myoMirs are generally highly expressed in muscle and would be expected to be included among the highly expressed miRs in this dataset.To address this point of the reviewer, we have included in Supplementary Table 4 also logCPM of miRNA levels in muscle samples, as obtained by NGS. Since miRNA levels in serum were determined by absolute qPCR, the relative abundance of the different miRs is reported as no. of molecules/μl of serum in figures and tables. As hypothesized by the reviewer, myo-miRs were abundantly expressed in muscle samples, at significantly higher levels in patients. Intriguingly, these miRNAs were not differentially expressed in serum, suggesting that, differently from the SMA-miRs, myo-miRs are not actively secreted.Reviewer #1 (Recommendations for the authors):General comments:The authors refer to multiple sets of data that has not been included in the manuscript. These data should be added as supplemental material.The following materials have been included as supplementary:Supplementary file 1: demographic and clinical characteristics of patients who underwent to biopsySupplementary file 2: molecular and clinical details of the single patientsSupplementary file 4: detailed list of differential miRs, including the logCPMAdditionally, the raw data of NGS runs have been uploaded in a public repository Figures should be redone with open boxes so that all of the data points can be easily seen.This point has been addressed as requested. In order to magnify the distribution of miR levels in our cohort, we have replaced the linear scale with an exponential.The manuscript would benefit from careful editing for English, typographical errors and punctuation.This point has been addressed as requested.Overall, while the data from the manuscript are very interesting, it is a bit unfocused and includes experiments that address several different questions such as which miRs are differentially expressed in muscle, whether these changes are observed in serum, whether changing expression of these miRs in the nervous system influences disease progression, and whether circulating miRs could be a clinically useful biomarker for disease severity.Specific CommentsAbstractUnder results, add that the SMA-score improved prediction to > 80% for those under age 6.Under Discussion – it seems premature to speculate that the role of the differentially altered miRs was in programs of satellite cell differentiation. Keep in mind that the muscle biopsies sampled primarily muscle fibers and that satellite cells in those biopsies were quiescent, rather than the active proliferating form they take as myoblasts. Is it not also possible that these miRs target other key genes in mature myofibers? In addition, the paper really did not delve into role(s) of SMA in muscle per se, and did not try to link SMA1/2 levels to expression of the miRs identified. Thus, to me at least, any comment about function of SMA in muscle seems inappropriate for the abstract for this paper.See the response to specific comments #9.MethodsUnder 'Samples', add a reason that those controls were selected for the studies. Under discussion, review whether selection of these controls could be a confound.This point has been addressed as requested in the Methods section.Please provide a method for isolating/freezing myoblasts or cite your prior work if you have published these techniques.See response to item 16 in the Specific comments.Under 'Patients', were the authors involved in assigning SMA types blinded to the patient's diagnosis?See response to item 17 in the Specific comments.Under 'Whole miRome Sequencing', what filters were used . Are the raw read data available? Were they deposited in NIH GEO or other databases?Under 'Statistical Tests' please clarify if an FDR threshold was applied for non-parametric tests (Mann-Whitney U-test).See response to item 19 in the Specific comments.Results and DiscussionA significant weakness of the manuscript is that the experiments with injection of miRs into ventricles of the brain did not include controls to confirm that the miRs influenced mRNA or protein levels in the central nervous system. The most logical place to look for this disease of lower motor neurons would be spinal cord. Also unclear is why the miR were delivered to the central nervous system rather than skeletal muscle where they arose. Conceptually, any effects of the miRs identified in muscle and the circulation would be most likely to be evident in muscle or, possibly, at the nerve terminal; alternatively, circulating miRs could influence gene expression at any location in the body. I do not know if miRs cross the blood brain barrier.See response to item 21 in the Specific comments.It is quite difficult to figure out whether muscle or serum levels of miRs were used in the multivariable regression. The text of the results and discussion should be revised accordingly.See response to item 22 in the Specific comments.Relative abundance is one key parameter to consider when evaluating biological significance of miR expression. A comment regarding which of the differentially expressed miRs are highly expressed would be appropriate. The myoMirs are generally highly expressed in muscle and would be expected to be included among the highly expressed miRs in this dataset.See response to item 23 in the Specific comments.Reviewer #2 (Recommendations for the authors):Abiusi et al., describe a novel pipeline for predicting severity of infantile spinal muscular atrophy (SMA). They use muscle biopsies and primary cell cultures as well as serum from individuals with SMA. For additional studies, they use an SMA mouse model with miRNA anti-sense injections. They conclude their new model was able to improve prediction of phenotypic severity when related to patient subtype and stratified by age. While the paper has a solid base, I think there are areas that need to be clarified, strengthened or carefully considered. I thank the authors for doing this work and putting together the manuscript. I hope the following will help solidify and improve aspects of the paper.Strengths– SMA is a deleterious genetic disease and the ability to improve prediction of severity would be an important clinical outcome.