Actaea purpurea (P.K. Hsiao) J. Compton, and its closest relatives, and conducted a systematic survey of positive selection in their plastid genes using the McDonald‐Kreitman test and codon‐based methods using maximum likelihood to estimate the ratio of nonsynonymous to synonymous substitutions (ω) across a phylogeny. We found that during the speciation of A. purpurea and its relatives, all plastid genes evolved neutrally or were under purifying selection. Genome size, gene order, and number were highly conserved. Comparing to A. purpurea, plastomes of Actaea japonica and Actaea biternata had low genetic diversity, consistent with previous studies. Our work not only sheds important light on the evolutionary history of A. purpurea and its kin, but also on the evolution of plastomes during plant speciation.We have seen an explosive increase of plant plastid genome (plastome) sequences in the last decade, and the view that sequence variation in plastomes is maintained by the mutation‐drift balance has been challenged by new evidence. Although comparative genomic and population‐level studies provided us with evidence for positive evolution of plastid genes at both the macro‐ and micro‐evolution levels, less studies have systematically investigated how plastomes have evolved during the speciation process. We here sequenced 13 plastomes of  Actaea purpurea and its relatives were conserved with respect to size, structure, gene content, and order, with few variations. Positive selection analysis suggests that all plastid genes evolve neutrally or are subjected to purifying selection. Actaea japonica's low genetic diversity probably results from a recent expansion, not a recent selective sweep on plastid genes.Thirteen plastomes of 1representative populations of  Sambatti et al.  J. Compton is a perennial herb growing in the understory or the forest margins  Prantl, and the three species formed a well‐supported clade  to study genetic divergence of the group, and they found a striking pattern: all individuals of A. japonica and A. biternata shared one haplotype. Compared with A. purpurea, which had multiple haplotypes, the lack of genetic variation in A. japonica and A. biternata might be caused by a historical selective sweep, or a recent demographic expansion of A. japonica and A. biternata populations. If the selective sweep hypothesis is true, plastid genes may have played an important role in the divergence and speciation of A. purpurea and its relatives. To discriminate the two scenarios, we sequenced 13 plastomes of A. purpurea and its closest relatives, and conducted a systematic survey of positive selection in plastid genes of A. japonica + A. biternata, using both population genetic‐based test  across a phylogeny. We also investigated the structure and gene content variation in this group. Our work sheds light on the evolution of plastomes in divergence and speciation, and also on the evolutionary history of A. purpurea and its close relatives.s Hsiao, . Its flos Hsiao, . Phyloge22.1Actaea L. were sampled in the study, covering all their distribution area  for library preparation and sequencing. In short, total genomic DNA was extracted from 20 to 30 mg silica‐gel dried leaves using a modified Cetrimonium bromide (CTAB) method   and CPGAVAS2 , and subsequently checked manually in Geneious R10. In order to identify the interspecific structural variation between A. purpurea and its relatives, we used mVISTA   of all coding and noncoding regions (intergenic regions and introns).We conducted multiple sequence alignment in MAFFT v7  . Tandem Repeats Finder v4.09.1 Benson,  was used2.5A. asiatica  across a phylogeny. We used EasyCodeML v1.0   to complement the above analysis. This test calculates a neutrality index (NI) by dividing the ratio of nonsynonymous to synonymous polymorphisms within species to the ratio of nonsynonymous to synonymous divergence between species. A less than one value of NI would indicate positive selection. All MKTs were run using the MKT‐web   had the smallest plastome, and HB11 of A. japonica  had the largest  and three genes had two introns   Table .Actaea plastomes showed that IRs were relatively stable, and there was no significant expansion or contraction events. The LSC‐IRb and IRa‐LSC boundaries were located in two copies of the rps19 gene, respectively, and no displacement was detected. IRb‐SSC and SSC‐IRa boundaries were located in two copies of the ycf1 gene , ndhG, and ycf1. The corresponding noncoding regions were rpl14‐rpl16, ndhF‐trnL(UAG), trnH(GUG)‐psbA, ccsA‐ndhD, and psbT‐psbN  than A. purpurea  (Table p = 3.7E‐7)  and the SSC   and the latter two formed a clade  way or under purifying selection (ω < 1). Two genes (rpoC1 and rpoC2) had a global ω > 1, but the two‐ratio model was not significantly better than model 0 . In summary, our positive selection analysis showed no definite evidence for adaptive evolution of plastid genes.As positive selection tests require a modest to high amount of sequence variation between taxa, we only reported test results in 12 genes with suitable number of variable sites. Our results showed that no Tajima's ve Table . Branch  0 Table . Insuffi 0 Table . Notably3.6Actaea purpurea and A. japonica + A. biternata were divergent in PC1 but not in PC2  of A. japonica plastomes was much lower than that of A. purpurea , trnH(GUG)‐psbA, ccsA‐ndhD, and psbT‐psbN. Among these regions, trnH‐psbA has been a classic plastid marker in many phylogenetic and phylogeographic studies . Thus, it is possible that this gene may participate in the adaptation to different conditions for photosynthesis between A. purpurea and its relatives, considering their large distribution range.In our data set, no fixed differences in transfer RNAs or ribosomal DNAs between species were detected, which is not unexpected giving these genes conserved function. The population genetic‐based and dN/dS‐based methods yielded inconsistent results. No positively selected genes were detected in the dN/dS‐based method, as in all cases, the alternative models were not significantly better than the null models. Insufficient variation in our sequence data resulted in infinite or undefined NI values in MKTs. There were four genes with NI < 1 in MKTs, but none of them were significant. We note that the Actaea purpurea is distributed in the northern part of the group's distribution, while A. japonica is in the south, and A. biternata only in Japan  is not caused by a historical selective sweep, then a recent demographic expansion would be the only explanation. This means that the current parapatric distribution was formed by expansion of A. japonica + A. biternata from a possible previously sympatric population. In other words, the initial phase of divergence between A. purpurea and A. japonica + A. biternata most probably occurred in sympatry. This is consistent with the results of demographic modeling, showing that there has been continuous gene flow after the divergence of the two species ; formal analysis (lead); investigation (lead); writing – original draft . Yi Ren: Conceptualization (supporting); supervision . Jian‐Qiang Zhang: Conceptualization (lead); funding acquisition (lead); writing – original draft .All authors claim no conflict of interest.Figure S1–S7Click here for additional data file.Table S1–S5Click here for additional data file.


Theoretical arguments and empirical evidence have been provided in the literature for the role of fairness in wellness. In this paper, we explore the role of two potential mediating variables: autonomous human choice and social capital. Using aggregated panel data across countries belonging to the Organisation for Economic Co‐operation and Development (OECD), we compared the OECD Social Justice Index (SJI) with data on life satisfaction to test whether fairness has direct and indirect effects on wellness. Results from a series of Manifest Path Analyses with time as fixed effect, support the hypothesis that the OECD SJI is directly linked to country‐level life satisfaction, additionally revealing that its indirect effect operates primarily through people's autonomous choices in life and their country's level of social capital. Our results contribute to two distinct bodies of knowledge. With respect to community psychology, the findings offer empirical evidence for the synergistic effect of personal, relational, and collective factors in well‐being. With respect to the impact of economic inequality on wellness, we extend the literature by using social justice as a more comprehensive measure. Limitations and recommendations for future studies are discussed. What we aim to show is that the complex relationship between them can be better understood if we analyze the primary role of social justice  presents an interesting opportunity to study the role of fairness, autonomy, and relatedness on wellness since, as a group of nations, it is invested in studying and promoting well‐being policies OECD, . Recent In summary, the present study seeks to enrich our understanding of the roles of fairness, autonomy, and relatedness on wellness. In doing so, we aim to contribute to at least two distinct bodies of knowledge: the synergy of personal, relational, and collective factors in CP, and the epidemiology of well‐being across nations. Our review of the literature led us to devise a model that incorporates fairness, autonomy, and relatedness via several directional hypotheses. These will be outlined in the next section.1.1Our investigation stems from the notion that wellness is produced by experiences of fairness and conditions of justice across multiple domains of life , according to which autonomy supports well‐being , maximum likelihood with 1000 Bollen–Stine corrected bootstraps . On the other hand, the OECD SJI includes new indicators such as “poverty risk, children (<18),” “ecological footprint per capita,” and “infant mortality per 1000.” Lastly, the OECD SJI covers eight time points , compared to the six of the EU version.2.2Following the results of an earlier study . Life satisfaction is based on the answers to the following question: “Please imagine a ladder, with steps numbered from 0 at the bottom to 10 at the top. The top of the ladder represents the best possible life for you and the bottom of the ladder represents the worst possible life for you. On which step of the ladder would you say you personally feel you stand at this time?”Data on self‐reported life satisfaction were sourced from the 2.3This study examines a previously tested set of variables , which assigns each country analyzed equal purchasing power in international dollars.https://li.com/), which has developed a comprehensive index of social capital which “measures how cohesive a society is in terms of people trusting, respecting and helping one another, and the institutional structures they interact with” , p < 0.001. Therefore, to control for the effect of time, we regressed our main outcome variable (life satisfaction) onto the variable “time,” in each model considered.To best analyze the panel data, we tested whether a pooled OLS regression would be