Of the thousands of age-associated sites, only 350 sites were differentially methylated in the same direction in all cell types and validated in an independent longitudinal cohort. Genes close to age-associated hypomethylated sites were enriched for collagen biosynthesis and complement cascade pathways, while genes close to hypermethylated sites mapped to neuronal pathways. In silico analyses showed that in most cell types, the age-associated hypo- and hypermethylated sites were enriched for ARNT (HIF1β) and REST transcription factor (TF) motifs, respectively, which are both master regulators of hypoxia response. To conclude, despite spatial heterogeneity, there is a commonality in the putative regulatory role with respect to TF motifs and histone modifications at and around these sites. These features suggest that DNA methylation changes in healthy aging may be adaptive responses to fluctuations of oxygen availability.Age-associated DNA methylation in blood cells convey information on health status. However, the mechanisms that drive these changes in circulating cells and their relationships to gene regulation are unknown. We identified age-associated DNA methylation sites in six purified blood-borne immune cell types (naive B, naive CD4 Human aging is associated with site-specific changes of DNA methylation. Summary measures of DNA methylation called ‘epigenetic clocks’ are extensively used in aging research to estimate biological age . EpigeneResearch suggest that changes in DNA methylation with aging are regulated by specific mechanisms rather than by a stochastic drift . For exaA main obstacle in understanding mechanisms driving age-associated changes of DNA methylation is that most human studies were performed in mixed blood cell types. The few studies that investigated select immune circulating cells failed to propose a unifying biological hypothesis explaining predictable changes of DNA methylation with aging .We analyzed age-associated methylation in six purified blood-borne cell types sorted from peripheral blood mononuclear cells (PBMCs) from 55 donors of ages ranging from 22 to 83 years. To minimize the confounding of age-associated pre-clinical and clinical diseases, participants were ascertained to be healthy by trained health professionals according to strict clinical criteria. We looked for CpGs differentially methylated with aging in the same direction in multiple cell types. Next, in each cell type, we conducted enrichment analyses of genes close to age-associated CpGs. Finally, we looked for chromatin accessibility markers and transcription factor (TF)-binding sites close to the same age-associated CpGs. Our findings suggest that changes in methylation with aging are related to fluctuation of energetic metabolism during the life course.A principal component analysis (PCA) was performed on normalized DNA methylation data for all cell types from all the 55 donors . The PCA+ T cells (+ T cells (9–14% overlap) . The number of hypo- or hypermethylated sites varied considerably between cell types  with hig T cells . Using aoverlap) . Having ferences .Like other studies, we found that a significant proportion of age-hypomethylated CpGs were in the intergenic and open sea (>4 kb from CpG island) regions while age-hypermethylated CpGs were in promoters and CpG islands (Chi sq test p < 0.001) . AdditioRCAN1  and KLF14 (Krϋppel-Like Factor 14) show similar age-associated patterns in all cell types  and 404 (age-hypermethylated) sites in 5 or more cell types . Thus, mll types .Next, we wanted to investigate whether the top age-associated genes are the ones which are shared across cell types. For this we arranged the age-associated probes with decreasing order of adjusted p-value and looked at the annotated genes to identify the top 15 genes in each cell type . THSD4 ar = 0.49, p = 1.2e−09 and hypermethylated with age CpGs: r = 0.5, p = 6.9e−06 for average beta coefficients across six cell types, We hypothesized that the age-associated CpGs identified across the six immune cells in this cross-sectional study would also show longitudinal changes of the size and direction predicted. We used DNA methylation data (Illumina 450K microarray on DNA from buffy coats) assessed at baseline and 9- and 13-year follow-up in 699 participants of the InCHIANTI study . Of the + T cells, and monocytes  (n = 776) pointed to genes enriched in collagen biosynthesis, complement cascade, and GTPase pathways (left-most column in bottom panel of n = 404) were enriched for neural pathways previously implicated to brain aging along with G-protein-coupled receptors pathways  . Probes pathways   age-associated methylation sites. For B and CD4er sites . Both ager sites . No specer sites . These per sites  and stro, also named HIF1β) was associated with age-hypomethylated CpGs across most cell types (+ T cells where the top enriched motif was B-cell lymphoma gene 6 (BCL6). BCL6 code for a zinc finger TF that plays a critical role in the generation of memory and effector cells in acute infection (Specific TFs binding may induce loss of DNA methylation or bind DNA that is methylated . Throughll types . The onlnfection . Anothernfection .−27) that binds to selective inflammation-related genes, such as IL6 and STAT3 and stabilize their expression (Repressor Element 1-Silencing Transcription Factor (REST) was the TF motifs most frequently associated with age-hypermethylated CpGs in five of six cell types . Age-hyppression . We furtpression . HoweverThe recurring enrichment of ARNT and REST with age-associated CpGs observed across multiple cell types, despite relatively few shared genomic region locations, suggests a common mechanism of gene regulation. We found that only 17 and 44 age-associated hypo- and hypermethylated probes, respectively, shared ARNT or REST motifs across all cells , suggestARNT mRNA was significantly overexpressed in older age in three of the six cell types and REST mRNA showed a significant decrease of expression with age in most cell types  for the same cohort of donors from Novel and important conclusions arise from our observations. First, only few CpG sites are hypo- and hypermethylated with aging across all circulating cells while majority of the significant age-associated methylation changes are cell selective. Indeed, several CpGs show differential age methylation in opposite directions in different cell types and are unchanged in PBMC, suggesting that they may be missed when studying mixed cell samples. Noteworthy, age-related methylation differences in this cross-sectional study were strongly and significantly correlated with longitudinal age-associated methylation changes in an independent population.Second, age-associated hypomethylated sites were significantly enriched for active enhancers whereas age-hypermethylated sites were enriched for bivalent/polycomb regions, confirming previous findings in whole blood . Age-difARNT significantly increases with age in all cell types except monocytes, while mRNA coding for REST declines with aging in four cell types and shows no significant change in naive CD8+ T cells and NK cells. mRNAs coding for CTCF showed strong age association across numerous cell types  who were free of diseases (except controlled hypertension or history of cancer silent for >10 years), not on medications (except one antihypertensive drug), had no physical or cognitive impairments, non-smokers, weighed >110 lbs, had body mass index <30 kg/m2  study participants  buffer. Enriched cell populations were FACS (fluorescence-activated cell sorting) sorted by flow cytometry as per Human Immunophenotyping Consortium (HIPC) phenotyping panels  to the UCSC RefSeq genes (hg19), we grouped the locations into three categories: (1) promoter group – TSS 1500 (from 201 to 1500 bp upstream of TSS), TSS 200 (≤200 bp upstream of TSS), 5′UTR, first exon; (2) genebody – exons , exon intron boundary, intron and 3′UTR; and (3) intergenic probes. The first gene in the annotation package was considered. Probes were divided into three groups – within CpG islands (CGI), within CpG shore (0–2 kb from CGI), CpG shelf (2–4 kb from CGI), and open sea (>4 kb from CGI).Analyses were performed by the R minfi package . Probes β values using the R betareg function. p-values were adjusted for multiple testing (Benjamini–Hochberg [BH] adjusted p < 0.05). Probes with FDR p < 0.05 for age and FDR p > 0.05 for sex were considered age-differentially methylated CpGs. Beta-regression estimate value was used to group the age-associated probes as hypo- (Estimateage <0) or hypermethylated (Estimateage >0). The overlap of probes across multiple combinations of the six cell types was assessed using R package SuperExactTest (v.1.1.0)  .Based on the EPICarray annotation, genes were classified as differentially hypo- or hypermethylated with age. Genes with both age hypo- and hypermethylated CpGs were removed from the analysis. Enrichment analysis was performed by the tmodHGtest method in the tmod v.0.46.2 R package, comparing a foreground list of genes found in ≥5 cell types against reference gene set collections ‘Hallmarks’ and ‘Canonical Pathways’  from the Molecular Signature Database MSigDB (v.7.4) .q-value <0.05 was imposed to find the most significant pathways.For the gene enrichment analysis of the principal components, the top 500 CpG probes corresponding to the positive and negative directions along PC1, PC2, and PC3 were extracted and annotated to nearest gene as per the manufacturer’s annotation file. The ambiguous genes with probes associated with both positive and negative PC directions were removed from the analysis. The remaining genes were run through the abovementioned enrichment analysis pipeline. A filter based on ENCODE  were downloaded from Roadmap epigenomics project. Bedops tool was used to map the age-associated methylated sites to the respective chromHMM profiles. All Infinium MethylationEPIC array probes were also partitioned using each of the immune cell chromHMM profiles as controls.The 18-state chromHMM models  for various immune cells  is a population-based cohort of individuals ≥20 years old from the Chianti region of Tuscany, Italy (PMID: 11129752). The Italian National Institute of Research and Care on Aging Institutional Review Board approved the study protocol and all participants explicitly consented to participate. DNA methylation from 699 participants (1841 observations) was used for the analysis. CpG methylation of 485,577 CpGs was determined by the Illumina Infinium HumanMethylation450 BeadChip  and data processed by the R package ‘sesame’. Mean rates of change were estimated from 2 to 3 longitudinal timepoints.6 cells, depleted from ribosomal RNA and 50 ng was used for cDNA synthesis and library preparation. Libraries were sequenced for 138 cycles on Illumina HiSeq 2500. After adapter removal and end trimming of raw FASTQ files, transcript abundances were quantified with reference to hg19 transcriptome using kallisto 0.44 (with options --single -l 250 -s 25). Transcripts were aggregated to genes with tximport and filtered out if less than 10 TPM were detected in more than 33% of the samples. Linear regression models (~phase + age*sex) were used on TPM normalized expression values to study expression changes of selected TFs with age. Only the regression coefficient and p-value for the three TF genes – ARNT, CTCF, and REST were used in this study.Total RNA was extracted from 2 × 10OSF.Published SomaScan protein data from the same cohort of donors used in the present study were extracted to look for age-associated changes in seven cytokines  . Briefly This fundamental work advances our understanding of chromatin changes that may be associated with aging across six distinct immune cell types. It highlights a non-uniform process of expression of aging signatures while a core signature is preserved across different cell types. The research employs solid validated and robust analysis methodologies. The findings would be of interest to researchers studying DNA methylation clock and aging biology. 