– Use of miRNA sequencing to find biomarkers is a solid experimental approach.– Coupling biomarkers with genetic outcomes is a logical predictive strategy.– Follow-up testing on previously proposed biomarkers.Weaknesses– There is a disparity in FDRs used for various miRNA analyses. Reasons for differences in the accepted FDR should be explained and also may have affected downstream analyses. FDRs listed for miRNome was said to be selected at p<0.01 in the methods, with muscle having 99, myoblasts having 20 and myotubes having 19 DE miRNA. However, using their stated FDR of p<0.01, two of their selected predictors, miR-181 and miR-324 do not meet that threshold for being differentially expressed. Then there is a switch to accepting an FDR of p<0.05. Uniformity of data analyses is crucial for biomarker studies and this is a major oversight.We are very grateful to the reviewer for noticing our mistake, due to a typo. The FDR for all analyses was selected <0.05. The text has been modified accordingly in the Methods section.– For the first tier round of qPCR follow up, how and why where those individuals selected out of the complete cohort? Having 1 SMA1 and 9 SMA II seems like a very oddly weighted group breakdown.Thank you very much for the constructive comment, we specified this information in the Results. At that stage, due to the lack of preliminary data, we opted for the more homogenous sub-cohort of patients, in terms of age and severity, to reduce potential biases in miR quantification. The type I patient was the only available at the time.– How was type I error limited for the absolute qPCR? FDRs of relative qPCR were stated to be an FDR but nothing is mentioned for absolute qPCR. This is important considering 50 assays were completed for these outcomes.See response to Specific comments #19.– A table showing all the outcomes of the relative and absolute qPCR would provide a great deal of information and transparency. For example, the miRNA selected as 'predictors' for SMA were upregulated, but biomarkers can also be down-regulated.As requested we have included a supplementary table (#5) reporting the results of the single miRNAs in relative and/or absolute qPCR.– The link of SMN being depleted in muscle having primary effects is intriguing, but should be interpreted with caution. The importance of having a tonic motor connection with a healthy motor neuron cannot be underestimated. Changes in differentiation factors in proliferating myoblasts and forming myotubes related to myomiR are often seen in other pathological conditions that result from denervation . Additionally, only these factors were considered and not any phenotypic measurements of differentiating myotubes. The data are intriguing, but directed and focused studies are needed to investigate how muscle may or may not be regulated by global SMN1 reductions.Thank you very much for the comment. We fully agree that our data alone do not allow drawing any conclusion on the pathogenic role of skeletal muscle in SMA, but this was not the primary aim of the study that has been designed for biomarker discovery. However, besides data obtained in murine models or those in human whole muscle samples, some in vitro studies on human muscle cell cultures have demonstrated primitive alterations of patients’ satellite cells, including the inability of SMA myotubes to sustain motor neuron innervation, when co-cultured with wild type motor neurons .– There is no description of when the biopsies of the SMA patients were taken. As they say they were taken from the quadriceps during the first stages of the disease, this could be quite variable depending on fiber type of the muscle group the biopsy was taken from, time diagnosis was confirmed and the age at the time of biopsy. Clarification of these points, as well as for the primary tissue cultures, is important.See response to item 12 in the Specific comments.– It is not listed where the serum from individuals with SMA came from. Please explain if these were obtained from a repository similar to the muscle tissues or if separate process was conducted.We agree with the reviewer. Patients were enrolled ad hoc in the participating neuromuscular centers. These patients are or were in routine clinical follow-up. This aspect has been specified in the Methods section.