more suitable than a Fixed effect model. Results from Wald test indicate that a fixed effect model is preferable to a pooled OLS, χ2(14) = 91.97, p < 0.001, a decision was made to exclude them through listwise deletion. This resulted in the complete removal of every observation that presented a missing value at any of the time points considered  and a consequent reduction of the sample size of about 15% (from 328 to 279 observations) in all models we tested.Since our data set presented more than 5% of missing data on some variables such as OECD SJI and autonomous human choice, and Little's test (1988) showed that they were not missing completely at random (MCAR), Statistical analyses were conducted with the R v.4.0.3 software, with the support of the following packages: BaylorEdPsych v.05 , followed by autonomous human choice, β = 0.16, p < 0.001, 95% BS CI , OECD SJI, β = 0.11, p = 0.031, 95% BS CI , postcommunism, β = −0.14, p = 0.001, 95% BS CI , and lastly GDP, β = 0.09, p < 0.001, 95% BS CI . Time is the only nonsignificant variable associated to life satisfaction, β = 0.04, p = 0.135, 95% BS CI . In terms of R2, the effects of OECD SJI and covariates explain around 73.3% of variance in LS.Results from the OLS multiple regression are in line with the ones obtained in an earlier study  = 257.725, Bollen–Stine p < 0.001, CFI = 0.73, TLI = 0.422, RMSEA = 0.358, 90% CI , SRMR = 0.137. An inspection of standardized residuals and modification indices revealed a series of unspecified regressions paths, particularly from postcommunism and autonomous human choice onto GDP and social capital. Therefore, a choice was made to respecify the model by adding those previously unspecified parameters, provided their established theoretical and statistical substantial contribution  = 13.265, p = 0.195, CFI = 0.992, TLI = 0.971, RMSEA = 0.077, 90% CI , SRMR = 0.032, providing evidence that this is one of the possible models that we can apply to the data , autonomous human choice, β = 0.57, p < 0.001, 95% BS CI , and GDP, β = 0.32, p < 0.001, 95% BS CI . Moreover, social capital is also significantly predicted by autonomous human choice, β = 0.32, p < 0.001, 95% BS CI , and postcommunism, β = −0.36, p < 0.001, 95% BS CI . Similarly, GDP is significantly predicted by autonomous human choice, β = 0.26, p < 0.001, 95% BS CI , and postcommunism, β = −0.36, p < 0.001, 95% BS CI .As we can see from Table Lastly, it is worth noticing that the combined direct and indirect effects included in Model 3 explain around 72.7% of variance in life satisfaction, 76.1% in social capital, 43.5% in GDP, and 32.8% in autonomous human choice.3.1.1β = 0.24, p = <0.001, BCa 95% BS CI , followed by the path through autonomous human choice, β = 0.09, p = <0.001, BCa 95% BS CI , and GDP, β = 0.03, p = 0.02, BCa 95% BS CI .In terms of indirect effects, we found the strongest significant pathways going from OECD SJI to life satisfaction through social capital, β = 0.09, p < 0.001, BCa 95% BS CI , and through GDP, β = 0.01, p < 0.001, BCa 95% BS CI .We also found significant indirect pathways going from OECD SJI to life satisfaction, first through autonomous human choice and then through social capital, β = 0.48, p = <0.001, BCa 95% BS CI .The total of the combined direct and indirect effects of OECD SJI on life satisfaction shows a highly significant total effect, The findings described above can also be inspected in a graphic format through a series of CERES plots , is associated with a direct increase in national life satisfaction of about 0.1 points or 10% . On the other hand, each unit of increase in the OECD SJI is also associated with a direct increase in social capital of about 6.8 points , in autonomous human choice of about 13.67 points , and in GDP of about 7.14 billion dollars. In turn, life satisfaction shows an increase of about 0.3 points for every 10 points of increment in social capital, whereas 10 points of increment in autonomous human choice are associated with a direct increase in life satisfaction of about 0.06 points. Lastly, 1 billion increase in a country's GDP is associated with a direct increase of about 0.004 points in life satisfaction. Although we advise caution in drawing causal inferences from a correlational study, if our assumptions were correct, this would mean that that it might be necessary to raise the level of social justice in a country of about 4.5 points to make social capital increase life satisfaction of 1 point, all other values kept constant. On the other hand, raising a country level of social justice from its minimum to its maximum, or in other words of 10 points, would increase GDP of about 71.4 billion, which in turn would contribute only to 0.28 points of increase in life satisfaction. Similarly, an increase of 10 points in social justice would be likely to contribute of about 0.82 points of increase in life satisfaction through an increase in autonomous human choice.3.1.2χ2(8) = 10.992, Bollen–Stine p = 0.202, CFI = 0.997, TLI = 0.987, RMSEA = 0.052, 90% CI , SRMR = 0.024. In addition, a nonsignificant χ2 difference test shows that the calibration and validation sample can be considered invariant at the metric level, ΔMLR χ2 = 6.47, Δdf = 14, Δp = 0.06, and scalar level, ΔMLR χ2 = 6.47, Δdf = 3, Δp = 0.8, providing evidence that the two samples do not significantly vary with respect to intercepts and parameter estimates. These findings suggest that our main results could be replicated in other samples.Although rarely employed, cross‐validation and comparison of alternative models are always a desideratum in the analysis of covariance structures , relational , and collective factors  are significant predictors of life satisfaction. This confirms long‐held beliefs in CP that these three sets of factors operate in synergy. Furthermore, they support the notion that social policies must attend to three sets of values concurrently: personal , relational , and communal  , the OECD SJI presents a lack of contextualism and cross‐cultural sensitivity that should not be ignored when interpreting the results of this study.Regarding our main findings, we should be mindful that these have been derived from a correlational study and as such we cannot exclude that some of the variables we modeled as endogenous could be in fact exogenous and vice versa. Although we provided some examples of alternative models, future studies should explore other candidate models, which could not be tested in this study. In particular, we recommend that future studies explore in more detail the alternative model in which GDP is treated as antecedent of the relationship between social justice and autonomous human choice and national happiness.Additionally, we cannot exclude that unmodelled variables, other than social justice and postcommunism might contribute to explain variation in social capital, autonomous human choice, and GDP at the country level. In the same vein, there might be some unexplored predictors of life satisfaction, which were not included in this study.In terms of sampling, one of the main limitations is that our data set includes only aggregated data at the country level. As such, we were unable to analyze our data through multilevel models as in the previous case  reaches a power of 0.25, which is well below the recommended threshold of 0.8. Given the underpowered model, we cannot be confident in having escaped some Type II error. Lastly, the relatively small sample size combined with a limited number of time points prevented us from using longitudinal models to better analyze panel data.As a last note of caution, we should bear in mind that our sample does not extend beyond OECD countries; therefore, we should be careful not to generalize these results to other countries.6In this paper, we provided quantitative evidence to support the direct link between social justice and life satisfaction at the national level. We have also investigated an indirect relationship between these two constructs, which is mediated by social capital, autonomy, and GDP. However, our findings warn us once more against considering GDP as the primary measure of country‐level wellness. Indeed, amongst all the variables employed in our study, GDP was the weakest link with national life satisfaction and the other variables we considered. While autonomous human choice had a positive relationship to social capital, GDP, and life satisfaction, postcommunism correlated negatively with all these variables. Our main findings show that promoting social justice is likely to increase aspects of social capital such as social relations, trust towards others and social institutions, and engagement in social life, all of which result in gains in life satisfaction. At the same time, equal opportunities and sound distributive policies might propel the economy of a country, with positive effects on citizens' satisfaction. Lastly, social justice has a positive impact on people's autonomous choice, which is another important element for the pursuit of a happy life.These results suggest that the well‐being scholarship should consider higher‐level variables that are responsible for people's happiness. Beyond the individual, it is important to consider national‐level factors. Guided by CP's ecological perspective, we were able to offer evidence that confirms the interdependence among personal (autonomy), relational , and communal  determinants of wellness at the national level of analysis. Whereas prior epidemiological data elucidated the important role of economic inequality in well‐being and ill‐being, our study goes beyond financial disparities. The framework of social justice employed in the current study also includes a variety of factors impinging on distributive and procedural justice, which are directly and indirectly involved in promoting national life satisfaction.Turning to the specific contribution that these findings make to the field of CP, our aim is to help the discipline expand its range of action towards the global arena (Marsella, https://publons.com/publon/10.1002/jcop.22822The peer review history for this article is available at