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: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 Carlos Isales as the Senior Editor. The reviewers have opted to remain anonymous.Thank you for submitting your article "Epigenetic signature of human immune aging: the GESTALT study." 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:1) A number of points require clarification as indicated by the reviewers. Please address each of these points in revision.2) Clarify the study is a reanalysis of previously published data to shed light on new patterns.Reviewer #1 (Recommendations for the authors):This is an interesting study that potentially identifies a single fundamental mechanism that regulates chromatin changes in aging from stochastic changes. The notion that the methylation changes are cell selective is an interesting concept.Building on the comments regarding circulating and tissue-resident cells, can the authors provide data to support or refute whether programs are consistent in the different compartments? It would strengthen the work to provide discussion on these points.The interpretation of the data relies on changes in genes related to hypoxia to support that the metabolic state of the cell determines outcomes. It would be useful to test this hypothesis which would be possible in vitro to determine if programs are indeed determined by metabolic states that in vivo differ in different microenvironments, or that cells are intrinsically differentially programmed.Although the samples were obtained from participants who were deemed 'clinically' healthy, were any finer criteria used to distinguish and cross-correlate the immune cell phenotype with the methylation changes? The identification of an inflammatory program in the data associated with aging is interesting. While it might occur that low-level inflammation is inherently associated with aging, distinguishing the two programs would be important in teasing the data apart. Thus, a current limitation of the work is the lack of cellular phenotypic and functional mapping corresponding to the molecular analysis to bring clarity to whether overlapping programs occur and inflammation contributes to driving aging normally, or whether separate programs usually occur in parallel but could overlap. Dissecting this apart further would strengthen the work.Reviewer #2 (Recommendations for the authors):1. The authors claimed that clustering by cell type (PC2) was stronger than by age. For the PCA, it would be great if the authors could explain what PC1 indicates and present the information about all PCs.2. It has been reported that sex-related differences contribute to immune cell aging . It is unclear how sex differences affect the dataset that the authors analyzed and how sex-adjusted β-regression was conducted.3. The authors identified 350 age-associated differentially methylated sites among all six immune cell types and compared them with other published studies. Do these sites overlap with the DNA methylation clock sites identified in PBMCs since these sites change in the same direction in separate cell populations? Also, only 10 of these 350 sites overlap with Horvath's pan-tissue epigenetic clock. Is there any factor that can explain this difference? For example, sequencing depth, coverage, etc?4. In the legend of Figure 2, the most significant genic probes are classified as -log10(padj)<10. Did the author mean -log10(padj)>10?5. It needs to be clarified how the top 15 genes were chosen. How many age-associated CpGs contribute to these 15 genes? Also, if more genes are considered, will more genes be shared among cell types?6. In Figure 3C and 3D, the differences in β coefficient in the InCHIANTI study are small . Are the differentially methylated sites called in GESTALT identified as differentially methylated in the original InCHIANTI study?7. In Figure 4C and Supp Figure 4, it seems both hypo- and hyper-methylated sites with age show the V-shaped pattern.8. It is unclear how the expression levels were measured. Expression levels from qPCR or RNA-seq need to be shown in addition to Supp Table 6. RNA-seq was mentioned in the method section, and if this was performed in this study, the quality metrics for the data need to be provided and the data need to be uploaded to GEO. The current GEO number (GSE184269) provided in this manuscript is linked to a published study and does not contain RNA-seq data.9. There are several places where the authors mentioned "data not shown". It may be better if these data could be presented in supplementary figures or tables.Reviewer #3 (Recommendations for the authors):Specific suggestions for Authors:1) As mentioned in the public review, certain claims should be toned down or placed in context.2) The authors need to make it clear in the introduction that this current study is based on the reanalysis of a data set they have published in 2021 and describe key findings and limitations of the initial study.3) It is not clear from the methods and figure legends that motif predictions were done on DMRs that could be found in at least 5 cell types, as only loosely mentioned in the text. Please clarify this point in methods and legends.4) Presumably, motif enrichment was performed against a genomic background. This information is not found in the methods and should be added.5) Motif enrichment analysis was done in windows of +200bp around DMRs. Please explain why this choice was made and whether a narrower window  would yield drastically different outcomes.6) Can the authors speculate on why they see enrichment for neuronal and pancreas gene ontology pathways related to conserved DNA methylation changes?7) Data should be shown in important instances like "We identified 35 genes that were hypomethylated with aging and had close by an ARNT motif in all six cell types (Data not shown). Ten of these genes  have been linked to hypoxia response (37-46). Similarly, we found 20 genes with probes hypermethylated with age and with REST motif in the vicinity in all six cell types (data not shown)." Please provide the information. Essential revisions:1) A number of points require clarification as indicated by the reviewers. Please address each of these points in revision.2) Clarify the study is a reanalysis of previously published data to shed light on new patterns.We have addressed the points raised by the three reviewers. The data analyzed in this manuscript were collected in the context of the GESTALT study, a study of biomarkers of aging that is run in parallel to the Baltimore Longitudinal Study of Aging at the clinical site of the National Institute on Aging Intramural Research Program in Baltimore. The senior author of this manuscript designed the study and has been the π of this project from the beginning. Part of the GESTALT cohort data was previously deposited in the public domain as requested by the previous publication journal. In particular, the methylation data was previously used to explore epigenetic differences between different types of circulating immune cells in a previous published study [1]. However, methylation data was never used previously to look at association with aging, and to explore whether some CpG sites are differentially methylated with aging in the same direction across various circulating cell types. Identification of such shared CpG sites can suggest mechanisms of their agerelated changes. We note that it is common that data collected in a cohort study are used for multiple analyses that explore different hypotheses.Reviewer #1 (Recommendations for the authors):This is an interesting study that potentially identifies a single fundamental mechanism that regulates chromatin changes in aging from stochastic changes. The notion that the methylation changes are cell selective is an interesting concept.Building on the comments regarding circulating and tissue-resident cells, can the authors provide data to support or refute whether programs are consistent in the different compartments? It would strengthen the work to provide discussion on these points.The interpretation of the data relies on changes in genes related to hypoxia to support that the metabolic state of the cell determines outcomes. It would be useful to test this hypothesis which would be possible in vitro to determine if programs are indeed determined by metabolic states that in vivo differ in different microenvironments, or that cells are intrinsically differentially programmed.Although the samples were obtained from participants who were deemed 'clinically' healthy, were any finer criteria used to distinguish and cross-correlate the immune cell phenotype with the methylation changes? The identification of an inflammatory program in the data associated with aging is interesting. While it might occur that low-level inflammation is inherently associated with aging, distinguishing the two programs would be important in teasing the data apart. Thus, a current limitation of the work is the lack of cellular phenotypic and functional mapping corresponding to the molecular analysis to bring clarity to whether overlapping programs occur and inflammation contributes to driving aging normally, or whether separate programs usually occur in parallel but could overlap. Dissecting this apart further would strengthen the work.We thank the reviewer for the insightful suggestion. To investigate further into the role of age-associated inflammatory phenotype, we analyzed the published protein data from the same cohort of donors to look for age-associated changes in seven cytokines [2]. For each cell type, all CpGs reported as significantly hypo- or hyper-methylated with age  were reanalyzed by separately adding each one of the seven pro-inflammatory cytokines Supplementary File 11. By comparing a model with a cytokine as explanatory variable (CpG ~ age + sex + cytokine) with another model without it (CpG ~ age + sex), we explored the robustness of age as explanatory variable of methylation, as well as possible mediating effects arising from pro-inflammatory cytokines.In the Supplementary File 11, columns (C-J) show that the age association remains significant for most CpGs, even after adding one of these inflammatory mediators into the model. Interestingly we find that for age associated hypermethylated sites in CD4 cells, 10% of the CpGs associated with age show significant association with TNFRSF1A in the model which implies an association of these methylated sites or genes with the cytokine production and/or release in the circulation. The remaining columns (K-Q) show the number of CpGs for which there’s a significant association between CpG and the target analyte (in the model adjusted for age and sex). As noted above, TNFRSF1A and TNFRSF1B are associated with more than 7000 CD4 age-associated hypermethylated CpGs, suggesting an important role of age-differential methylation in the pro-inflammatory state of aging. For other cell types  TNF-α appears to play a role. Fewer associations are observed for the remaining analytes.The new analysis has been added to the results and the description of the analysis has been added to the methods section.Reviewer #2 (Recommendations for the authors):1. The authors claimed that clustering by cell type (PC2) was stronger than by age. For the PCA, it would be great if the authors could explain what PC1 indicates and present the information about all PCs.We performed gene set enrichment analysis with the top 500 CpG probes corresponding to PC1, PC2 and PC3. Following this, the probes were annotated to nearby genes as per manufacturer’s annotation file and the genes which had probes with both positive and negative values for a PC were excluded. With the revised manuscript, we have provided a supplementary spreadsheet with columns providing information on the associated PC component and direction. A filter with