– The disparity in group sizes from type I to type II and III is unfortunate. It is understood the difference in disease disparity causes this, but it is a limitation in the search for prognostic biomarkers to have such unbalanced group differences.We fully agree with the reviewer. However, it is unlikely to succeed in balancing the sub-populations, in such wide phenotypic spectrum of disease, in terms of age of onset, severity and relative abundance of the different forms. Additionally, the total number of type I patients in our study has been limited also by the difficulties in sampling adequate amounts of blood from such young and/or hypotonic patients. Indeed, we had to exclude some other patients due to the lack of serum samples.– Assignment of patients to the SMA subgroup is vague and likely difficult to understand for non-clinicians. Explicit descriptions of how each individual used the clinical data available to stratify patients would be appreciated.In the Introduction, we specified some details on how SMA patients are classified, based on the clinical severity. Since this classification has been published several years ago, we preferred not to detail the single items used for scoring patients. The refs have been specified in Introduction and Methods section.– The authors do not describe what SMN1/2 encodes, what its biological function is, and why genetic disruption of its expression is so detrimental to muscle function. A brief paragraph providing some general background on SMN would be appreciated for readers not familiar with SMA. Additional notes of onset, severity and phenotype differences between SMA I-III would also be useful to provide some additional background for the disease.See response to Specific comments #10. As requested, we added some details on SMN.– Data that is listed as 'available on request' or 'data not shown', should be provided in a Supplementary file either with the journal or 3rd party repository (figshare or similar). In this age of almost unlimited file space, all data reported should be directly presented to the reader.See response to item 1 in the General Comments.– Paragraph #2 of the introduction should be removed or worked into other portions of the paper.– This Italian cohort of authors should be commended for their preparation of the manuscript in English. However, there are many sections (such as paragraph 4 of the introduction) that would be greatly improved by a careful proofread by a native English speaker.See response to item 3 in the General Comments.– One abbreviation of microRNA, either miR or miRNA, should be used throughout the paper.See response to item 4 in the General Comments.– Background information on what miRNA are and their biological affect would be useful.See response to item 5 in the General Comments.– It is unclear what 51 serum/RNA/DNA samples means. Does it simply mean the authors collected 51 samples, then isolated RNA and DNA from it? Or were samples received with both RNA and DNA already isolated?See response to item 6 in the General Comments.– Exact p values should be listed uniformly throughout the paper (some figures have asterisks or section have p<0.05).See response to item 7 in the General Comments.– What passage numbers were use for cell cultures? How were the primary myoblasts isolated and stored (i.e. was CD56+ screening used)? These are important for people that may wish to try to replicate your study.See response to item 13 in the General Comments.– Please list the exact local ethics committee  and approval number.See response to item 14 in the General Comments.– p values reported for miR-324 and 451 in Results section for Figure 3 do not match those listed on the figures for Figure 3 .See response to item 20 in the General Comments.–Related to figures, improved opacity to allow the reader to see the individual data points would be appreciated.See response to item 2 in the General Comments.Reviewer #3 (Recommendations for the authors):1) Title. I would edit the title to reflect a more realistic scenario of this investigation that is the discovering and validation of miRNAs. The application of the SMA-score is in my opinion preliminary (see below further comments).The title has been rephrased as requested.2) Abstract. Edits are also necessary in the abstract. i.e. there is incomplete information given that a part of these studies were performed in mice models; wording: "evaluate its controversial pathogenic role" is not addressed in this work and the conclusion that "may provide additional benefit to SMA patients" is not new; also "the SMA-score could be crucial for the prognostic assessment of pre-symptomatic patients" is rather speculative given the lack of data in pre-symptomatic patients regarding the candidates miRNAs and the score application. In summary, the abstract should be more focused in the issues of the study.The abstract has been rephrased as requested.3) Methods. The authors should clarify the meaning of "first stages", does mean that all the samples were taken at the beginning of manifestations? Perhaps a Table  can be included with a summary of the samples studied with additional information of first stages.As requested, a supplementary table has been added (#1). See response to item # 12 of the Specific comments.4) Discovering and data of specific miRNAs is interesting and the analysis is adequate. The lack of longitudinal analysis or trajectories to ascribe them a value as dynamic biomarkers should be commented.See response to item # 8 of the minor comments.5) The cohort of type I patients is small in my opinion to establish a correlation (only four patients). But it could be interesting to try a correlation between the values of type II versus type III cases to determine if patients