By being aware of the associated factors of primary snoring (PS) and obstructive sleep apnoea (OSA) in sleep bruxism (SB) patients, dentists may contribute to the screening and early recognition of SB patients with PS or OSA.To identify the associated factors of PS and OSA from questionnaire‐based data in SB patients.A total of 968 self‐reported SB patients  were retrospectively enrolled. Self‐reported sleep‐related breathing status  was the dependent variable. Independent variables were questionnaire‐based data on demographics, lifestyle, psychological status, pain and sleep.For PS, no statistically significant associated factor was identified in analyses. For OSA, increased age (OR = 1.04 [1.03–1.06]), male gender (OR = 3.33 [2.17–5.00]), daily alcohol consumption (OR = 1.96 [1.18–3.33]), depression (OR = 1.10 [1.06–1.14]), daytime sleepiness (OR = 2.94 [1.85–4.76]) and high risk of gastroesophageal reflux disease  were found to be significant risk factors, while high risk of temporomandibular disorder (TMD) pain (OR = 0.51 [0.30–0.86]) and chronic pain (OR = 0.73 [0.59–0.90]) were significant protective factors. These results were confirmed in the subsequent network analysis.Within the limitations of this study, no associated factor is identified for PS. For OSA, dentists should keep in mind that increased age, male gender, daily alcohol consumption, depression, daytime sleepiness and high GERD risk are associated with increased OSA risk in SB patients, while high TMD‐pain risk and chronic pain are associated with decreased OSA risk in this population. The reasons of referring patients to the OPD clinic include tooth wear, OSA/snoring and TMD/oro‐facial pain. Prior to the first appointment at the OPD clinic, all referred patients were asked to fill in a set of questionnaires that were used as part of the regular intake procedure. Among others, these questionnaires included questions about patients' demographics, life style, psychological status, pain‐related complaints and sleep‐related complaints. In addition to the regular set of questionnaires, as part of the standard care procedure of the OPD clinic, dedicated questionnaires were completed by patients with specific complaints. For example, for patients who reported SB, the Oral Behaviours Checklist (OBC), a self‐report scale to quantify the frequency of jaw behaviours,2.2Sleep‐related breathing status  was the dependent variable in this study. As such, participants were categorised as participants without sleep‐related breathing condition, participants with probable primary snoring (primary snorers), or participants with probable OSA (OSA patients). The STOP‐Bang  questionnaire2.3Demographic variables: age and gender;Lifestyle variables: smoking, daily alcohol consumption and intake of sleep medication;Psychological variables: somatic symptoms, depression, anxiety and stress;Pain‐related variables: temporomandibular disorder (TMD) pain, TMD‐related headache (temple area), primary headache (migraine or tension type) and chronic pain (intensity and disability);Sleep‐related variables: daytime sleepiness, gastroesophageal reflux disease (GERD) and dry mouth.In this study, independent variables were divided into five categories:All the above‐mentioned information was obtained from the set of questionnaires of the OPD clinic. Demographic variables and life style variables were obtained from a custom‐made questionnaire focusing on the patients' personal information. Data about somatic symptoms, depression and anxiety were obtained from the Patient Health Questionnaire (PHQ)‐15,2.4p < .1) with the dependent variable were considered eligible to be entered in multivariable models. Before entering significant variables in the multivariable logistic regression model, multicollinearity was checked using a tolerance value <0.1 or variance inflation factor (VIF) >10.p < .05. Analyses were conducted using the IBM SPSS Statistics 27 software package (IBM Corp.).As descriptive statistics, nominal and ordinal data were presented as percentages. For continuous data, Kolmogorov–Smirnov test was first used to check if the data was normally distributed. Normally distributed data were presented as mean ± SD; data that were not normally distributed were presented as median . Multinomial logistic regression modelling was used to evaluate the association between the dependent variable  and the independent variables. As the first step, univariable logistic regression models were built to assess the association between the dependent variable and each of the independent variables. Independent variables that showed at least a weak association , a programming software, using the package ‘bootnet’ (version 1.4.3)3Of the 2218 patients who completed the OBC from January 2017 to December 2020, 1024 patients reported to grind their teeth more than one night per week. Of these 1024 patients, 56 adolescents were excluded so that finally 968 adult patients were included in this study. Of the 968 participants, 726 (75%) were categorised as participants without sleep‐related breathing condition, 71 (7.3%) were categorised as primary snorers, and 171 (17.7%) were categorised as OSA patients. Descriptive statistics of the participants are shown in Table The results of the logistic regression analyses are shown in Table Results of the network analyses for PS and OSA are shown in Figures 4The present study aimed to identify associated factors of PS and OSA from self‐reported questionnaire data in SB patients. For PS, no associated factor was identified, neither in the multinomial logistic regression model nor in the network analysis. For OSA, increased age, male gender, daily alcohol consumption, depression, daytime sleepiness and high risk of GERD were found to be risk factors of OSA, while high risk of TMD pain and chronic pain were found to be protective factors of OSA, both in the multinomial logistic regression model and in the network analysis.Notably, there was a female dominance  in the included SB patients. Regarding the prevalence of SB in men and women, previous studies reported conflicting results, i.e., some studies found that SB is more prevalent in women than in men,16. In addition, for patients with depression, antidepressants may worsen or induce SB.How increased age, male gender, alcohol and daytime sleepiness may contribute to the OSA pathophysiology has been thoroughly discussed in previous studies.per se.It is noteworthy that, compared with depression, arousal is a more well‐recognised connecting factor between OSA and SB, which may better explain the association between OSA and SB at event level. A previous PSG study reported the temporal association between OSA events and SB events, and the authors hypothesized that the co‐activation of oropharyngeal muscles may maintain the patency of the airway but may lead to SB at the same time, suggesting a potential protective role of SB against airway obstruction.In addition to GERD, the present study also suggested a comorbidity network among TMD pain, OSA and SB. The negative association between TMD pain and OSA in SB patients may be explained by the gender difference between participants without sleep‐related breathing condition and OSA patients: a majority  does not satisfy the recommended standard that events per variable (EPV) in multinomial logistic regression model should be more than 20.5Within the limitations of this study, no associated factor is identified for PS. For OSA, dentists should keep in mind that increased age, male gender, daily alcohol consumption, depression, daytime sleepiness and high GERD risk are associated with increased OSA risk in SB patients, while high TMD‐pain risk and chronic pain are associated with decreased OSA risk in this population.Zhengfei Huang involved in conceptualization, data acquisition, analysis and writing the original draft. Ghizlane Aarab involved in conceptualization and writing—review and editing. Thiprawee Chattrattrai involved in analysis and writing—review and editing. Naichuan Su involved in analysis and writing—review and editing. Catherine MC Volgenant involved in data acquisition and writing—review and editing. Antonius AJ Hilgevoord and Nico de Vries involved in writing—review & editing. Frank Lobbezoo involved in conceptualization, data acquisition and writing—review and editing.There is no conflict of interest.https://publons.com/publon/10.1111/joor.13354.The peer review history for this article is available at Appendix S1‐S2Click here for additional data file.


Better therapeutic options other than conventional chemotherapy for pediatric patients with refractory Langerhans cell histiocytosis (LCH) remain undetermined.We successfully treated two patients with refractory and risk organ negative LCH with clofarabine (CLO) monotherapy after recurrence. We administered total 23 courses of CLO monotherapy in patient 1 and 4 courses in patient 2. Both patients had distinct clinical manifestations but achieved a durable complete response with acceptable adverse effects of transient myelosuppression. CLO monotherapy was still effective when he had the second recurrent lesion after first completion of CLO in patient 1. We could discontinue prednisolone to control his refractory inflammation of LCH after completing CLO chemotherapy in patient 2.Although large‐scale studies are warranted, CLO monotherapy could be a therapeutic option for high efficacy and feasibility besides other intensive combination chemotherapies or allogeneic hematopoietic stem cell transplantation for refractory LCH without risk organ involvement in children. The tumor size decreased after two cycles of CLO monotherapy , anemia, and thrombocytopenia, which resolved with granulocyte colony‐stimulating factor (G‐CSF), red blood cell concentrate (RBC) transfusion, and platelet concentrate (PC) transfusion. There were no life‐threatening infections such as sepsis and fungal pneumonia during any cycles of CLO monotherapy.A 3‐year‐old boy was diagnosed with LCH‐MS with periorbital bone and multiple skin lesions at 2 years of age Figure . He was 2.2A 2‐year‐old boy was diagnosed with single‐system multisite LCH  at 6 months of age, which developed to LCH‐MS at 1 year of age. He received 6‐week induction chemotherapy of PSL, VCR, and Ara‐C according to the JLSG‐02 protocol and achieved a partial response. During the maintenance therapy, he developed recurrent fever and abnormal skin lesions Figure . A skin 3Patients with LCH generally have good prognoses, and the 5‐year OS is >85% even in patients with LCH‐MS and risk organ involvement.CLO is a second‐generation purine analog resembling cladribine and fludarabine in structure, except for its biochemical modifications that enhance its resistance to deamination and degradation.Simko et al. reported that among 11 patients with refractory or recurrent LCH, 10 responded to CLO monotherapy. The estimated progression‐free survival and OS at 1 year were 76% and 91%, respectively. There were no life‐threatening adverse effects during therapy in their study.There remains the need for a clearly defined third‐line chemotherapy for refractory and risk organ negative patients. Considering the effectiveness and feasibility of these treatment strategies, CLO monotherapy could be a therapeutic option besides other intensive chemotherapy regimens or allogeneic HSCT for treating refractory and/or recurrent LCH, as our two patients we presented here, although large‐scale studies are required to make a definitive conclusion.The authors have no conflict of interest in the publication of this paper.Conceptualization, M.I. and Y.S.; Investigation, M.I. and Y.S.; Resources, M.I., T.N., S.K., T.S., K.M., Y.W., N.S., Y.S.‐N., M.O., T.R. and H.N.; Data Curation, M.I.; Writing—Original Draft; M.I.; Writing—Review & Editing; Y.S.; Funding Acquisition, Y.S.; Supervision, S.K.All authors had full access to the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. The off‐label use of CLO was approved by the chemotherapy protocol committee of the Tohoku University Hospital. Informed consent was obtained from the guardians of two patients in this study.