q-value<1.e-5 was imposed to highlight the most significant pathways. PC1 genes are enriched for T cell receptor and Natural killer cells -associated pathways while PC2 shows enrichment of Hallmark IL2 STAT5 signaling and Reactome innate immune system. We conclude that PC1 contributes more towards separation of CD4, CD8 and NK cells from B cells, monocytes and granulocytes while PC2 separates the innate from the adaptive cells. The details have been added to the Results section (page 4) and the Methods section (page 18) along with the addition of Supplementary File 2.2. It has been reported that sex-related differences contribute to immune cell aging . It is unclear how sex differences affect the dataset that the authors analyzed and how sex-adjusted β-regression was conducted.We performed β regression with age and sex as two variables and in order to get the probes associated with age, we only selected the probes with adjusted p value for age <0.05 and excluded the ones that were also had p<0.05 for sex . We have added this information in greater detail in the Methods section (page 17). We also agree with the reviewers that identifying sex-differences is an interesting avenue for future research with greater number of samples.3. The authors identified 350 age-associated differentially methylated sites among all six immune cell types and compared them with other published studies. Do these sites overlap with the DNA methylation clock sites identified in PBMCs since these sites change in the same direction in separate cell populations? Also, only 10 of these 350 sites overlap with Horvath's pan-tissue epigenetic clock. Is there any factor that can explain this difference? For example, sequencing depth, coverage, etc?There can be several reasons for the observation that the CpGs identified in our study show only a small overlap with those identified in Horvath’s epigenetic clock. The “Horvath clock” was developed on methylation from multiple tissues and the “Hannum clock” was developed from whole blood. The contribution of different cell types depends on their frequency, and therefore methylation sites that change with aging in cells that are present in a high proportion would be predominant on those that only exist in low proportion. Indeed, the Horvath epigenetic clock works better in the GESTALT study when the data from PBMC are considered (59 probes overlapped instead of 10). Also, since these methylation clocks are statistically derived through a regression model using 21369 probes present in 27k microarray, it is possible that neighboring CpG gets picked up for the clock or many of the 850k sites went unrepresented. We have added this explanation to the Results section on page 5.4. In the legend of Figure 2, the most significant genic probes are classified as -log10(padj)<10. Did the author mean -log10(padj)>10?Thank you for pointing out the error. It has been fixed in the figure legend of the revised manuscript.5. It needs to be clarified how the top 15 genes were chosen. How many age-associated CpGs contribute to these 15 genes? Also, if more genes are considered, will more genes be shared among cell types?We thank the reviewer for the question. As a clarification we have incorporated additional information on number of age-associated probes for each of these top 15 genes in the Supplementary File 5. In Figure 1, we have looked at the overlap of all age-associated probes. Here we wanted to focus on whether the most significant age-associated genes are shared across cell types. When we increased the selection to the top 50 genes (new data added to Supplementary File 5), the number of shared age-hypo- or hypermethylated genes increase by only 5 and 13 genes respectively. This underscores our conclusion that “most CpGs with age-associated methylation consistent across cell types undergo moderate  methylation changes with aging.” We have rephrased this part of the Results on page 6 of the revised manuscript.6. In Figure 3C and 3D, the differences in β coefficient in the InCHIANTI study are small . Are the differentially methylated sites called in GESTALT identified as differentially methylated in the original InCHIANTI study?Changes in methylation with age (per year) tend to be small although they may be highly significant. Taking that into account, both the cross-sectional and longitudinal association with aging in the InCHIANTI are consistent in direction with those detected in the GESTALT study for the “shared” age-related CpG methylation.7. In Figure 4C and Supp Figure 4, it seems both hypo- and hyper-methylated sites with age show the V-shaped pattern.As correctly noted by the reviewer we do observe a V pattern and strong H3K4me1 peak at age-associated hypo as well as hypermethylated sites. This implies that the age-associated sites are enriched for active and/or primed enhancers. However, as the DHS and histone data in the ENCODE database was only available for either one of 2 donors , we were unable to see how the patterns change with age. We have added this note to the revised manuscript in the Results section (page 9) and Discussion section (page 13).8. It is unclear how the expression levels were measured. Expression levels from qPCR or RNA-seq need to be shown in addition to Supp Table 6. RNA-seq was mentioned in the method section, and if this was performed in this study, the quality metrics for the data need to be provided and the data need to be uploaded to GEO. The current GEO number (GSE184269) provided in this manuscript is linked to a published study and does not contain RNA-seq data.We thank the reviewers for their valid concern. We would like to clarify that expression values of the transcription factors are obtained from RNA-Seq data. In the paper we have specifically looked into the expression of 3 selected transcription factors to look for their association with age. Towards this, we have provided an additional Supplementary File 8 with the Kallisto TPM normalized values for the three transcription factors along with the sequencing data quality metrics.9. There are several places where the authors mentioned "data not shown". It may be better if these data could be presented in supplementary figures or tables.These are the 3 places where we have mentioned “data not shown” and all of them have been addressed-1.“Both age-associated hypo- and hypermethylated sites showed evident H3K4me1 peaks, a marker commonly associated with active and primed enhancers  (26). No specific trend was observed for H3K4me3 and H3K27ac (data not shown)”. We have added the results for H3K4me3 and H3K27ac to the Figure 4—figure supplement 1 and edited the Results section of revised manuscript (page 9).2.“We identified 35 genes that were hypomethylated with aging and had close by an ARNT motif in all six cell types (Data not shown)”. We have added the results for all the 35 genes with ARNT motif in the vicinity, to the Supplementary File 10 and edited in the Results section of revised manuscript (page 11).“Similarly, we found 20 genes with probes hypermethylated with age and with REST motif in the vicinity in all six cell types (data not shown)”. We have added the results for all the 26 genes with REST motif in the vicinity, to the Supplementary File 10 and edited in the Results section of revised manuscript (page 11). We also corrected a typing error as there are 26 genes and not 20 (page 11).Reviewer #3 (Recommendations for the authors):Specific suggestions for Authors:1) As mentioned in the public review, certain claims should be toned down or placed in context.In the revised version of the paper, we have added new citations and new data to address the concern raised by the reviewer.2) The authors need to make it clear in the introduction that this current study is based on the reanalysis of a data set they have published in 2021 and describe key findings and limitations of the initial study.We respectfully disagree with this statement. Very often data produced by cohort studies are reanalyzed according to different hypotheses. For example, NIA maintains the Baltimore Longitudinal study of aging and more than 1500 manuscript have been published over the last 20 years. Similarly, the genetic data from the UK biobank have been used for hundreds of analyses and produced some of the most interesting works in the literature over the last 10 years. There are probably hundreds of examples, including the Framingham study, the Cardiovascular Heart Study, the Health ABC study, and the Health and Retirement survey. In none of these cases, the content of previous papers is reported in the introduction, especially when, as in this case, the results are not relevant for the analysis reported in this manuscript.3) It is not clear from the methods and figure legends that motif predictions were done on DMRs that could be found in at least 5 cell types, as only loosely mentioned in the text. Please clarify this point in methods and legends.Thank you for your feedback. We used all the age-associated probes for HOMER analysis and not just the ones shared across 5 or more cell types. We added the associated details of the analysis on pages 17 and 20.4) Presumably, motif enrichment was performed against a genomic background. This information is not found in the methods and should be added.Thank you for pointing out the missing details. We added the HOMER background associated details in the Methods section on page 19. Briefly, HOMER software creates a list of background sequences which are randomly selected from the genome and matched for GC% content to the list of target sequences. We used this background file for our motif search in HOMER.5) Motif enrichment analysis was done in windows of +200bp around DMRs. Please explain why this choice was made and whether a narrower window  would yield drastically different outcomes.We appreciate a very valid point raised by Reviewer 3. We have used a 200bp window because it is the default size in HOMER software. However following Reviewer 3 comments we reanalyzed the data with +50bp window size and the results have been tabulated in the revised Supplementary File 7. We observe that the top hits across 5 of the 6 cell types continue to be ARNT and CTCF for age-hypomethylated sites and REST for age-hypermethylated sites. Of note, unlike the hits with 200bp window size, Arid5a and Bcl6 were not observed in 50bp window size indicating that these motifs are comparatively farther from the CpG sites. We have added a note about the new analysis and the results on page 10 of the revised manuscript.6) Can the authors speculate on why they see enrichment for neuronal and pancreas gene ontology pathways related to conserved DNA methylation changes?We appreciate the question regarding the relevance of the abovementioned pathways to our study. A recent study by Ewing et al. found CpG sites getting hypermethylated in immune cells of multiple sclerosis patients mapped to neuronal pathways where they argue that neuronal genes like GRIN, GRID and Netrin play a critical role in immune cell development as well (https://pubmed.ncbi.nlm.nih.gov/31053557/). Also, a paper by Karagiannis et al. finds neuronal genes in their PBMC aging data. Both references have been added to the Results section (page 8). However, didn’t find much with respect to pancreatic genes in the literature warranting future investigation in this direction.7) Data should be shown in important instances like "We identified 35 genes that were hypomethylated with aging and had close by an ARNT motif in all six cell types (Data not shown). Ten of these genes  have been linked to hypoxia response (37-46). Similarly, we found 20 genes with probes hypermethylated with age and with REST motif in the vicinity in all six cell types (data not shown)." Please provide the information.Thank you for the suggestions. We have added the information in Supplementary File 10 along with modifying the Results section in the revised manuscript on page 11.