with three copies acquire (type III) or not (type II) the ability for autonomous walking.We agree with the reviewer that the type I cohort is very small. However, due to the difficult sampling and to the amount of biological specimen required for the different analyses reported in this study, we had to exclude 4 additional patients due to the lack of serum or RNA samples. Additionally, the spreading of experimental treatments has complicated the enrollment of further naïve patients.We re-evaluated with the referral clinicians the whole cohort and concluded that one of the patients has been erroneously attributed to type I while being type II. This aspect has been emended in table and figures, and the equations have been concordantly corrected. These modifications have led to a further improvement of the correlation between the SMA-score and the SMA decimal classification.As suggested by the reviewer, we compared SMA-miRs’ levels in type II and III patients with 3 SMN2 copies . The difference was not significant for any miR or the sum. However, the age at sampling was significantly higher in type III . In our opinion it would be more appropriate to compare age-matched groups to draw any conclusion.6) There are four patients in the list of type II and III disease with two SMN2 copies. In absence of positive modifier variants (both nomenclatures can be included for clarity in the paper) these "outliers" may influence the final score? i.e. PT11 2.70 vs. PT 38 2.12 >6 years (according to data set). Values should be with period not commas, the same applies to the equation.We have included an additional supplementary table (#2) with individual data for each patient, which has integrated and replaced the previous file “patient_database”. Of the mentioned type II patients, one was twin-sister of a type I male that were previously reported . The 2 other patients were confirmed, both in terms of clinical severity and SMN2 copy number/absence of splicing variants. Regarding the type III patient, due to homonymy, the number of SMN2 copies was erroneously attributed. Indeed, DNA sample of this patient was not available. These data have been amended in figures, table, and equations.7) What explanation is feasible to explain the correlation differences in > or < 6 years? Can the authors clarify scores >6 years or < 6 years from the same patient?2 is 80.31 . These aspects have been pointed in the manuscript.In supplementary table 2, we have indicated the SMA score obtained with both equations for patients below 6 years. Indeed, the correlation between the scores is very high, since the correlation coefficient is 0.90 and R8) Discussion: neurofilament should be referenced :932-944. doi: 10.1002/acn3.779. PMID: 31139691; PMCID: PMC6530526.See response to item #7 in minor comments.9) The authors provide additional evidence that muscle is involved in SMA but as they said in Discussion, there is some heterogeneity in the samples. The statement "Taken together, these data suggest that systemic therapeutic approaches increasing SMN levels also in skeletal muscle tissues may provide additional benefits to SMA patients" remains speculative according to what is discussed below this statement about miR-324-5p, miR-451a and miR-181a-5p. I would try to elaborate a statement after the discussion of the role in muscle of the miRNAs detected with a more realistic conclusion.Thank you very much for the comment. We have rephrased the Discussion accordingly.10) "More information is (are) available".Thank you very much for the comment. We have corrected the typo.11) Please clarify some aspects of the multivariate analysis performed. Selection of variables that are introduced in the multivariate analysis can be done by a full model  or selection of only those variables with significant value in the bivariate linear regression (one by one). The authors state: "Continuous variables were compared by linear correlations. Multivariate analysis was used to correlate severity and molecular parameters ". Which variables were significant if compared one by one?SMN2-fl levels, we have also evaluated SMN-del7 and SMN-total transcripts. The inclusion of these variables in the multivariate analyses led to a reduction in both significance and strength of association, since p-value increased and R2 decreased. Thus, we do not agree that by simply adding variables the R2 value increases. Similarly, the single miRNA performed worse than the miR-sum. As reported in the Results, the strongest contribution to the model was not surprisingly provided by SMN2 copy number and SMN2-fl levels.Indeed, even if it has not been reported, in the present study, besides Besides the contribution of the single variables in the definition of the equation, in our opinion, the correlation of two completely independent variables  is unequivocally strong, up to levels that have never been raised so far in SMA biomarker research. Nonetheless, we fully agree that these data need to be validated in independent cohort, as well as, longitudinal evaluation of SMA-miR levels is required. We remind that we have shown in our previous studies that longitudinal levels of SMN2-fl transcripts are very stable over more than one year . This aspect has been pointed in the Discussion.12) Please clarify in Table 1 the meaning of P in the column of absolute qPCR.The p-value has been obtained by comparing miR levels in patients and controls by Mann-Whitney