Intracerebral hemorrhage should be considered as a possible adverse event in patients with anaphylactic shock who are treated with adrenaline administration, especially in those at high risk of serious bleeding events. Although prompt intramuscular injection of adrenaline is the first‐line treatment for anaphylactic shock, physicians should recognize that adrenaline injection can lead to intracerebral hemorrhage, especially in high bleeding risk patients. She denied any personal history of drug allergy or anaphylaxis and no allergic reactions had previously occurred. She had a history of hypertension, dyslipidemia, and arteriosclerosis obliterans treated with axillary‐femoral bypass, for which she was prescribed aspirin 100 mg per day. She was a former smoker with a quarter pack of cigarettes per day for 50 years.Empirically, she was given intravenous antibiotics (1 g dose of cefoperazone‐sulbactam) for a suspected bacterial infection 3 h after initiation of hemodialysis. A few minutes later, she proceeded to develop periorbital edema, dyspnea, and altered consciousness, and her blood pressure fell to 54/30 mmHg. Her family physician diagnosed her with anaphylactic shock caused by the antibiotic and intramuscularly administered 0.3 mg dose of adrenaline (1:1000 dilution) twice every 5 min, as well as 5 mg dose of chlorpheniramine maleic acid, 20 mg dose of famotidine, and 125 mg dose of methylprednisolone. A few minutes after receiving adrenaline, the patient developed tachycardia with a pulse rate of 140 beats/min and hypertension with a blood pressure of 208/88 mmHg. Thirty minutes after onset upon arrival of emergency medical services personnel at the scene, her blood pressure fell to 94/44 mmHg. She was admitted to our institution for further treatment 1 h after the incident.En route to the emergency department, she appeared pale. She had a Glasgow Coma Scale (GCS) score of 12 (E2V4M6), respiratory rate of 20 breaths/min, arterial oxygen saturation of 100% with oxygen delivered through a face mask (3 L/min), pulse rate of 110 beats/min, blood pressure of 104/78 mmHg, and body temperature of 37.1°C. Neurological examination revealed no focal deficits except for altered mental status, presumably attributed to anaphylactic shock.4 cells/L), normal prolonged prothrombin time (11.5 s), and activated partial thromboplastin time (43.1 s). Blood culture test did not identify any bacteria. A head computed tomography (CT) scan was conducted to determine the causes of altered consciousness other than anaphylactic shock. The CT scan revealed a hemorrhagic lesion measuring 9 × 9 × 5 mm in the right basal ganglia (Figure Laboratory test results demonstrated chronic kidney disease as indicated by urea nitrogen levels of 17 mg/dL, elevated creatinine levels of 4.86 mg/dL, thrombocytopenia (blood platelets cell count of 9.0 × 10a Figure . We conda Figure . During The patient was transferred to the local rehabilitation hospital 28 days after admission with weakness of the left upper and lower limbs, which affected her daily life, and a modified Rankin Scale score of 5.3We herein report a 75‐year‐old female patient on dialysis with serious sequelae caused by intracerebral hemorrhage following anaphylactic shock treated with intramuscular administration of adrenaline.Leukopenia, non‐occlusive mesenteric ischemia, ischemic stroke, and intracerebral hemorrhage are adverse events after anaphylactic shock that have previously been reported in the medical literature.Although other etiologies cannot be excluded, we assume that acute hypertensive attack induced by adrenaline and dialysis with a high risk of hemorrhage may be associated with the pathogenesis of intracerebral hemorrhage, in our case at least partially. Indeed, during anaphylactic shock, our patient's cerebral blood flow decreased more than what could be anticipated based on the blood pressure observed in animal experiments.Adrenaline is one of the most commonly used medications to manage conditions such as cardiac arrest, asthma, septic shock, and anaphylactic shock, but serious adverse events can occur, including arrhythmias, lactic acidosis, pulmonary edema, and cerebrovascular disease.Remarkably, other multiple factors may also have induced intracerebral hemorrhage and development of hematoma expansion in the present case. First, higher age and smoking history or underlying diseases including hypertension, dyslipidemia, and chronic kidney disease could precipitate the intracerebral hemorrhage.4Intracranial hemorrhage following anaphylactic shock treated with intramuscular administration of adrenaline should be recognized as an adverse event, especially in high bleeding risk patients.Shunki Yamamoto, Takashi Hongo, and Atsunori Nakao conceptualized the study Shunki Yamamoto, Takashi Hongo, Tomokazu Tamura, and Atsunori Nakao performed data curation. Shunki Yamamoto, Takashi Hongo, Tetsuya Yumoto, Hiromichi Naito, and Atsunori Nakao investigated the study. Shunki Yamamoto and Takashi Hongo prepared original draft. Takashi Hongo, Tetsuya Yumoto, Hiromichi Naito, and Atsunori Nakao reviewed and edited the manuscript.The authors declare that they have no competing interests.Written informed consent for participation was obtained.Written informed consent was obtained from the patient for the publication of this case report and the accompanying images. A copy of the consent form is available for review by the Editor‐in‐Chief of this journal.


Heart failure (HF) is a major public health concern worldwide. The diversity of HF makes it challenging to decipher the underlying complex pathological processes using single biomarkers. We examined the association between urinary peptides and HF with reduced (HFrEF), mid‐range (HFmrEF) and preserved (HFpEF) ejection fraction, defined based on the European Society of Cardiology guidelines, and the links between these peptide biomarkers and molecular pathophysiology.In silico analysis suggested that urinary biomarker abnormalities in HF principally reflect changes in collagen turnover and immune response, both associated with fibrosis. Unsupervised clustering separated study participants into two clusters, with 83% of non‐HF controls allocated to cluster 1, while 65% of patients with HF were allocated to cluster 2 (P < 0.0001). No separation based on HF subtype was detectable.Analysable data from 5608 participants were available in the Human Urinary Proteome database. The urinary peptide profiles from participants diagnosed with HFrEF, HFmrEF, HFpEF and controls matched for sex, age, estimated glomerular filtration rate, systolic and diastolic blood pressure, diabetes and hypertension were compared applying the Mann–Whitney test, followed by correction for multiple testing. Unsupervised learning algorithms were applied to investigate groups of similar urinary profiles. A total of 577 urinary peptides significantly associated with HF were sequenced, 447 of which (77%) were collagen fragments. Heart failure, irrespective of ejection fraction subtype, was associated with differences in abundance of urinary peptides reflecting collagen turnover and inflammation. These peptides should be studied as tools in early detection, prognostication, and prediction of therapeutic response. (I) chain; COL1A2, collagen alpha‐2(I) chain; COL2A1, collagen alpha‐1(II) chain; COL3A1, collagen alpha‐1(III) chain; FGA, fibrinogen alpha chain; HF, heart failure; HFmrEF, heart failure with mid‐range ejection fraction; HFpEF, heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; IGF, insulin‐like growth factor; UMOD, uromodulin.Clear differences between urinary peptides from patients with heart failure and controls are observed, indicating alterations in collagen turnover and immune response; while there is a high similarity between urinary profiles among heart failure subtypes. COL1A1, collagen alpha‐1 Heart failure (HF) is a syndrome, not a discrete diagnosis, although three subtypes, based on left ventricular ejection fraction (EF), are commonly recognised. However, HF is likely to be far more heterogeneous. Multiple aetiologies (including ischaemic heart disease and hypertension) may lead to abnormalities in the systolic and/or diastolic function of the heart. Because of the similarity in the molecular events underlying many of these clinical pathways, it is challenging to differentiate the molecular processes associated with different subtypes of HF, indicating a need for a deeper understanding of the molecular mechanisms leading to HF. Describing the complex pathophysiology of HF using single biomarkers is challenging and does not reflect the clinical and pathophysiological complexity of the syndrome.The application of proteome analysis to clinically relevant problems is an emerging and promising field of biomarker research.The aim of the present study was a comprehensive description of molecular differences at the level of the urinary proteome between individuals with HF and without HF, as well as between HF subtypes. The focus was placed on peptides with high specificity for HF based on the comparison between case and control groups matched for kidney function, sex, age, blood pressure and the presence of diabetes and hypertension.We extracted patient data from the Human Urinary Proteome database of capillary electrophoresis mass spectrometry (CE‐MS) data on urinary peptidesUrine samples were obtained from the following studies: (i) STANISLAS cohort studyn = 154). Only patients with NT‐proBNP or BNP >125 pg/mL or >35 pg/mL were included. To account for an update in the ESC guidelines, the diagnosis of HF subtypes was assigned based on the EF thresholds in the ESC recommendationsHeart failure was defined using the European Society of Cardiology (ESC) guidelines recommended at the time of patients' recruitment. In all cases, the diagnosis was based on the presence of symptoms or signs of HF, caused by a structural and/or functional heart abnormality. Patients with HF with missing measurements of EF or natriuretic peptides [N‐terminal prohormone of B‐type natriuretic peptide (NT‐proBNP) or B‐type natriuretic peptide (BNP)] were excluded (n = 451). The non‐HF control group consisted of individuals who at the time of urine sampling had no known diagnosis of HF (n = 3977). The latter group included, among others, healthy individuals, patients with chronic kidney disease (CKD), hypertension, diabetes or coronary artery disease (or a combination of these pathologies). CKD was defined