Commercial smartphone apps designed to promote emotional well-being are becoming increasingly popular, but few apps have been empirically validated.This study examined the feasibility and effectiveness of a self-guided app designed to reduce daily stress via positive messaging and tailored short inspirational talks .A total of 166 participants  were recruited through social media advertising and randomized into an intervention  or active control (twice daily mood monitoring [MDMQ]) group. Primary  and secondary outcomes  were measured at the baseline (week 1) and end point (week 4). The app evaluation questions were assessed at week 2. All interactions and measurements were collected on the internet and through the apps.P=.05). For the intervention group, the change from baseline to week 4 was significant for vitality (P=.002) and hassles (P=.004), CSE total (P=.008), and CSE Emotional subscale (P=.02). For the control group, any changes over 4 weeks were not significant for any outcome. There was a significant group-by-time interaction for MDMQ calmness (P=.04). By week 4, calmness was significantly higher in the intervention group (P=.046). Of those in the intervention group at week 2 (n=68), 39 (57%) participants recommended the app and 41 (60%) participants wanted to continue using it. Pep talks and customizable voice options were the most popular features.In total, of 166 participants, 125 (75.3%) completed the trial. There were no differences in dropout rates between the groups . There were significant group-by-time interactions for vitality and hassles but no significant effect for CSE total  12622001005741; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=384304&isReview=true The COVID-19 pandemic has been linked to measurable decreases in emotional well-being in Australians , an areaMarkers of emotional well-being have important clinical implications, given that they are associated with symptoms of anxiety and depression. There is growing evidence of the connection with other markers of health. For example, in a large sample of older adults in the United Kingdom n=8780), self-realization (a concept tied to eudemonic well-being) and mood were positively associated with biological markers of inflammation in a model controlling for various confounders, including health conditions and mental health symptoms and conditions 80, self-,10.Stress is conceptually related to well-being. Stress is a psychological response to a situation that exceeds a person’s resources or the product of a person being unable to achieve their immediate goals ,12. StreOne theory that combines the concepts of affect, psychological well-being, and stress is the Conservation of Resource (CoR) theory ,18. ThisApp-delivered health programs have grown substantially with the popularization of smartphones  and haveEmotional well-being is an important area, and apps have the potential to play a role in enhancing positive mental health through emotional well-being ; howeverWe aimed to recruit approximately 150 adults aged 25 to 50 years, including 38 (25%) of whom were men. A comparison of 100 completers would allow the detection of a medium to large effect size (0.4) in coping self-efficacy .The selected age range and gender proportion were chosen, as they reflected the target audience of the Hey Lemonade smartphone app. Other inclusion criteria were as follows: owning a device with an operating system suitable for installing the Hey Lemonade app and currently residing in Australia. Exclusion criteria were self-reported and included having a professionally diagnosed mental health disorder, currently experiencing an abnormal level of life stressors , being related to or close friends with the research team or developers of the Hey Lemonade app, and having fewer than 11 apps of any nature installed on their phone. This final criterion was chosen as an indicator of low app engagement and possibly app literacy . People In this study, we used a 4-week randomized controlled trial design comparing the Hey Lemonade app (intervention plus daily mood monitoring) with an active control group (daily mood monitoring only). Participants were not blinded to the name of the intervention app and were informed that the study would evaluate the effectiveness of an app for managing everyday types of stressors. Those in the control group used only a freely available ecological momentary assessment app (SEMA3) to capture their daily mood data  describ. This waThe intervention app was developed by Hey Lemonade without input from the authors . It was The app’s core function is to provide 3- to 4-minute pep talks about daily stresses that can be customized through the choice of different voice options (referred to as companions in the app). The pep talks were written by professional writers and clinicians, including 2 psychologists, a clinical psychologist, and a solution-focused coaching specialist, who was also a provisional psychologist. The peps were grouped into the following 8 themes: All the Relationships, Daily Pep, Work Pressure, Pump-ups, Pepping Domesticity, Navigating the Feels, Looking After You, and Big Life Stress. Preliminary user experience and interface research led to the development of 30-40 uniquely written peps recorded using 7 voice options. The pep talks were voiced by public figures in the Australian community, representing a diverse mixture of characteristics. Each pep had at least 3 different voice options available.Pep talks were developed using core principles, including positive affirmation, humor, universality through specificity, and encouraging breathing techniques, as well as using motivational language theory  and a soOther key aspects of the app included the ability to gift relevant peps to people not using the app, daily pop-up inspirational written quotes delivered via an app notification, and a weekly email from the Hey Lemonade team. As the app was designed to have new content added monthly, new peps and a new voice option were added to the app at the start of week 2 to replicate this feature within the trial period. For further details about the intervention, refer to the CONSORT –EHEALTH checklist  providedApp engagement levels were measured throughout the trial in the intervention group. Data were collected by the app, deidentified, and supplied to us by Hey Lemonade. Overall use was calculated as a summed interaction score . This score captures each time a participant engaged with the app in any form. Overall length of any interaction with the app (out of a possible 29 days) was calculated as the difference between the first and the last recorded interaction. If a person had any interaction on day 1 and another on day 28, the length of the interaction was 27 days. This outcome is used to represent an active membership period. Within the app, once a pep had played to completion, users could also rate how they felt: 1=a lot worse; 2=a little worse; 3=about the same; 4=a little better; and 5=a lot better.cannot do at all), 5 (moderately certain can do), and 10 (certain can do). Scores were summed for a total CSE score (Cronbach α=.95), as well as for specific domains. The subscales showed excellent consistency: CSE Problem-Focus , CSE Stop Unpleasant Emotions , and CSE Get Support .CSE was measured using the 26-item CSE Scale  at week Constructs captured as secondary outcomes are described in The study was approved by the Commonwealth Scientific and Industrial Research Organisation Human Research Ethics Committee (application 2022_037_LR) and registered at the Australian and New Zealand Clinical Trials Registry (12622001005741).Participants were recruited through paid advertisements of Commonwealth Scientific and Industrial Research Organisation on Facebook, targeting people aged 25 to 50 years in October 2022. The Hey Lemonade company directors also promoted the trial on their social media pages .Interested participants were directed to a web-based participant information sheet and consent form, which included screening questions to assess eligibility. Those who passed the screening questionnaire were asked to contact the trial manager to express interest in the study. Eligible participants were contacted and asked to provide verbal consent to participate in the study and demographic information. The participants were then emailed the web-based baseline questionnaire. Participants who completed this step were enrolled in the study, given a participant identifier, randomized via a computer-generated sequence on a 1:1 basis ensuring balanced distribution of gender, and provided with instructions about how to install the SEMA3 and Hey Lemonade (intervention-only) apps. The intervention app was installed from the App Store via TestFlight or Google Play using beta testing links because it was not publicly available at the time of the trial. The trial manager randomized the participants, and the research team was blinded to the participant allocation and did not have contact with the participants throughout the study.Trial outcomes were assessed at baseline, week 2, and end point (week 4). The study was conducted without face-to-face contact. All assessments were completed on the web through the web-based survey platform Alchemer via a link sent to the participants at each assessment point. Participants were sent 1 email reminder if they had not completed the survey within 24 to 48 hours. If they failed to complete the survey after this reminder, they were marked as lost to follow-up. Participants were also able to formally withdraw at any point after the baseline. These participants were asked a reason for their withdrawal. Those who completed the final survey were sent an Aus $50 (US $33.50) electronic gift voucher to thank them for their participation. No costs were associated with accessing any of the apps used in this study.For the Hey Lemonade app, users reported issues accessing the content on 6 occasions. These issues were usually resolved within 24 hours. For the SEMA3 app, approximately 30 participants reported technical difficulties that affected a higher number of Android users. After 3 to 4 days, these issues could not be resolved, so the trial team created a replacement recurring web-based survey to assess momentary mood using the Alchemer platform, in which participants were asked to complete without reminders.To compare the effect of group on change over time for all trial outcome measures, we conducted linear mixed models fitting a marginal model (in which random participant effects are not considered) with unstructured covariance matrices to optimize efficiency ,40. Fixe165=0.851; P=.40). Owing to the technical issues with the SEMA3 app, the number of missing observations in the first week of the trial was high , although this was comparable with previous work [The daily mood data comprised a total of 5305 observations with an average of 31.77  observations per participant. There was no significant group difference in the number of observations  for Microsoft Windows was used to perform all analyses, and statistical tests were 2 tailed, with A total of 1066 people accessed consent and screening information, with 572 (53.66%) meeting the eligibility criteria. After being contacted by the trial manager, 30.6% (175/572) of individuals consented to participate in the trial. Of the participants who consented 94.9% (166/175) completed the baseline questionnaire and were randomized into either the intervention  or control  condition ; Table 2A total of 41 participants were lost to follow-up or withdrew from the trial following the completion of the baseline questionnaire and group randomization. There were no significant differences between completers and noncompleters in any of the measures, including demographic variables or baseline primary and secondary outcomes.r=0.51; P<.001), as well as life satisfaction  and vitality . Moderate negative relationships were found between CSE and negative affect , hassles , and perceived stress . Uplifts were weakly to moderately positively associated with CSE .There were significant, moderate positive correlations between the primary outcome measure, total CSE, with positive affect  for those who completed the intervention (n=62) was 213 (range 9-936). One-third of the users who completed the study had between 100 and 200 interactions with the app, whereas 1 F4,76=1.55; P=.20).In the multiple regression analysis, participant sex, age, number of wellness apps, and device type failed to predict higher total engagement with the app over the trial, explaining 2.7% of the total variance  times per month. Of all peps accessed, 66.2% (605/914) were marked as finished. A total of 14% (11/81) of users failed to play a pep to marked completion at any point throughout the trial.Once a pep had been played to completion, participants were offered the opportunity to indicate the extent to which listening to the pep had impacted how they were feeling, a feature included for the trial duration only. Of all the peps marked to completion, 81.5% (493/605) received feelings ratings. On the basis of individual pep topics, more than half of the  available topics were rated ≥4 on average (“a little better” to “a lot better”), with the mean of all ratings being 4.01 (SD 0.71). On average, each pep was rated ≥3 (“about the same”). The 2 most popular peps were accessed 133 and 128 times throughout the trial, with the third to fifth most popular accessed 47 to 41 times. A total of 9 peps were accessed less than 10 times throughout the trial.P=.05). Exploratory analyses were conducted, and models were created using the 3 subscales of CSE to understand if these changes occurred in specific domains. The results revealed a significant interaction effect only for the CSE Emotional subscale (P=.04). The only significant