U-test. This aspect has been specified in the table legend and in Methods.13) The statement "The inclusion of SMA-miRs, age and SMN2-fl levels has almost doubled the accuracy of the severity prediction of SMN2 copy number alone, from about 43% to 82%." should be better discussed. Data of calculations on SMN2 alone (according to the authors apparently is 43%) should be provided because is confusing.2=52.45%, p<10-5, n=41; Figure 5 – figure supplement 1A). This has been specified in the Results and in the statistical analysis section of the Methods. Additionally, we have related SMN2 copies with the decimal SMA classification that has raised the R2 up to 67.00% . While SMN2 copy number alone provides sufficient predictability in the case of patients with 2 or 4 copies, the relevance in patients with 3 copies is very limited. Indeed, in our cohort, the SMA decimal classification ranges in these patients ranges from 1.9 to 3b. The correlation of the SMA score with the decimal classification in this subgroup of patients (n=21), is significant with a correlation coefficient of 0.55 .The correlation between SMA Type and SMN2 copy number has been evaluated by a linear regression model , 9 with 3 copies (37%) and 2 with 2 copies (8%). In a total of 18 type II patients the score was calculated and 15 (83%) had 3 SMN2 copies as expected in these type of patients. Adding the 4 type I patients the total number of patients with calculated score is 46 .The different biological samples were not available for all patients. As requested, this has been specified in the Methods. Additionally, for each statistical test, the number of samples available has been detailed.14) I found 7/24 (30%) cases with type III disease with an insufficient SMA-score (less than 2.5 assuming in type II disease according to the score). It is possible to discuss these results?As reported in supplementary file 2, in the updated version of the equation, the number of type III with low SMA-score is of 1 patient . This is likely due to the SMN2-fl levels, which appear to be quite low.15) As the authors mentioned in the last paragraphs, data in newborns (control and SMA) and trajectories with longitudinal data and evolution of the miRNAS should be investigated to ascribe a potential role as a biomarker and to validate the utility of the score.We agree with the reviewer. Longitudinal data are mandatory for any biomarker study.16) Even though the variants rs121909192 and rs1454173648 were discarded, a sentence may be included mentioning that investigation of the entire sequence of the SMN2 of patients (perhaps with a reference) may provide additional information about prediction of severity and would be a next step to help improving accuracy of prediction.As requested, a sentence and a reference have been added.


IntroductionA neck of femur fracture is a rare injury in the pediatric population and is of foremost importance, as it is associated with a high rate of complications. It usually occurs due to high-velocity trauma or a fall from a height. There is a scarcity of data on risk factors and their role in the prognostication of avascular necrosis. The purpose of the study was to retrospectively analyze the association of various risk factors with avascular necrosis (AVN) of the femoral head in patients with a neck of femur fracture in the pediatric age group.Material and methodsThe study included 21  pediatric patients with a neck of femur fracture treated at a university-level hospital. The patients were followed for a minimum of one year and the clinico-radiological outcome was analyzed using Ratliff criteria. The association of AVN with age, gender, side, fracture type, and injury with treatment delay, type of reduction, and type of internal fixation used was studied.ResultsThe mean age of the treated patients was 11 (±3.178) years (range=5-16 years). Avascular necrosis was seen in four patients and coxa vara occurred in two of them. A statistically significant association was seen between the Delbet fracture type and avascular necrosis, and three out of four cases of AVN were a Type I fracture . Three out of six patients having concomitant skeletal or other organ injuries developed AVN . The rate of AVN was higher in patients who were managed after 48 hours of initial injury but no statistically significant correlation was found . No statistically significant association with AVN was found between gender, age, type of reduction (closed/open), or the implant used (cannulated screws/k-wires).ConclusionsMultiple independent factors may have a role in the development of AVN of the femoral head in children. Prognostication should not be based on a single factor. Statistically significant results in this study have shown that the type of fracture and concomitant skeletal or other organ injuries are important risk factors and should be kept in mind. All independent risk factors must be noted and should be considered while prognosticating the outcome of a child with a neck of femur fracture. Femur neck fractures in children represent less than 1% of all pediatric fractures and are often due to a high-velocity injury . There iVascularity of femoral headPediatric neck femur fractures are associated with a high rate of complications due to the presence of terminal blood supply to the capital femoral epiphysis. The three vessels supplying the femoral head are the medial femoral circumflex artery (MFCA), lateral