based on the clinical diagnosis and/or on the kidney function (eGFR < 60 mL/min/1.73 m2). eGFR was estimated based on the Chronic Kidney Disease Epidemiology Collaboration (CKD‐EPI) equation. Hypertension was diagnosed based on the use of antihypertensive drugs, SBP of 140 mmHg or higher, and/or DBP of 90 mmHg or higher.Figure Individuals without HF with NT‐proBNP >300 pg/mL (or BNP >100 pg/mL), EF <50% or with New York Heart Association (NYHA) III–IV symptoms were excluded from the control group .Proteases responsible for the generation of the urinary peptide fragments were predicted using the Proteasix tool.Figure n = 442), HFmrEF (n = 144) and HFpEF (n = 187). For each of the subtypes, the same number of controls were matched , as shown in Table Table Among the 4970 participants included in the study after data curation Figure 1A, caseP < 0.05) between patients with HF and controls. The top 20 peptides with the lowest P‐value for differential expression between groups are listed in Table Table Figure In this study, 3332 sequenced urinary peptides were investigated. A total of 577 peptides differed significantly . Moreover, we investigated an association of peptide abundance with eGFR (used as a continuous variable) in patients with HF. Seventy‐three peptides showed significant correlation (P < 0.05 BH adjusted), with rho value above 0.2. An additional 210 peptides (P < 0.05 BH adjusted) had rho values below 0.2, indicating very weak/negligible relationship.To assess the specificity of the findings for HF, we compared the 577 peptides that were significantly different between patients with HF and controls with the 273 peptides significantly associated with CKD in a previous study CKD27320. The P < 0.0001)   were allocated to cluster 2, while 83% of non‐HF controls were allocated to cluster 1  Figure 2B. Ther differences between the three HF subtypes in pairwise comparisons. Only 13 peptides were significantly different between HFrEF and HFpEF Figure Combining the urinary peptides with best discriminatory ability (based on the AUC) into classifiers using support vector machines did not enable reliable differentiation of the subtypes of HF  were shortlisted . While our data demonstrate highly significant differences between patients with HF and non‐HF controls for multiple urinary peptides, there were very few differences among the different HF subtypes defined by EF. Our study was also designed to identify HF specific peptides. To limit the potential impact of co‐existing diseases (CKD) and various other factors (e.g. age) on urinary peptides, analysis was performed in matched cohorts. Identified peptides significantly associated with HF were clearly distinct from those peptides associated with CKD, supporting their specificity for HF.This is the first investigation of the urinary proteomic profile of more than 1500 patients with HF encompassing the full spectrum of EF and non‐HF controls  in patients with HF, suggesting that disturbance in collagen degradation, possibly due to increasing stability of collagen networks and cross‐linking that protects them from degradation. Our findings are consistent with the observation that all major HF subtypes are associated with cardiac fibrosis and potentially also fibrosis of other organs and tissues including arteries, where collagen degradation may play a major role.Circulating biomarkers reflecting collagen metabolism have been shown to be associated with histologically proven myocardial fibrosis in HF .Besides pathways reflecting alteration in collagen turnover , the second most prominent finding was pathways associated with immune response, mostly innate immunity. Our analysis revealed alterations in Toll‐like receptor (TLR) cascades, the involvement of which in the inflammatory response in HF is well recognised.n = 800.Surprisingly, the three HF subtypes could not be separated based on urinary peptide analysis, whereas the differences between patients with HF and non‐HF controls were obvious. This implies that the molecular alterations in urine are indifferent to the EF. In line with our findings, it has been proposed that changes in fibrillar collagen (collagen type I) turnover are common in HF independent of EF.Collectively, considering the complex pathophysiology underlying HF, urinary proteomics may have an advantage to better profile fibrosis and also systemic impact of HF in comparison to single biomarkers. Based on urinary peptide alterations, it appears that targeting collagen degradation may be feasible and a novel approach to combat fibrosis. Further studies are planned to evaluate the applicability of the biomarkers we have identified for detection of patients with HF. One aim is investigating if the biomarkers identified here would enable early detection of HF, prior to the onset of symptoms, to enable timely  intervention. In addition, we aim at testing the value of the biomarkers described here in predicting disease progression. Further, testing of the biomarkers for their value in predicting drug response, as was e.g. shown for CKD273,The strength of our study was a large sample size covering patients with HF across the full range of EF. As a result, confidence in the validity of the findings is very high. Moreover, all urinary peptide datasets were acquired using the same analytical platform (CE‐MS), with analysis and data processing performed according to ISO13485 standards. This allows for generation of highly comparable data, enabling comparisons in the wide spectrum of conditions.Limitations included that individual patient data were derived from the different cohorts of HF patients and controls enrolled at multiple clinical centres. However, case‐control matching for clinical/demographical variables known to have an impact on urinary peptides allowed to harmonise the data in the respective comparisons. Although efforts were made to collect urine samples on the same day as other study assessments, this may not have been the case for every participant. There was no standard operating procedure applied for the collection of all urine samples, specifically there were no requirements made for an early morning or mid‐stream sample. However, previous studies based on CE‐MS have shown good reproducibility of data, even if sampling is not fully standardized.In addition, this was a retrospective cross‐sectional analysis. Therefore, for non‐HF controls, the information on measurements performed for patients suspicious for HF  is frequently missing. Our study was not designed to compare the diagnostic performance of urinary peptides with NT‐proBNP and BNP. Those plasma biomarkers were used as one of the criteria for defining HF and thus inclusion/exclusion of patients in our study, preventing an unbiased comparison. A previous study demonstrated that a set of urinary peptides had similar utility as BNP in diagnosing patients with HF, while a combination of BNP with urinary peptides provided additional diagnostic information.Heart failure is consistently associated with differences in urine peptides, compared to non‐HF controls, reflecting fibrosis and the systemic impact of HF. HF subtypes based on left ventricular phenotype, although clinically different, are very similar at the level of urinary peptides. Definition of HF subtypes based on molecular changes, similar to oncology, may be more appropriate, especially when aiming for personalized intervention. Application of urinary peptides to support management of patients with HF, although feasible, requires further assessment in prospective trials, to investigate the potential for early detection, molecular subtyping, prediction of therapeutic response as well as guiding therapeutic intervention.AC, CD, JD, AG, AM, JR, NG, PR, FZ, HM, ZZ, JS, AL are supported by the EU Commission via the HOMAGE (HEALTH‐FP7–305507 HOMAGE) project. CD, FZ, HM, JD and JS were previously supported by the EU‐MASCARA (HEALTH‐FP7–278249) project, and CD and JM receive support from the British Heart Foundation (RE/18/6/34217). TH is supported by the EU Commission via the CaReSyAn Project (MSCA‐ITN‐2017‐Project ID: 764474). VJ is supported by the Deutsche Forschungsgemeinschaft'  by the Transregional Collaborative Research Centre  (subproject S‐03). PR, NG, FZ are supported by the RHU Fight‐HF, a public grant overseen by the French National Research Agency (ANR) as part of the second ‘Investissements d'Avenir’ program (reference: ANR‐15‐RHUS‐0004), and by the French PIA project ‘Lorraine Université d'Excellence’(reference: ANR‐15‐IDEX‐04‐LUE). The Stanislas Cohort is sponsored by Nancy CHRU (France); its biobanking is managed by Biological Resource Center Lorrain BB‐0033‐00035. Generation Scotland received core support from the Chief Scientist Office of the Scottish Government Health Directorates [CZD/16/6] and the Scottish Funding Council [HR03006] and is currently supported by the Wellcome Trust [216767/Z/19/Z]. The non‐profit Research Institute Alliance for the Promotion of Preventive Medicine received a non‐binding grant from OMRON Healthcare Co., Inc., Kyoto, Japan.Conflict of interest: HM, AV, JS and VJ are members of the European Uraemic Toxin Working Group (EUTox). HM is cofounder and co‐owner of Mosaiques Diagnostics. TH, MM, JR, JS and AL are employees of Mosaiques Diagnostics GmbH. PR reports personal fees (consulting) for Idorsia,G3P, KBP, and Sanofi, honoraria from AstraZeneca, Bayer, Boehringer Ingelheim, CVRx, Fresenius, Grunenthal, Novartis, NovoNordisk, Sequana medical, Servier, Stealth Peptides, Ablative Solutions, Corvidia, Relypsa and Vifor Fresenius Medical Care Renal Pharma, outside the submitted work, PR is the cofounder of CardioRenal. NG reports personal fees from Novartis, AstraZeneca, Bayer, Boehringer, Vifor, outside the submitted work. FZ reports personal fees from Janssen, Bayer, Amgen, CVRx, Boehringer, AstraZeneca, Cardior, Cereno pharmacuetical, Applied Therapeutics, Merck, Novartis, NovoNordisk, Myokardia, Actelion, Owkin, Cellprothera, other from CVCT and Cardiorenal, outside the submitted work. AM reports personal fees from Orion, Servier, Otsuka, Philips, Sanofi, Adrenomed, Epygon and Fire 1 and grants and personal fees from 4TEEN4, Abbott, Roche and Sphyngotec. JM reported other support from AstraZeneca; non‐financial support from Cytokinetics, Bayer, Theracos, Oxford University, Dalcor, Merck, GlaxoSmithKline, Bristol Myers Squibb, Vifor‐Fresenius, Kidney Research UK, Alnylam, Abbvie, Cyclerion, Cardurion; and personal