pairwise comparison was for the intervention group, with a significant improvement in the CSE Emotional subscale from baseline to end point  and hassles , with the intervention group reporting lower hassles. The magnitude of the change in the intervention group was significant for vitality (P=.002) and hassles (P=.004), with the intervention group showing positive improvements in both instances . Pairwise comparisons suggested that at baseline, there was no significant group difference in calmness scores (P=.67), whereas at week 4, calmness was significantly higher in the intervention group than in the control group  or control groups (P=.21). There were no significant effects for valence or energetic arousal .There was a significant interaction between group and time for the momentary mood outcome of the Multidimensional Mood Questionnaire in the calmness domain  indicated that they would recommend the app to family and friends, with a further 16 (24%) who were unsure. A total of 60% (41/68) indicated that they wanted to keep using the app for a few months or indefinitely, with 16% (11/68) not wanting to access the app any further. Pep talks and customizable voice options were selected as the favorite features of the app for most users .In terms of qualitative feedback regarding how they felt after listening to a pep, most participants  referenced positive energy with a small number of detractors . The total app use was reduced over the 4 weeks and was not predicted by any participant characteristics. Pep talks, which are the central features of the app, were favorably rated by users. Those who entered the data immediately after listening to a pep largely indicated feeling positive changes in their momentary mood state. Of the 3 aspects of momentary mood measured daily, calmness improved significantly for the app users. Finally, there were substantial improvements in perceived daily hassles and vitality for those randomized to the app condition. Overall, the significant changes observed were aligned with qualitative feedback, which highlighted the impacts of the app on feeling calmer and more positive.There is very little published evidence in the space of well-being apps, despite the hundreds of apps available for download . Most ofMore recently, the Positive Activity Model has supported the idea that simple tools can improve well-being . The curApp usability and user feedback data were promising. More than 75% (53/68) of participants completing evaluation in week 2 reported wanting to continue using the app beyond the trial. Before commencing, participants were blinded to the content of the app and were told only that the study evaluated its effectiveness on daily stressors. A small number of people did not enjoy the app . Nevertheless, this sample was not specifically interested in wellness apps, as evidenced by the low number of existing wellness apps installed on the participants’ devices. In combination with partial blinding, it was expected that the app would not be to everyone’s taste. However, the overall qualitative feedback was also mostly positive, reflecting positive changes in calmness while also focusing on feeling positive or having an improved outlook. This appears to have translated to positive changes in momentary calmness and vitality but not overall satisfaction with life.The hassle conceptualization of stress has been called “a minor events approach”  and aligHassles may also be reduced through increased vitality, given that positive energy has been associated with fewer negative appraisals of personal problems . VitalitThe increase in vitality in the intervention group represented a 7.8% improvement on average. A previous study observed that a 5% to 10% decrease in vitality  was associated with increased disease risk for conditions ranging from depression to angina and osteoarthritis . Thus, tIn the context of a broader theoretical model, it appears that a simple tool can have benefits for some aspects of coping. However, the CoR theory needs to consider not only equipping people with tools but also the confidence to use them . Using aThis study was a controlled, rigorously designed trial, powered appropriately to detect meaningful effects. Previous studies have used anywhere between 12 days and 12 weeks to evaluate similar apps with those of longer durations targeting clinical samples ,22. The Our primary research questions focused on the effectiveness and feasibility of the app rather than mechanisms for change; therefore, we can only use the literature to guide the interpretation of which specific features of the app were associated with the changes observed. Coaching frameworks, humor -62, and The current sample was targeted toward individuals in the market for whom the app was developed and designed in a process that occurred before this effectiveness trial. The target market included a narrow age range, comprising mostly women with no major mental health challenges. Approximately one-third of the interested participants were deemed ineligible. It may be possible that healthier samples and women have stronger CSE overall, which makes it easier to build upon . HoweverNot all feedback received regarding the Hey Lemonade app was positive. There was a notable proportion of unsure selections  regarding the recommendation of the app to others. Qualitative feedback regarding the ability to gift peps to people provided some insights into possible hesitation to recommend with users, suggesting that they needed to feel comfortable enough to forward on “self-help–type” materials. The nature of a mental well-being focus may create challenges for recommending and sharing components.One of the largest challenges in this study was the technical issues associated with daily mood monitoring using the freely available SEMA3 app. These may have disproportionately affected the control group, for whom mood monitoring was the primary task associated with trial participation, as well as Android users who appeared to report more technical issues. Unfortunately, using a third-party app, such as SEMA3, meant that these issues were outside the control of the research team. It is reassuring that no negative changes were observed in the control group; however, it is unclear if this may have disrupted any possible positive change generated by mood monitoring for those in the control group.The Hey Lemonade app is designed to be a simple, no-fail tool to assist people in managing daily stress. The intervention did not result in a significant change in the primary outcome of CSE, but it did improve momentary calmness and secondary outcomes, including positive feelings and the ability to cope with general life hassles over 4 weeks. This indicates that a digital intervention such as the Hey Lemonade app might be useful for bolstering people’s resource kitty and hence make them more equipped to face daily challenges. More broadly, the findings also suggest that simple solutions may have the ability to generate meaningful outcomes for well-being . These f


Chronic hypercapnic respiratory failure in obstructive lung diseases may benefit from nocturnal Home non-invasive ventilation (HNIV). It has been shown that in patients with persistence of hypercapnia after an acute episode of chronic obstructive pulmonary disease (COPD) exacerbation requiring mechanical ventilation, HNIV may improve the risk for new admission and survival. The ability to reach these aims depends on the correct timing of enrolling patients, as well as a correct definition of ventilatory needing and setting of the ventilator. This review tries to define a possible home treatment path of hypercapnic respiratory failure in COPD by analyzing the main studies published in recent years. Chronic hypercapnic respiratory failure in lung diseases usually represents a reason to consider the prescription of home noninvasive ventilation (HNIV). When to start it and how to get it depends on the underlying chronic respiratory disease and the available clinical evidence. The aim of this review is to focus on indications and modes of using NIV at home in patients with chronic respiratory failure secondary to obstructive lung disease . We will start with a clinical case to follow a possible “journey” of a patient with chronic respiratory failure who is a possible candidate for home ventilation.2 = 0.31 showed a PaCO2 of 85 mmHg, PaO2 of 65 mmHg and pH of 7.21. Lung ultrasound examination, targeted to detect specific ultrasound patterns according to international recommendations [2 was still elevated (56 mmHg), despite a normalization of the pH (7.37). For this reason, physicians considered the opportunity to prescribe NIV at home to facilitate the discharge of the patient.A 68-year-old patient was hospitalized for an acute exacerbation of COPD (AECOPD) with acute respiratory failure and acidosis. During an initial observation in the emergency room, after stabilization with oxygen therapy targeted to keep an oxygen saturation between 89 and 92%, as indicated by BTS guidelines , arteriaWe conducted a comprehensive PubMed search of full-length articles in English using the following key terms: “chronic hypercapnic respiratory failure” or “COPD” and “home non-invasive ventilation”. We considered RCTs and physiological studies published since 2000, as well as European and American recommendations on the application of HNIV in chronic respiratory failure for patients with hypercapnic COPD. We excluded articles published in non-peer-reviewed journals. Papers were independently reviewed by the two authors, and those judged to be more informative for the purpose of the review were retained.2O). This promising study showed a significant reduction of new readmission for AECOPD in the group treated with NIV . However, there was an unclear definition of AECOPD, and the very small sample size and high drop-out rate (25% of enrolled patients) made the results difficult to apply in clinical practice. Moreover, NIV or control therapy was initiated before hospital discharge after more than 48 h of successful weaning. Some years later, two large-scale international randomized control trials (RCTs) investigated the efficacy of HNIV in reducing mortality and readmission rates after an AECOPD compared to standard treatment [2 after 3 months. In contrast, the HOT-HMV trial [2 within a normal range in the weeks following their acute exacerbation. The normalizing of PaCO2 post-exacerbation was already described by an observational study many years ago [Patients with AECOPD needing mechanical ventilation who survive after hospitalization have a high risk of readmission and death. More than sixty percent of them may have another life-threatening event, and 50%, on average, may die mainly due to respiratory failure . For thiears ago  and that2 value for at least the first year of treatment [To standardize indications to HNIV, a recent European Task Force suggested, with a conditional recommendation, that HNIV should be used after an AECOPD episode requiring acute NIV if hypercapnia persists in the follow-up after 2–4 weeks . Howeverreatment .2, or in patients with complaints of excessive snoring, disrupted sleep or morning headache. The HOT-HMV trials left individual centers to use established pathways for OSA screening: patients in which there was a clinical suspicion of OSA based on clinical review or overnight oximetry underwent further testing with limited respiratory polygraphy. However, it has been shown that the use of a specific screening instrument, such as sleepiness scales, would miss nearly half of patients with severe OSA [2 [Both previously mentioned RCTs, RESCUE and HOT-HMV, excluded patients with OSA. However, the criteria to define OSA were different and did not consider a standardized use of polysomnography as the gold standard. In fact, in the RESCUE study, overnight polygraphy or polysomnography was suggested in patients with a body mass index ≥30 kg/mvere OSA . Similare OSA [2 . This raFor this reason, the most recent American Thoracic Society guideline on HNIV in chronic hypercapnic COPD patients  highligh2) are the main reasons for the controversial results. The first RCTs [2 value. These RCTs defined a phase of clinical research in which not much emphasis was placed on the setting of NIV.Another phenotype of chronic hypercapnic respiratory failure is represented by COPD patients who have not experienced hospitalization due to severe acute exacerbation. Several studies have investigated the effects of long-term HNIV on various outcomes in hypercapnic stable COPD, including mortality, hospitalization rate, and patient-centered outcomes, such as exercise tolerance, symptom severity or health-related quality of life (HRQL) ,14. Howerst RCTs ,16 enrolrst RCTs  found, i2 > 51.9 mmHg) and randomized them to either HNIV or standard therapy [2 reduction of at least 20% from baseline or to achieve PaCO2 <48 mmHg. The trial was terminated before the target sample size of 300 patients was attained due to a change in the national guidelines for NIV provision supporting the use of HNIV. One hundred and ninety-five patients were enrolled in almost 5 years. The results showed a 1-year survival benefit in patients randomized to HNIV with an increase in HRQL. Surprisingly, the standard therapy group showed a three-month mortality rate of around 30% despite having a relatively well-preserved exercise capacity  and low emergency admission rates. The main differences in the enrolled criteria and outcomes among these studies are shown in The more recent multicenter RCT included 195 patients with stable chronic hypercapnia  of 5 cmH2O, back-up rate = 12 breaths/minute. He was discharged to a rehabilitation center due to the significant reduction of exercise tolerance and compromised activities of daily living. The