femoral circumflex artery (LFCA), and artery of ligamentum teres (ALT). Trueta described that vascular supply to the femoral head is dynamic and changes with the age of the child . VasculaAvascular necrosis (AVN) of the femoral headAVN of the femoral head is one of the most dreadful complications and its rate varies from 0 to 77% in the literature ,9. VarioVarious other complications seen in these fractures are malunion, delayed union, premature physeal closure, growth arrest, coxa vara, coxa valga, and infection. Definitive early treatment with anatomical reduction is imperative to achieve satisfactory outcomes while preventing complications -15.Literature reports multiple risk factors for the development of AVN but with no consensus and no established causal relationships . This stA retrospective analysis of all children with a neck femur fracture from January 2017 to March 2019 was done after taking approval from the institutional ethical review board at a university-level teaching hospital. The inclusion criteria were children less than or equal to 16 years of age with a neck of femur fracture. Children with pathological fractures, open fractures, or nonunions were excluded from the study. Children with a follow-up of less than one year after surgery were also excluded.Medical records of all these patients were analyzed for demographic characteristics, mechanism of injury, associated injuries to other organ systems, fracture type, injury, and treatment duration. The type of reduction and method of fixation were also analyzed. The fracture type was classified according to Delbet’s classification Figure  16]..16].Treatment strategyAs per institutional protocol, emergent management of trauma patients was done. Definitive treatment was done after the stabilization of the patient. Closed reduction was attempted first, and open reduction was done after two attempts of failed closed reduction. Internal fixation was done using partially threaded cannulated cancellous screws. Kirschner wires were used for fixation in patients with age less than five years Figures -4. A hipOutcome assessmentThe clinic-radiological outcome was assessed at the final follow-up using Ratliff's clinical and radiographic evaluation score Table  1]..1].Radiographs were evaluated for fracture union, arthritic changes, neck-shaft angle, and avascular necrosis. The AVN was further classified according to the Ratliff classification system Figure  1]..1].Statistical analysisAssociation of AVN with age, gender, side, fracture type, injury to treatment delay, type of reduction, and type of internal fixation used was studied. Evaluation of the risk factors was done using logistic regression analysis. A receptor operating characteristic curve (ROC) was used to determine the cut-off value in cases of a numerical variable. In categorical variables, subgroup analysis was done using logistic regression. Student’s t-test and chi-square tests were also used in subgroup analysis. A p-value of less than 0.05 was considered significant. All analyses were done using the Statistical Package for the Social Sciences software .Injury characteristicsTwenty-one patients  with a neck of femur fracture and satisfying the inclusion criteria were studied. The patient's demographic profile and fracture characteristics were noted Table . The meaOperative characteristicsThe mean time from initial injury to surgery was 88.76 hours (range 14-355 hours). The most common reason long injury to surgery duration was delayed presentation. Few patients had in-hospital delays to ensure the safety of children with severe combined injury or unstable circulatory conditions. All patients underwent definitive treatment either by open reduction (12 patients) or close reduction (9 patients) with internal fixation using partially threaded cannulated cancellous screws (20 patients) or Kirschner wires (1 patient).Operative outcomeAll fractures united with two (9.52%) going into varus malunion. These patients did not report any pain, limitation of movement, or avoidance of any other activity.AVN was seen in four out of 21 cases (19.04%) and three of them had segmental involvement (Ratliff type II AVN) Figure  while onThe hip outcome was good in 17 (80.9%) cases, three (14.28%) of them had a fair outcome, and one (4.76%) had a poor outcome based on Ratliff’s radiographic and functional evaluation score. All of the patients (4/21) with fair and poor outcomes had developed avascular necrosis. These patients had occasional pain with mild hip movement restriction and were able to carry out the normal activities.It was also found that three out of four patients who developed AVN had sustained a Delbet type 1 fracture and chances of developing this complication were found to be significantly more in this fracture pattern than others  Table .Three out of four patients who developed this complication had associated injuries to other organ systems or additional fractures Table . On statNo statistically significant association with AVN was found between gender, age, side, time to reduction (injury to treatment delay in hours), type of reduction (closed/open), or the implant used (cannulated screws/k-wires) Table . VariousFemur neck fractures are infrequently seen in children and a great amount of force is required to produce them. Most commonly (in approximately 50%), the injury is sustained after high-velocity trauma . Risk faFracture typeIn the