fees from Amgen, and personal fees from Abbott, Hickma, Sun Pharmaceuticals, Servier lecture fees outside the submitted work.Appendix S1. Supplementary Methods. Detailed information on CE‐MS analysis, peptide sequencing and bioinformatics.Table S1. Characteristics of the matched heart failure patients. Calculations are presented as median [interquartile range] or number (%). Bold indicates P < 0.05. Mann–Whitney test was used for continuous variables, while the Chi‐squared test was applied for categorical variables.Table S2. Discriminatory metrics for the selected urinary biomarkers. Information is given for the top 20 peptides providing the greatest discrimination between patients with HF (n = 773) and matched controls (n = 773) as well as between matched controls and patients with HFrEF (n = 442), HFmrEF (n = 144), HFpEF (n = 187) , frequency, AUC, sensitivity, specificity, PPV and NPV are provided. Sensitivity and specificity values are given at the optimum cut‐off level that was defined to maximise both sensitivity and specificity values.Table S3. Distribution of peptides by original cohort. Analysis was performed for the three most representative heart failure cohorts with the highest number of patients . Information is given for the top 20 peptides providing the greatest discrimination between patients with HF (n = 773) and controls (n = 773). Average abundance, fold change and frequency in each analysed cohort are given. Differences in peptide abundance between three groups was evaluated using Kruskal–Wallis test, followed by post‐hoc analysis using Dunn test with Bonferroni method for P‐value adjustment.Table S4. Distribution of peptides in patients enrolled with acute (n = 89) and chronic heart failure (n = 682). Information is given for top 20 peptides providing the greatest discrimination between patients with HF (n = 773) and controls (n = 773). Average abundance, fold change and frequency in each analysed group are given. Peptide abundance between three groups was evaluated using Kruskal–Wallis test, followed by post‐hoc analysis using Dunn test with Bonferroni method for P‐value adjustment.Table S5. Urinary peptide differences between heart failure subtypes. Significantly altered peptides between HFrEF (n = 117) and HFpEF (n = 117) matched for sex, age, eGFR, systolic and diastolic blood pressure, diabetes and hypertension are listed, along with peptide characteristics , frequency, average abundance and P‐value (BH adjusted). Discriminatory metrics i.e. AUC, sensitivity, specificity, PPV and NPV are given. Significant peptides were defined as passing the criterion of P < 0.05 and the frequency threshold of 30%. Peptides are sorted by increasing P‐value.Table S6. List of the shortlisted in silico predicted proteases. Proteases that did not meet the criteria for shortlisting (i.e. at least one protease/CS association reported in the literature and the percentage of cleavage events above 1%) are marked in grey.Click here for additional data file.Figure S1. Workflow for matching patients with heart failure. Participants diagnosed with HFrEF (n = 442), HFmrEF (n = 144), HFpEF (n = 187) were matched for sex, age, eGFR, systolic and diastolic blood pressure, diabetes and hypertension. This resulted in the selection of 117 individuals in each group. *When performing matching for patients with HFmrEF and HFpEF, HFmrEF patients that have been matched to HFrEF were considered. †When performing matching for patients with HFrEF and HFpEF, HFrEF patients that have been matched to HFmrEF were considered, similarly ‡HFpEF that have been matched to HFmrEF were considered.Click here for additional data file.Figure S2. Analysis of heart failure patients stratified by cohort. Analysis was performed for three cohorts with the highest number of HF patients . Results are provided for peptides found to be significantly different between all patients with HF (n = 773) and controls (n = 773) including 577 peptides (A and B) and, separately, the 20 peptides with the greatest discrimination between HF and controls (C). Correlation of (A) the peptide fold changes calculated in selected cohorts and in the complete HF cohort (n = 773), in comparison to all controls included in the study and (B) average peptide abundance in three HF cohorts. (C) Box‐plots displaying peptide abundance per cohort. Peptide abundance for the controls (n = 773) is provided as a comparator. Mean is indicated with a red diamond.Click here for additional data file.Figure S3. Analysis of heart failure patients stratified based on the enrolment status (acute and chronic heart failure). (A) Correlation of peptides significantly different between HF and controls when comparing average peptide abundance observed in patients with acute (n = 89) and chronic HF (n = 682). (B) Distribution of abundance for top 20 peptides exhibiting greatest discrimination between HF and controls  The comparison was performed between 273 CKD associated peptides defined previously when comparing patients with CKD and normal controls  and 577 HF associated peptides defined in this study. Seventy‐one peptides were found overlapping between these two sets of biomarkers. (B) Correlation analysis of fold changes for 71 common peptides is presented.Click here for additional data file.Figure S5. Summary of the consensus clustering results. Segregation of patients with HF only into clusters for k = 2–8 solutions. Percentage of patients assigned to the class is given. Chi‐squared test was applied to assess differences in the distribution of patients within the class.Click here for additional data file.Figure S6. Performance of biomarker panels discriminating between heart failure subtypes. The urinary peptidomics data from patients with HFrEF (n = 117), HFmrEF (n = 117) and HFpEF (n = 117) matched for sex, age, eGFR, SBP, DBP, diabetes and hypertension, were randomly divided into two sets . Thirty peptides with the highest AUC were selected in the training set  and combined using SVM, followed by optimisation of SVM parameters. Performance of biomarkers was assessed in the test set. Receiving operating characteristic analysis based on test set data was conducted for combination of biomarkers discriminating (A) patients with HFrEF (n = 47) from patients with HFmrEF (n = 47), (B) patients with HFmrEF (n = 47) from patients with HFpEF (n = 47) and (C) patients with HFrEF (n = 47) from patients with HFpEF (n = 47). Information on specificity and sensitivity of the model at the pre‐specified cut‐off (based on the Youden index J) is provided.Click here for additional data file.Figure S7. Urinary peptides differences between heart failure subtypes and controls. Volcano plot showing distribution of the identified sequenced peptides between matched controls and patients with HFrEF, HFmrEF and HFpEF. Directionality of the difference, magnitude as well as significance level  are displayed. Discrimination between collagen and non‐collagen derived peptides is provided. Peptides originated from proteins for which at least 10 significant peptides were identified  when comparing all patients with HF and controls are color‐coded. Peptides with P < 0.05 (BH adjusted) are marked in grey.Click here for additional data file.


Although acute lymphoblastic leukemia (ALL) is most common in pediatric and adolescent and young adult (AYA) patients, 20% of cases are diagnosed in patients ≥ 55 years old. Use of intensive pediatric regimens in AYA populations has demonstrated excellent tolerability and significant improvements in event‐free survival (EFS) and overall survival (OS). The backbone of pediatric regimens includes asparaginase and corticosteroids, both of which are associated with more toxicity in older patients and those with body mass index (BMI) ≥ 30 kg/m which leads to poor tolerance of these regimens. We tested the safety and efficacy of a dose‐modified The Cancer and Leukemia Group B 10403 regimen using reduced doses of pegylated (PEG)‐asparaginase (ASP) and corticosteroids (RD‐10403) in 30 patients with Philadelphia‐chromosome negative ALL who were ≥50‐year‐old and younger adults with significant metabolic or hepatic co‐morbidities. The complete remission rate on day 28 was 77%, 3‐year EFS was 54%, and estimated 3‐year OS was 55%. Grade 3+ toxicity was noted in 40% of patients during induction, and induction‐related mortality was 3%. Additional prospective evaluation of RD‐10403 is merited to determine efficacy and safety of this regimen and to serve as a framework for chemoimmunotherapy combination therapy. The bacDue to the treatment‐related AEs associated with intensive pediatric regimens, it has been difficult to establish a standard of care approach in adults ≥ 40 years old with newly‐diagnosed ALL . Low intGiven our interest in exploring these issues, we tested the safety and efficacy of a modified CALGB 10403 regimen using reduced dosages of PEG‐ASP and corticosteroids (RD‐10403) in patients ≥ 50 years old and younger adults with significant metabolic or hepatic co‐morbidities. We had previously demonstrated that adequate asparaginase activity levels with less toxicity can be achieved with reduced PEG‐ASP dosing . Here, w22 of PEG‐ASP along with dexamethasone 10 mg/m2 on day 1–7 and 15–21 during induction . In patients with metabolic syndromes  steroids were further reduced to administration on day 1–7 alone. Patients with CD20 positivity in ≥20% of lymphoblasts received rituximab during Course I, II, and III of therapy. Treatment continued for 2 years from the beginning of interim maintenance for women and for 3 years from the beginning of interim maintenance for men. CR was conventionally defined as the presence of ≤5% blasts in the bone marrow biopsy specimen and recovery of peripheral blood counts. Measurable residual disease (MRD) was assessed by multicolor flow cytometry on bone marrow aspirate specimens obtained at day 28 of therapy with a sensitivity of 10−4. High‐risk disease biology was defined as patients who had Philadelphia‐chromosome‐like (Ph‐like) ALL or an MLL rearrangement identified on fluorescence in‐situ hybridization or cytogenetics, TP53 mutation detected on next‐generation sequencing assay, and/or an early T‐cell precursor ALL phenotype. Survival curves (EFS and OS) were constructed using the Kaplan‐Meier method [We performed a single‐center retrospective analysis of adult patients with Ph‐ ALL who were treated per RD‐10403 between August 2014 and April 2019. RD‐10403 was adopted for use at our