attending physician decided to stop nocturnal NIV, wait and follow up with ABG while pulmonary rehabilitation was carried out. After 2 weeks, the ABGs showed a normal value of PaCO2 (42 mmHg) with a normal pH (7.40). Polysomnography was used to diagnose a severe OSA with an apnea/hypopnea index of 56 events/minute. The patient underwent a CPAP titration study, and the patient was discharged with a CPAP set at 12 cmH2O. His follow-up at 6 and 12 months confirmed that he had stable normal PaCO2 level on ABGs.Due to the persistence of hypercapnia after NIV weaning, the patient was discharged with HNIV. The setting chosen was spontaneous/timed mode with an inspiratory positive airway pressure (IPAP) of 25 cmH2 during treatment [2 but also in improving clinical outcomes  with an unexpected, better tolerability [2 or improve it at least of 20% of the baseline value. Later, Murphy et al. showed that high pressure with a low respiratory rate was able to reach the same results as high intensity [2 reduction versus those that did not. Hence, we do not know if the clinical and physiological effects of HNIV are all mediated by the PaCO2 reduction. On the other hand, one previous study showed a survival benefit without a change in hypercapnia [2 should be considered, respectively, the only enrollment criteria and target of successful HNIV. Concerning the NIV setting, the European Task Force [2 levels in patients with COPD as a conditional recommendation with very low certainty evidence. Adherence to HNIV is another crucial point that can determine the success of this treatment. For COPD patients, an increased adherence to the therapy up to 20 h/day was shown to significantly correlate with a lower mortality rate [A pressure-targeted mode is the most frequently used mode of ventilation during HNIV in chronic hypercapnic COPD. However, some years ago, several studies failed to show a significant reduction of PaCOreatment ,16,17, rrability . The newercapnia . Therefosk Force  suggestsity rate .2 reduction  is mandatory to increase the cost–benefit ratio of HNIV. Adherence to the therapy may be a crucial point in reaching all established objectives.In chronic hypercapnic COPD, the indication for HNIV is based on very low certainty. It is strongly recommended that polygraphy be carried out to exclude OSA in patients who were hospitalized for an AECOPD requiring mechanical ventilation. Inspiratory pressures high enough to significantly improve hypercapnia or to restore normocapnia should be accurately titrated. Having clear objectives of HNIV more than PaCO


Ankle-foot orthoses (AFOs) are extensively used as a primary management method to assist ambulation of children with Cerebral Palsy (CP). However, there are certain barriers that hinder their prescription as well as their use as a mobility device in all kinds of daily-life activities. This exploratory research attempts to further understand the existing limitations of current AFOs to promote a better personalization of new design solutions.Stakeholders’  perspectives on AFO technology were collected by two online surveys. Respondents evaluated the limitations of current assistive solutions and assessment methods, provided their expectations for a new AFO design, and analyzed the importance of different design features and metrics to enrich the gait performance of these patients in daily-life. Quantitative responses were rated and compared with respect to their perceived importance. Qualitative responses were classified into themes by using content analysis.130 survey responses from ten countries were analyzed, 94 from professionals and 36 from end-users with CP. The most highly rated design features by both stakeholder groups were the comfort and the ease of putting on and taking off the assistive device. In general, professionals preferred new features to enrich the independence of the patient by improving gait at functional levels. End-users also considered their social acceptance and participation. Health care professionals reported a lack of confidence concerning decision-making about AFO prescription. To some degree, this may be due to the reported inconsistent understanding of the type of assistance required for each pathological gait. Thus, they indicated that more information about patients’ day-to-day walking performance would be beneficial to assess patients’ capabilities.This study emphasizes the importance of developing new approaches to assess and treat CP gait in daily-life situations. The stakeholders’ needs and criteria reported here may serve as insights for the design of future assistive devices and for the follow-up monitoring of these patients.The online version contains supplementary material available at 10.1186/s12984-023-01162-3. Physical disabilities derived from neurological or motor disorders are a global societal problem. In children, Cerebral Palsy (CP) is the major cause of physical disability such as gait limitations . CP resuThe improvement of walking ability is considered one of the primary goals to allow for a more active and independent lifestyle in CP , 7. In cideal orthotic management that should be prescribed to tailor the specific needs of an individual patient. First, current clinical standards for choosing all possible AFO design features and the impact of these features on patient outcomes in daily-life are unclear . These referred to effort expectancy , performance expectancy , social influence , and facilitating conditions ; (4) Gait in daily-living; and (5) Limitations of current devices. Both clusters (4) and (5) included OE questions similar to those presented for GThe final version of the survey for group Gentclass1pt{minimaDemographics, and 5–point Likert scales, with 1—very unimportant to 5—very important for Importance of design features, and with 1—strongly disagree to 5—strongly agree for Expectations for a new device. Like GImportance of design features to differentiate in case they rated all of them as ‘important’ or ‘very important’.For GTwo groups of stakeholders were approached to participate as respondents to the surveys: GThe group of GThe study information for GThe main strategy to approach end-users .Responses to both surveys were exported into an Excel file for data cleaning and analysis. Spanish and Dutch responses were translated into English by two bilingual researchers (CB and MvH).Importance of design features, the Mann–Whitney U test with Descriptive statistics and graphic representations were used to summarize and compare CE responses. For the cluster Responses to the OE questions were analyzed using content analysis . IrrelevA total of 94 professionals and 36 end-users responded to the surveys. Demographic information about the respondents is described in Tables Health care professionals  with the statement “There is enough information to feel confident when prescribing the correct AFO type  for a specific patient”, which indicates that more than 50% of the health care professionals think that more information is required.As many as 79.3% of the health care respondents believed (i.e. agreed or strongly agreed) that “patients’ performance in the clinic is different than in real-life settings”. This might be related to the fact that almost all the health care professionals (98.8%) considered that “it would be important to get information about patients’ walking on daily-life activities”, and that 95.2% of them agreed with the statement “A report on the use of AFOs on daily-life could provide useful information to improve the patient’s assessment in clinic”.Both stakeholder groups , Non-standardized Terrains (18.9%) and Home (16.2%).Other identified themes indicated the importance of having a functional gait pattern in specific locations such as Equal social interaction (20.7%) was identified related to the ability to keep up with able bodied peers and family members.Finally, the theme Bulkiness , followed by Cost (29.9%), Control (28.6%), and Adaptability (20.8%) of the device.The first theme and main identified problem of powered exoskeletons was their Availability (11.7%), understood as the possibility of getting access to an exoskeleton, Flexibility & ROM (7.8%), Acceptance (6.5%) and Durability (5.2%), the last two only mentioned by the group of professionals , Bulkiness (17.4%), Wearability (9.8%), specifically referring to the difficulties to combine AFOs with clothing and shoes, Metrics (9.8%), with answers like “Possibility to test different AFO models with quantitative metrics to evaluate which solution is the best for a specific patient”, User friendliness (9.8%), Cost (8.7%), Durability (6.5%) and the improvement of general Walking (5.4%). In the latter, professionals highlighted the necessity to improve ‘Functional’ Walking, while end-users stressed the desire of generating ‘Normal’ Walking patterns with AFOs .The present study was designed to collect the existing limitations on the AFO technology for individuals with CP and identify areas of improvement. The results derived from the surveys provide insights on the stakeholders’ needs and criteria to assist pathological gait in CP, highlighting important required features that may be useful for both (1) the assessment and prescription of current AFOs, and (2) the development of future novel devices. A recent publication  has prevIn total, 94 professionals in CP  and 36 end-users with CP (patients or families) responded to our surveys. We acknowledge that some individuals with CP who answered the questionnaire and who are affected by severe motor impairments (i.e. GMFCS V) are maybe unlikely to benefit from assistive AFOs to promote their walking capabilities in daily-life. However, we also gathered their responses and recognized their wishes as they all have residual functions to contribute with small actions to everyday tasks.The most valuable feature identified by both stakeholder groups in the close-ended questions was the “comfort while wearing” the assistive device, i.e. avoiding skin pressure, friction or abrasions. This has also been a primary concern of previous studies about the efficacy of AFOs for CP , 21, andAll design features of the survey were considered to be important, but generally professionals rated them higher than end-users did Fig. . Howeverentclass1pt{minimaRelevant in-home metrics . A similar circumstance happened when selecting the top-1 general parameter under Concerning the classification that professionals made of the type of walking assistance with respect to the level of the GMFCS, there were some clear trends Fig. : (1) patGait management and AFO prescription of the survey, where health care professionals reported a lack of confidence concerning decision-making about AFO prescription. This might  be related to the fact that more than 79% of health care professionals thought that the performance of patients in the laboratory  is different than in real-life settings. This behaviour has been a long investigation of psychologists and it is known as the ‘Hawthorne effect’ [capacity demonstrated in a standardized environment (laboratory) is usually overestimated and exceeds their walking performance in real-life settings. That is likely the reason why around 98% of the health care professionals emphasized the importance of gathering information regarding the use of assistive technology at home, as this may enrich the assessments and evaluations at the clinic. Table This convoluted connection between the level of the GMFCS, the patient’s pathological gait and the type of assistance needed makes it hard to prescribe the most suitable AFO for a specific patient , 18. Thi effect’ , which s effect’ , 22, sugNew and effective approaches are needed to assess and treat CP pathological gait in non-standardized settings . ExistinFor new AFO designs, the benefits of (powered) robotic technology (e.g. tailoring the assistance provided) should be considered. User’s expectations to adopt a new solution are positive Fig. . HoweverFinally, the incorporation of sensors within the design of new AFOs might be an option to provide metrics and assess the user’s gait in daily-life to inform clinical decision-making.The survey results encompassed responses of stakeholders from ten different countries. However, the majority of these stakeholders were from Spain and The Netherlands. This might provoke some bias with the representation of the broader world population. A second bias might come from the voluntary nature of participation in the online surveys, which might cause that some questions are responded positively towards the necessity of changes in current gait assistive technology for CP . FinallyThis exploratory study provides insights into the weighted desires of children with CP, their families and professionals in the field towards the use and design of (AFO) assistive devices. The study suggests that the identified prioritized areas of improvement should be considered as important information for new designs of these assistive devices, but it is not meant to be a resolute guide, nor does it attempt to rationale for the biomechanical basis to influence in gait performance.With this research we tried to give clarity on (1) what needs to be improved in current assistive technology to enrich gait in daily-life activities, and (2) what type of day-to-day performance measurements may allow better personalization of gait management and AFO prescription. The outcomes of our investigation bring different and complementary information, which is valuable for both designers of assistive devices for CP and clinicians involved in treatment and follow-up care of these patients.Additional file 1. Final version of the English survey for Professionals stakeholder group (GP).Additional file 2. Final version of the English survey for end-users with CP and families (GU).