present study, the Delbet type II fracture was the most common fracture pattern 47.61%). Dai et al. in their study of 44 children reported that more than half (25 out of 44) were of Delbet type II 1%. Dai e.Avascular necrosisAVN is the most critical factor that determines the prognosis of neck femur fractures. It is the most dreaded complication of this fracture and lacks effective treatment. The rate of AVN in this study was 19.04% (4/21). The rate of AVN of the femoral head reported in other studies varies from 0% to 77% ,9.Age and AVNA study by Moon ES et al. has shown that AVN was more common in the adolescent age group than in young children (30% vs 19%) . A similIn this study, three out of four cases of AVN were of age greater than 10 years but no statistically significant results were seen .Fracture type and AVNIn a meta-analysis of 360 patients by Moon ES et al., the occurrence of AVN was 38% of type I, 28% of type II, 18% of type III, and 5% of type IV fractures . AnotherSimilar results were found in this study, and three out of four patients who developed AVN had sustained a Delbet type 1 fracture. The chances of developing this complication were found to be significantly more in this fracture pattern than others  Tables -4.Associated injuries and AVNNeck of femur fractures are often associated with injury to other bones or other organ systems in the body. In this study, a concomitant injury was observed in six patients (28.57%). Dai et al. reported similar findings and combined injuries were found in 23% of the cases but there was no statistically significant result showing their association with the development of AVN . ContrarThe vascular damage to the supply of the femoral head is considered to take place during initial injury and fracture fragment displacement and is supported by few studies ,22. AssoInjury to treatment duration (delay) and AVNA study by Azam MQ et al. reported that there was a progressive increase in the incidence of AVN with delay in weeks following initial injury . They reSimilar findings were noted in this study, three out of four cases who developed AVN were operated on after 48 hours of injury. Even though the number of cases who developed AVN was more in late surgeries but the result was not statistically significant.Yeranosian M et al. in their systematic review of 30 studies comprising 935 patients reported that the rate of AVN was 4.2 times higher in patients who were operated on after 24 hours of injury than in patients who were operated on early [Early hip decompression and AVNIn a study by Bukva et al., early decompression of the hip has been shown to decrease the incidence of AVN in patients with fracture of the neck of the femur in the pediatric age group . PattersYeranosian M et al. in their systematic review of 935 patients also did not show a beneficial effect of capsular decompression on the rate of AVN .Type of reduction and AVNIn this study, the percentage of AVN was 25% (3 out of 12) in those who underwent open reduction as compared to 11% (1 out of 9) in cases who were managed with closed reduction. The difference was not statistically significant . Recent studies have suggested a lower incidence of AVN in patients treated with open reduction and internal fixation as compared to conservative management ,27-28. TMany surgeons desist from open reduction to avoid injury to the blood vessels supplying the femur head but the lateral epiphyseal vessel, a terminal branch of the medial circumflex femoral artery, runs along the neck and not in the capsule and therefore is not injured while doing anterior capsulotomy during open reductions. Ju et al. in their study of 58 patients reported that open reduction and internal fixation had better outcomes than closed reduction and internal fixation .ComplicationsCoxa vara was previously reported was found to be in 10% to 20% of children with a neck femur fracture . It is tPrevious studies have shown a non-union rate of 7%-10% in children with a neck femur fracture with predisposing factors like oblique fractures, type II and III fracture, inadequate fixation, and infections. Non-union of femur neck fracture was not seen in any patient in our study.According to previous studies, postoperative infection was found in 1% of patients, but it was not observed in any of the patients in our study. The limitations of the study are the small sample size and being a retrospective study with a short follow-up. Considering that only four patients developed AVN, the study is not adequately powered to predict the risk of AVN. Further large multicentered studies are needed to assess the association of various risk factors.Multiple independent factors may have a role in the development of avascular necrosis (AVN) of the femoral head in children. Prognostication should not be based on a single factor. Statistically significant results in this study have shown that the type of fracture and associated injuries are important risk factors and should be kept in mind. All independent risk factors must be noted and should be considered while prognosticating the outcome of a child with a fracture of the neck of the femur. Authors feel that to know the association of each independent risk factor better, there is a need for further, large sample-sized, multi-centric, prospective studies. Large sample size will help us decrease the margin of error and generalize results to the pediatric population.