institution starting in August 2014. April 2020 was selected as the time point for data lock to allow for at least 1 year of follow‐up. IRB approval was obtained for this study. Patients were identified by review of electronic pharmacy records, and clinical data were abstracted by manual chart review. Patients were included if they had received 250, 500, or 1000 IU/mn Tables  and 1B. 33.12, and 83% of patients achieved therapeutic asparaginase levels at day 11 of induction (≥0.1 IU/ml). Thirteen patients received 1000 IU/m2, 12 patients received 500 IU/m2, and four patients received 250 IU/m2. One patient had PEG‐ASP held during induction due to drug‐induced hepatotoxicity from home medications. Of the four additional patients that did not achieve therapeutic PEG‐ASP levels at day 11, three received 500 IU/m2, and one received 250 IU/m2. No patients were given a second dose of PEG‐ASP during induction. The median total dexamethasone dose during induction was 140 mg/m2; 22 patients received 10 mg/m2 on day 1–7 and 15–21 of induction, seven received 10 mg/m2 on day 1–7 of induction, and one received 10 mg/m2 on day 1–7 and 15–18 of induction.Thirty consecutive patients with Ph‐ B‐ALL or T‐ALL that were treated with RD‐10403 from August 2014 to April 2019 were identified. Patient characteristics are outlined in Table 3.2n = 11), and nine patients achieved MRD negativity. At time of data lock, six patients were still being treated on the regimen, five had completed maintenance therapy per RD‐10403, five had discontinued due to adverse events (AEs) attributable to RD‐10403, and two had discontinued due to AEs unrelated to RD 10403 . Three patients underwent allogeneic hematopoietic stem cell transplantation  in first CR . Nine patients (30%) had discontinued RD‐10403 due to relapsed/refractory disease. For these nine, a median of one salvage therapy was utilized (range 1–4), and five patients subsequently underwent allo‐HCT in a second CR or later. For the entire cohort, the estimated 3‐year EFS was 54% , and estimated 3‐year OS was 55%   nor the age at time of induction  were significantly different.At least one Grade 3+ non‐hematologic AE was seen in 40% of patients during induction . Regarding the four patients with thrombosis, all four patients developed upper extremity deep vein thrombosis (DVT). One patient had proximal DVTs in both lower extremities as well. All patients received therapeutic anticoagulation for a minimum of 6 months with interruptions of anticoagulation when platelet count was ≤50000/μl. There was one Grade 5 death due to septic shock (Table p = 0.013). Two additional treatment‐related deaths occurred beyond induction therapy (one due to septic shock and one due to asparaginase‐induced hepatic failure), for an overall treatment‐related mortality (TRM) of 10%. Of the two additional patients that discontinued RD‐10403 due to attributable AEs, one had developed persistent Grade 1 neuropathy, and the other was diagnosed with methotrexate‐associated cirrhotic liver disease.The median asparaginase level for the entire cohort was 0.14 IU/ml on day 11 . The median day 11 asparaginase level was significantly higher in patients who developed Grade 3+ AE  when compared to those without Grade 3+ AE  , alanine transaminase elevation (29%), febrile neutropenia (24%), hyperbilirubinemia (19%), aspartate transaminase elevation (13%), and thrombosis (5%) with a TRM of 2% during induction. In comparison, 40% percent of our RD‐10403 patients had at least one Grade 3+ AE during induction with TRM of 3%. Nine of the 12 patients with Grade 3 of 4 AEs were able to receive additional PEG‐ASP during post‐remission therapy. Overall TRM attributable to RD‐10403 was 10%, and two (6%) patients were not continued on the regimen due to toxicity. We did not find a significant difference in BMI or age between patients who had Grade 3+ AEs and those who did not. However, median day 11 asparaginase level was significantly higher in those with Grade 3+ AEs. Previous work by Derman et al and by others has demonstrated lower rates of Grade 3+ AEs in patients receiving a reduced dose of asparaginase in comparison to a standard dose, suggesting that dose reduction may be critical in allowing for safe administration of this regimen to older patients , 20, 21.It is also important to consider that the entire traditional therapeutic approach for treatment of ALL, particularly for older adults, is undergoing re‐evaluation in new frontline trials and perhaps heralds a new era that introduces new agents in the frontline and minimizes exposure to the traditional chemotherapeutics that have been the backbone of the pediatric regimens. The FDA approvals of inotuzumab ozogamicin (InO) in relapsed or refractory (R/R) ALL and blinatumomab in R/R ALL and in MRD+ ALL have given clinicians targeted therapies with remarkable efficacy and tolerability , 24, 25.The feasibility of regimens similar to RD‐10403 may be of particular relevance for the many regions of the world where access to new antibody therapies remains very limited and cost‐prohibitive. In addition, the current treatment paradigm for T‐ALL still lacks targeted therapies, although some new agents are being actively investigated in the R/R setting . TherefoAnand Ashwin Patel designed the research study, analyzed data, and wrote the paper. Joseph Heng, Emily Dworkin, and Sarah Monick analyzed the data, helped to draft the paper, and provided critical revisions. Adam S. DuVall, Sandeep Gurbuxani, Satyajit Kosuri, Benjamin A. Derman, Hongtao Liu, Michael Thirman, Lucy A. Godley, Olatoyosi Odenike, and Richard A. Larson helped to draft the paper and provided critical revisions. Wendy Stock designed the research study, wrote the paper, and provided critical revisions.Anand Ashwin Patel, Sarah Monick, Adam S. DuVall, Sandeep Gurbuxani, and Satyajit Kosuri have no conflict of interest. Joseph Heng is honoraria from OncLive, while Emily Dworkin is honoraria from Abbvie. Benjamin A. Derman is in advisory board from Sanofi. Hongtao Liu did research funding from BMS and Karyopharm; is honoraria from Agios. Michael Thirman did research funding from Gilead Sciences, Pharmacyclics, Janssen, AbbVie, Merck, Syndax, TG Therapeutics, Tolero; is in advisory board from AstraZeneca, Celgene, Roche/Genentech, Pharmacyclics, Janssen, Abbvie. Lucy A. Godley is advisory board from Invitae, Inc; royalties from UpToDate. Olatoyosi Odenike did research funding from AstraZeneca, ABBVIE, astex, agios, incyte, janssen, NS‐Pharma, Oncotherapy Sciences, BMS; is honoraria/has ad board membership‐ ABBVIE, BMS, Celgene, Novartis, Taiho, PRA. Richard A. Larson has acted as a consultant or advisor to Amgen, Ariad/Takeda, Celgene/Bristol Myers Squibb, CVS/Caremark, Epizyme, MorphoSys, and Novartis, and has received clinical research support to his institution from Astellas, Celgene, Cellectis, Daiichi Sankyo, Forty Seven/Gilead, Novartis, Rafael Pharmaceuticals, and royalties from UpToDate. Wendy Stock is Honoraria from Abbvie, Jazz, Kite, Morphosys, Pfizer, Servier.


Transcriptome analysis of five MSI‐related genes  and five CRC‐related genes  showed that CDX2 expression was most severely decreased in SSA/P. Immunohistochemical staining confirmed that CDX2 protein was reduced compared with the surrounding mucosa. Direct sequencing of the BRAF gene showed that the BRAF V600E mutation was detected in only nine of 36 cases. In a mouse model, BRAF, APC, or CDX2 deficiency indicated that the gene expression pattern with loss of CDX2 is more similar to our SSA/Ps compared with those induced by BRAF or APC mutation. Transcriptome analysis of SSA/Ps showed characteristic gene expression with a strong resemblance to MSI‐H CRC. Downregulation of CDX2 expression is an essential molecular mechanism involved in the initial stage of SSA/P tumorigenesis. (UMIN000027365).The objective of this study was to elucidate the molecular background of sessile serrated adenoma/polyp (SSA/P) endoscopically resected with comprehensive gene expression analysis. Gene expression profiling was performed for 10 tumor‐normal pairs of SSA/P. Cluster analysis, gene set enrichment analysis (GSEA), and consensus molecular subtype (CMS) classification of colorectal cancer (CRC) were applied to our transcriptome analysis. Unsupervised cluster analysis showed that the gene expression profile of SSA/Ps is different from that of adjacent normal epithelial cells, even in the very early stage of tumorigenesis. According to the CMS classification, our microarray data indicated that SSA/Ps were classified as CMS1. GSEA demonstrated a strong association between SSA/P and microsatellite instability‐high (MSI‐H) CRC ( SSA/Ps showed characteristic gene expression with a strong resemblance to microsatellite instability‐high colorectal cancer. And the downregulation of CDX2 expression is an essential molecular mechanism involved in the initial stage of SSA/P tumorigenesis. Some SSA/Ps then acquire microsatellite instability (MSI) through MLH1 methylation, leading to MSI‐high (MSI‐H) cancer, while others lead to microsatellite stable (MSS) cancer.Recently, SSA/Ps have been attracting attention and are considered precursor lesions of CRC via the serrated pathway. SSA/Ps were hypothesized to have a high However, the prevalence of SSA/Ps might be lower than that in tubular adenomas.Consensus molecular subtypes (CMS) have recently gained attention.In this context, we investigated the molecular biological background of SSA/Ps through a bioinformatic analysis of comprehensive gene expression and performed CMS classification of SSA/Ps using the obtained gene expression profiles. Furthermore, based on transcriptome analysis, we investigated the molecular mechanism of the very early stages of SSA/P tumorigenesis.22.1This study was a prospective, single‐center study. Patients with SSA/P who underwent endoscopic resection at the University of Tokyo Hospital between June 2017 and September 2018, were enrolled. All patients were endoscopically or pathologically diagnosed with SSA/P before enrollment. The following patients were excluded: a past medical history of lower gastrointestinal surgery, comorbid malignant disease, familial polyposis, inflammatory bowel disease, ethical considerations, and not being diagnosed with SSA/P pathologically. Written informed consent was obtained from all the patients. Formalin‐fixed paraffin‐embedded samples of 39 endoscopically resected SSA/Ps at our institute were also collected