While oral immunotherapy (OIT) has been shown to promote the remission of mild peanut allergy in young children, there is still an unmet need for a disease-modifying intervention for older patients and those with severe diseases. In mice models, abatacept, a cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) immunoglobulin fusion protein, has been shown to promote immune tolerance to food when used as an adjuvant to allergen immunotherapy. The goal of this study is to explore the potential efficacy of abatacept in promoting immune tolerance to food allergens during OIT in humans.In this phase 2a proof-of-concept study (NCT04872218), 14 peanut-allergic participants aged from 14 to 55 years will be randomized at a 1:1 ratio to abatacept vs. placebo for the first 24 weeks of a peanut OIT treatment (target maintenance dose of 300 mg peanut protein). The primary outcome will be the suppression of the OIT-induced surge in peanut-specific IgE/total IgE at 24 weeks, relative to the baseline. Sustained unresponsiveness will be assessed as a secondary outcome starting at 36 weeks by observing incremental periods of peanut avoidance followed by oral food challenges.This is the first study assessing the use of abatacept as an adjuvant to allergen immunotherapy in humans. As observed in preclinical studies, the ability of abatacept to modulate the peanut-specific immune response during OIT will serve as a proxy outcome for the development of clinical tolerance, given the small sample size. The study will also test a new patient-oriented approach to sustained tolerance testing in randomized controlled trials. Oral immunotherapy (OIT) is a new treatment for food allergy (FA) . It consFA memory is mediated by B and T memory cells in lymphoid organs as well as by long-lived IgE-producing plasma cells that can persist for years in the bone marrow –13.During the early phase of OIT, exposure to the allergen results in the reactivation of memory B cells that are dependent on type-2 memory T cells (Th2 cells) , which lAbatacept is a cytotoxic T lymphocyte-associated antigen (CTLA-4)-immunoglobulin fusion protein approved by the U.S. Food and Drug Administration (FDA) and Health Canada for adults with psoriasis and rheumatoid arthritis as well as for children of 6 years and older with juvenile idiopathic arthritis. Abatacept interferes with the delivery of the costimulatory signal required for T-cell activation and plasma cell survival .T cells require two distinct signals from antigen-presenting cells (APCs) in order to activate . The firCTLA-4 is a regulatory receptor naturally expressed by T cells in the days following their activation. It has a much higher affinity for B7 molecules than CD28 and dislodges it in a competitive manner . CTLA-4 The concept of first and second signals also applies to some extent to IgE-producing plasma cells. Contrarily to IgG-producing plasma cells, IgE-producing plasma cells retain a functional BCR after differentiation , and it Genetic association studies have hinted at a link between CTLA-4 and allergic disease for some time. In 2004, four single nucleotide polymorphisms of CTLA-4 were found to be associated with IgE production and allergic phenotype in a cohort of 364 asthmatic families from European countries . The resIn 2013, a randomized controlled trial in adults with mild asthma failed to show the superiority of a 3-month treatment with abatacept over placebo at decreasing eosinophilic inflammation on subsequent allergen-specific bronchial challenges. This led the authors to conclude a lack of efficacy of second signal blockade in allergic inflammation . HoweverVan Wijk et al. reported, in 2007, that abatacept completely prevented primary humoral (IgE and IgG) and cellular [interleukins (IL)-4 and 5] sensitization to peanut in mice when added to cholera toxin-based oral sensitization protocol . AllergiSeveral groups reported improvements in airway eosinophil infiltration, IgE production, type-2 cytokine release, and allergen-specific airway hyper-reactivity in mice following treatment with abatacept –37. All We hypothesize that in teenagers and adults with persistent severe peanut allergy, administering peanut antigen through OIT while simultaneously blocking the second signal with abatacept will prevent the reactivation of the secondary allergic immune response and selectively suppress peanut-specific memory T and IgE-producing plasma cells, and thereby improve the rates of clinical remission.The ATARI trial is a phase 2a proof-of-concept trial comparing the efficacy of abatacept vs. placebo at suppressing the sIgE surge in the 1st month of peanut OIT, treated as a proxy measure of immune memory reactivation.This study is a phase 2a, double-blinded, and randomized proof-of-concept trial comparing abatacept with placebo as an adjuvant to OIT in peanut-allergic adolescents and adults. The study will be conducted in Sainte-Justine Hospital . A total of 14 patients will be recruited and randomized 1:1 to receive abatacept or placebo , in association with a peanut OIT for 24 weeks, after which OIT will be continued alone .Starting at week 36, participants will undergo a series of up to five oral food challenges (OFCs), interlaced with incremental periods of avoidance over 12 weeks to characterize the extent of sustained unresponsiveness (SU) to peanut .The primary outcome of the trial is the relative change from baseline in peanut-specific/total IgE ratio at the end of the treatment phase (week 24). The use of the specific/total IgE ratio aims to control for non-specific fluctuations in IgE production.Secondary outcomes include the following:The relative change in peanut-specific IgG4/IgE (sIgG4/sIgE) ratio from baseline to week 24.The absolute change in peanut sIgG4 from baseline to week 24.The maximum period of avoidance after which an OFC with 300 mg peanut protein is still tolerated.The mean cumulative function of food dosing allergic reactions.The highest tolerated dose on week 36 OFC.The time from the onset of OIT to the maintenance dose of 300 mg.The overall rate of adverse events (AEs).Exploratory outcomes include the following:a. Change in peanut atopy patch test from baseline to weeks 12, 24, and 48.b. Change in peanut skin test from baseline to weeks 12, 24, and 48.c. Relative change in peanut-specific/total IgE from baseline to weeks 2, 6, 12, 36, and 48.d. Relative change in peanut sIgG4/sIgE ratio from baseline to weeks 2, 6, 12, 36, and 48.e. Absolute change from baseline in peanut sIgG4 to weeks 2, 6, 12, 36, and 48.f. The highest tolerated dose on week 38 OFC [72 h SU].g. The highest tolerated dose on week 40 OFC [1-week SU].h. The highest tolerated dose on week 43 OFC [2-week SU].i. The highest tolerated dose on week 48 OFC [4-week SU].The study aims to enroll 14 participants aged 14–50 years with serum peanut sIgE >50 kU/L. The inclusion and exclusion criteria are presented in - History of two or more systemic corticosteroid courses within 6 months of screening or 1 course of systemic corticosteroids within 3 months of screening to treat asthma/wheezing;- One hospitalization or emergency department visit for asthma/wheezing within 6 months of screening;- Forced expiratory volume in 1 s (FEV1) <80% of predicted or FEV1/forced vital capacity (FVC) <75%, with or without controller medications;- Inhaled corticosteroid dosing of >500 mcg daily fluticasone .Several study requirements will also be verified before inclusion as follows:- Participants should be willing to be trained on the proper use of an epinephrine autoinjector and willing to possess an epinephrine autoinjector for the duration of the study or similar.- Participants should be able to discontinue their usual anti-allergic medication prior to skin prick tests and/or OFC, as described in Section 3.7.- Female participants with childbearing potential must agree to remain abstinent  or use acceptable contraceptive methods  during the trial.The first three doses of abatacept vs. placebo will be separated by an interval of 2 weeks, while the remaining doses will be given monthly, as recommended for autoimmune disorders. Since participants will be aged 14 years and older, adult dosages will be used, based on the participant's body weight: 500 mg if body weight < 60 kg, 750 mg if body weight ranges between 60 and 100 kg, and 1,000 mg if body weight > 100 kg.The randomization list will be generated by the study pharmacist using simple randomization. The medication or placebo will be transferred into a generic IV bag to maintain blinding and identified with the participant's ID and a blinded investigational product label. It will be administered intravenously through a 0.2–1.2 μm low protein-binding filter over 30 min by the blinded study nurse, as recommended by the abatacept product monograph. Since the study drug contains maltose and the placebo does not, to ensure the blinding in participants with diabetes, glycemia will not be monitored for 4 h following the perfusion.Peanut OIT will be initiated 24 to 72 h after the first injection of either abatacept or placebo. The initial food escalation (IFE) will consist of an OFC of up to 300 mg of peanut protein. IFE doses , or forgetfulness, the up-dosing visit will be postponed until the criteria are met. Participants will be informed that compliance rates lower than 80% will lead to their exclusion from the OIT program for safety reasons.Up-dosing will also be postponed in participants in whom it is contraindicated due to active illness or allergies.Before up-dosing, the participant's dosing diary will be reviewed by the investigator to grade dose-related reactions using the revised CoFAR Grading Scale for Systemic Allergic Reactions (version 3.0) . By defaParticipants who react to their dose escalation will not increase their daily dose and remain on the previously tolerated dose for another 2 weeks. The following up-dosing visit will plan for an escalation at half of the percentage increase of the failed escalation, to be adjusted based on the symptom diary. If escalation fails again, the following planned percentage increase will again be decreased by half at the subsequent visit and each following visit until the escalation is tolerated.When the participant presents no symptoms at all to their daily dose, the up-dosing rules dictate doubling the percentage increase. However, if this would lead to an increase by a percentage up-dosing that had failed in the past, the participant is required to have two up-dosing visits with absolutely no symptoms in their diaries before proceeding to that new percentage increase, instead of just one.Up-dosing visits will take place up to a maintenance dose of 300 mg, at which point the participant will remain on that daily dosage until the end of the study.The participants will be provided with pre-weighted peanut flour doses and instructed to ingest their dose every day at around the same time. Participants will have 24 h access to research staff for support with home dosing and to guide interventions in case of adverse events. They will be trained in the recognition of anaphylaxis and cofactors that increase the risk of reactions when they are taking their dose . They will be prescribed an epinephrine auto-injector and will be trained on its use.Medication can be prescribed to prevent OIT-induced allergic symptoms with daily dosing, as per the investigator's discretion. This can include H1 and/or H2 anti-histamine, leukotriene receptor antagonists, proton-pump inhibitors, prostaglandin E1 analogs, mast cell stabilizers, and/or swallowed corticosteroids. These medications will be documented in the patient diary and concomitant medication log.In the event of an identifiable cofactor , the OIT dose would be temporarily decreased by half. The participant would resume full dosing once the cofactor has been resolved. In the event of any systemic reaction or a moderate-to-severe local reaction at home, the OIT dose would be decreased by half until the following planned up-dosing visit.Oral tolerance will be assessed starting at week 36 to allow for a 4-month washout period after the last abatacept or placebo perfusion . ParticiParticipants who tolerate at least 300 mg of peanut protein on week 36 OFC will proceed to SU testing. They will be asked to continue daily dosing with 300 mg of peanut protein for 11 days, after which they will avoid peanuts for 72 h and then return to the clinic to repeat an OFC up to 9,000 mg of peanut protein.Participants who tolerate 300 mg of peanut protein on 72 h SU testing will resume daily dosing for 1 week and then avoid peanuts for a whole week, before returning to the clinic to repeat the OFC up to 9,000 mg peanut protein.Participants who tolerate 300 mg of peanut protein on the 1-week SU testing will resume daily dosing for 1 week and then avoid peanuts for 2 weeks, before returning to the clinic to repeat the OFC up to 9,000 mg peanut protein (2w SU).Participants who tolerate 300 mg of peanut protein on the 2-week SU testing will resume daily dosing for 1 week and then avoid peanuts for 4 weeks, before returning to the clinic for a final OFC up to 9,000 mg peanut protein on week 48.At any time in the SU testing phase of the study, if a participant presents symptoms to the dose of 300 mg, they will resume peanut OIT and continue daily dosing with no further SU testing until the end of the study at week 48.At any time during the study, participants should not take any of the following treatments:- Another investigational drug or approved therapy for investigational use;- Any biological immunomodulatory therapy or anti-tumor necrosis factor drug;- Any concomitant immunotherapy administered to any food;- Any aeroallergen or venom immunotherapy initiated or in the up-dosing phase during study participation;- Systemic steroids  for more than 7 days;- Beta-blocking agents.Before OFCs, subjects will be asked to stop the use of antihistamines (72 h for short-acting and 5–7 days for long-acting) and theophylline (12 h).Before skin prick testing, subjects will be asked to stop the use of antihistamines (72 h for short-acting and 7 days for long-acting).All adverse events (AEs) occurring during the study will be documented in the e-CRF. Concomitant illnesses, which existed before entry into the study, will not be considered AEs unless they worsen during the treatment period. All AEs, regardless of the source of identification , will be documented, as well as their severity, seriousness, and causality. AEs attributed to food dosing during OIT will be treated as AEs of special interest (AESI). IgE-mediated reactions related to OIT dosing will be recorded separately from the AE log following the CoFAR grading system.t-test. A 50% suppression was deemed clinically significant.Based on observations from preclinical studies in mice, abatacept is expected to suppress the allergen-specific IgE surge induced by OIT. The relative change in specific/total IgE at 24 weeks will be compared between the two groups using Student's Based on the PALISADE trial , we expeThe hypothesis tested in the ATARI study is that abatacept combined with peanut OIT will lead to peanut-specific T and plasma cell suppression and thus increase the rates of clinical remission compared with peanut OIT alone. The hypothesis has strong biological plausibility and is supported by animal models, but it has never been tested in humans.ATARI is intended as a proof-of-concept study and will likely not be powered to detect differences in clinical remission. Its primary aim is, therefore, to assess differences in a proxy outcome that would be associated with the development of clinical remission.Based on the choice of proxy outcome, we observed from preclinical studies that abatacept suppresses the initial surge in sIgE with allergen exposure . This isOne risk of using the surge in sIgE as a primary outcome in such a small sample is that we are highly vulnerable to random non-specific variations in total IgE productions, which could have a confounding effect and decrease power. In our own experience of longitudinal testing during peanut OIT or epicutaneous immunotherapy, spontaneous variations in sIgE, even large, are non-clinically significant when they parallel variations in total IgE, hence the choice to measure changes in the sIgE over total IgE ratio as the primary outcome.Changes in the sIgG4/sIgE ratio are another paraclinical outcome that is often measured during OIT. Since IgG4 production follows the same non-specific expansion/contraction variations as IgE, it is generally a more reliable measure of longitudinal changes in OIT than sIgE alone. However, it is unclear how abatacept will affect sIgG4 production. Based on preclinical data, it is possible that it may suppress the rise in sIgG4, which would complicate interpretation. The sIgG4/sIgE ratio will, therefore, be treated as a secondary outcome.In addition to providing the “go/no-go” decision for a subsequent larger trial testing clinical remission, ATARI provides a unique opportunity to pilot the design for such a trial. In previous OIT studies, clinical remission had been tested using fixed durations of food avoidance, which could last up to 6 months , 42. WhiThis has led to the current design of the sustained tolerance testing phase, where OFCs are performed after a series of incremental periods of avoidance, each separated by periods of daily dosing. While the initial intent is to increase patient acceptability, an additional upside is that it provides tolerance thresholds after a wide number of avoidance periods, which is highly relevant data for patients and clinicians. The downside of the approach is the need for multiple OFC visits. In the end, the ATARI trial will provide precious information on the feasibility and acceptability of this design.per se, it can still impede physiological immune responses and increase the risk of infection while on therapy, especially if combined with methotrexate and in patients with chronic obstructive pulmonary disease (COPD)  . ImmunosIn ATARI, we chose not to confirm peanut allergy by OFC prior to randomization. The rationale was to avoid that the first contact with peanut allergen would occur without a second signal blockade, which could theoretically prime the allergic response and act as a confounder. Whether this would be the case or not is unknown, but given this is a proof-of-concept trial, we chose to err on the side of safety , 5, 44. We also decided not to exclude patients who underwent a recent known or suspected IgE-mediated reaction to peanuts to avoid any selection bias. Such a “real-life” condition is different from intentional exposure to peanuts with OFCs and appeared acceptable. We will then document the history of previous exposure to peanuts, and we should be able to control for this to some degree in the analyses.All OFCs in ATARI are open-label. Because the OFCs need to take place at very precise moments in the schedule (24 h after randomization and immediately at the end of periods of avoidance), double-blind placebo-controlled food challenges occurring on 2 different days, up to a week apart, would not have been compatible with the study design.From a methodological point of view, since patients will be effectively blinded to their treatment arm, both groups should be equally affected by the risk of the subjectivity of open-label OFCs. Therefore, the only tangible impact on study integrity would be a loss in power for OFC-dependent outcomes. This can be compensated by adjusting the sample size in an eventual phase 3 trial.The study uses the currently approved intravenous dosages of abatacept for autoimmune disorders. While subcutaneous injections may be more practical in real-life, product viscosity and the possibility of local reactions make them more difficult to blind in a research setting. Another argument for intravenous administration was the rapid distribution of the medication, which increases the likelihood of having reached therapeutic levels in lymphoid tissue by the time OIT is initiated 24–72 h later.The advantage of the symptom-driven OIT protocol compared with fixed schedules is that it allows faster progression when tolerated. This maximizes the time spent at full maintenance dose while the investigational product is at therapeutic levels. This may or may not be clinically relevant. The minimal amount of peanut protein needed to induce remission with or without abatacept is currently unknown, but experience with epicutaneous and sublingual immunotherapy suggests that it may actually be quite low , 45.The ATARI study will provide the first human data on the use of abatacept as an adjuvant to allergen immunotherapy to promote sustained tolerance. The study uses an original design taking into account various biological, clinical, and patient considerations specific to abatacept or tolerance testing, and will aid in the conduction of future large-scale trials.The studies involving human participants were reviewed and approved by Comité d'éthique du CHU Sainte-Justine. Written informed consent to participate in this study was provided by the participants' legal guardian/next of kin.CB and PA contributed to protocol and manuscript writing. CB, FG-L, ÉR, KS, FG, LP, AD, and PB contributed to investigations. PB elaborated the design of the study and promoted the study. All authors contributed to the article and approved the submitted version.