retrospectively for histochemical analysis.This study was approved by the Research Ethics Committee of the Graduate School of Medicine and Faculty of the University of Tokyo and registered in the University Hospital Medical Network Clinical Trial Registry (UMIN000027365).2.2Specimens were obtained from the tumor and paired with the surrounding mucosa through endoscopic biopsy immediately before resection of the target lesions using endoscopic biopsy forceps . The samples were immediately placed in Eppendorf tubes with RNAlater  and stored at room temperature for several hours before storing at −80°C. The SSA/Ps were endoscopically resected after biopsy and pathologically evaluated after formalin fixation. The resected tissues were re‐evaluated using endoscope photographs and pathological specimens.2.3Specimens were homogenized using a Power Masher (Nippi Inc.) with BioMasher II (Nippi Inc.) in QIAzol Lysis Reagent (Qiagen). Total RNA was extracted using the miRNeasy Mini Kit (Qiagen). Quantity and purity  of the extracted RNA were measured using a NanoDrop1000 spectrometer (NanoDrop Technologies). Quality check of extracted RNA was performed by measuring RNA Integrity Number and the 28S/18S rRNA ratio using an Agilent 2100 BioAnalyzer (Agilent Technologies).2.4Oligonucleotide microarray  was performed using 10 SSA/P‐normal pairs, followed by fluorescence assessment using a microarray scanner D . Raw data were logged (base2) and quantile normalization was performed using the Gene Spring software (Agilent Technologies). Raw data are registered in NCBI's Gene Expression Omnibus and are accessible through GEO Series accession number GSE198692.2.5http://rana.lbl.gov/EisenSoftware.htm). The results were displayed using TreeView software (http://rana.lbl.gov/EisenSoftware.htm).Average linkage hierarchical clustering of both genes and cases was performed using median centering and normalization with Cluster 3.0 (2.6https://github.com/Sage‐Bionetworks/CMSclassifier)https://github.com/Lothelab/CMScaller).Classification of gene expression profiles of SSA/Ps into the four CMSs of CRC was performed using pre‐validated multiplatform analysis packages: CMS classifier  according to the manufacturer's instructions. BRAF exon 15 was amplified by PCR using the forward primer sequence 5’‐TCATAATGCTTGCTCTGATAGGA‐3′ and the reverse primer sequence 5’‐GGCCAAAAATTTAATCAGTGGA‐3′ to yield an amplicon size of 224 bp. The PCR mix contained 1x PCR Buffer for KOD FX Neo, 0.4 mM dNTPs, 0.3 μM primers, 0.5 U KOD FX Neo , and 1 μl DNA template in a total reaction volume of 25 μl. The PCR cycling conditions were as follows: 94°C for 2 min, 45 cycles of denaturation at 98°C for 10 s, annealing at 60 °C for 30 s, and extension at 68 °C for 30 s with a final extension at 68°C for 7 min. PCR products were loaded on an agarose gel, and the band corresponding to the BRAF exon‐15 fragment was excised from the gel and purified using a QIAGEN QIAquick gel extraction kit . PCR products (20 ng) were used as templates for sequencing. Sequences were outsourced, and the products were analyzed by Fasmac Japan .2.8cosmobio.co.jp) at a 1:200 dilution was applied for 60 min at room temperature. Sections were then incubated with the secondary amino acid polymer reagent Histofine Simple Stain MAX PO  for 30 min at room temperature. The reaction products were visualized by incubating the sections in a 20 mg/dL 3,3′‐diaminobenzidine tetrahydrochloride solution containing 0.006% H2O2 for 5 min. The immunostained sections were evaluated and scored by two expert pathologists.To examine the expression of CDX2 proteins, immunohistochemical staining was performed on 39 SSAP samples, three melanoma samples, and three advanced CRC samples. Two micrometer thick sections of formalin‐fixed embedded samples were deparaffinized. Antigen activation treatment was performed at 95°C for 20 min using citrate buffer . The sections were washed with running water and immersed in TBS. Primary immunostaining with CDX2 . The gene expression profiles obtained from mice were as follows: a) CDX2 null mutant colon epithelium, b) BRAF V600E mutant colon epithelium, c) CDX2 null / BRAF V600E mutant colon epithelium, and d) APC mutant colon epithelium, and normal colon epithelium. GSE84650 uses GPL17400 as the platform; therefore, the HUGO Gene Nomenclature Committee (https://www.genenames.org/) was used to convert the mouse gene symbol into a human gene symbol. Using the gene expression profile converted to the human gene symbol, each mutant colon epithelium was compared with the normal colon mucosa.The gene expression profile of our SSA/Ps was compared with the gene expression profile of the mucosa of the colon of mice obtained from GSE84650 of the GEO seriesEach gene set, such as (a) [Ohki mouse CDX2‐], (b) [Ohki mouse BRAF‐], (c) [Ohki mouse CDX2‐/BRAF‐], and (d) [Ohki mouse APC‐], was made by genes that were elevated compared with the normal colon. Four gene sets were included in the pre‐validated curated C2 gene set database, GSEA was performed using the gene expression profile of SSA/P obtained from the present microarray.GSEA was then performed to analyze genes with differences in expression between tumor and paired surrounding mucosa and to characterize SSA/P by comparing the obtained gene sets to known disease‐related gene sets, especially the pre‐validated curated C2 gene set database. The [OHKI SSAP UP] gene set comprised 100 genes that were most prominently upregulated in SSA/P compared with the surrounding normal mucosa. The [OHKI SSAP DOWN] gene set was made of 100 genes that most prominently downregulated gene transcripts in SSA/P compared with the surrounding normal mucosa. Two gene sets were included in the pre‐validated curated C2 gene set database, and cross‐reference gene enrichment analysis between SSA/P, adenoma, and MSI‐H CRC was performed.2.10http://david.ncifcrf.gov/home.jsp).Biological pathway analysis was performed to determine functional gene ontology terms specific to tumors and paired surrounding mucosa using DAVID Bioinformatics Resources 6.7  are shown in Tables We then identified the gene probes satisfying the criterion of mean + 3 standard deviations (SD) and performed an unsupervised cluster analysis. A total of 694 gene probes were satisfied mean + 3SD from 58,201 total probes. We created a cluster tree with these identified 694 gene probes and found that the tumor and normal mucosa were separated clearly Figure . These d3.3CMS classification was performed using comprehensive gene expression profiles of 10 SSA/Ps using the CMS Classifier and CMS caller. The CMS classifier showed that 70% (7/10) of SSA/Ps were classified as CMS1 Figure . The CMS3.4MSH2, MSH6, MLH1, PMS1, and PMS2, using the gene expression profiles of our SSA/Ps. We also focused on BRAF, KRAS, APC, TP53, and CDX2, which are established cancer‐related genes important for colorectal tumorigenesis.Based on the results of CMS classification, we focused on the genes associated with MSI, such as MSH2 0.96, MSH6 0.95, MLH1 1.06, PMS1 0.97, PMS2 0.78). On the contrary, many cancer‐related genes tended to show decreased expression in tumor tissues . Although mutation is a well‐known mechanism of oncogenesis for BRAF, KRAS, APC, and TP53, our data showed that transcription was slightly decreased for BRAF, KRAS, and APC . The expression level of CDX2 was considerably lower in the tumor tissue than in the normal tissue in all 10 cases.Figure 3.5BRAF gene since mutations in BRAF  have been most frequently reported in SSA/P.Next, we analyzed the sequence of the 3.6CDX2 expression was severely decreased in tumor tissues compared with that in normal tissues . To confirm these results in silico, we compared them with mRNA transcription data of animal models deficient in BRAF, APC, or CDX2 (GSE84650).p < 10−5), [Ohki mouse CDX2‐/BRAF‐] , [Ohki mouse BRAF‐] , and [Ohki mouse APC‐]   included in the [Ohki mouse CDX2‐] gene set were found in the top 100 genes  Figure . These r00 genes  that wer3.8p < 0.05), whereas 12 gene sets were downregulated in SSA/Ps (p < 0.05). The top 10 gene sets upregulated in SSA/Ps are shown in Figure p = 0.004). In this gene set, 39.1% (9/23) of genes were four times higher in SSA/Ps than in the surrounding normal mucosa. [SABATES_COLORECTAL_ADENOMA] was the gene set from the colorectal adenoma reported by Sabates et al., which consists of genes upregulated in colorectal adenoma compared with surrounding normal mucosa .p < 10−5).GSEA to classify the gene expression of SSA/Ps using the pre‐verified C2 curated gene set database showed that 265 gene sets were significantly upregulated in SSA/Ps . The functional classifications upregulated in tumors are shown in 4In this study, we performed comprehensive gene expression analysis by microarray using the very early stages of SSA/P tumors. Some reports have described the transcriptome analysis of SSA/Ps in Western countries.CMS classification by CMS ClassifierMSH2, MSH6, MLH1, PMS1, and PMS2) or CRC .BRAF and APC, were mildly decreased, but direct Sanger sequencing of the BRAF gene showed a mutation rate (BRAF V600E) of 25%, which was less than that previously reported.CDX2 showed the lowest expression ratio in tumor tissues compared with normal tissues, which was verified by immunohistochemical staining.This is the first study from East Asia, where the prevalence and character of gastrointestinal disease were quite different from Western countries. It has been reported that when MLH1 deletion is added to SSA/P, it acquires heteromorphism and progresses to MSH‐H CRC.CDX2 were more similar to those of our SSA/Ps, compared with those induced by BRAF or APC mutations. Some reports also showed decreased expression of CDX2 in SSA/P,CDX2 correlates with BRAF V600E mutation and the serrated pathway.CDX2 is a well‐known master gene essential for intestinal development, differentiation, and maintenance of function.CDX2 plays an important role in the very early stages of SSA/P tumorigenesis.Furthermore, GSEA using animal models (GSE84650) showed that gene expression patterns induced by loss of GSEA also showed that SSA/P has a gene expression profile with a strong correlation to MSI‐H CRC and tubular adenoma. Previously, it was thought that SSA/Ps might have different characteristics from tubular adenomas, but our results suggest that SSA/Ps and tubular adenomas might have similar gene expression profiles. On the contrary, cross‐reference analysis showed that SSA/Ps were correlated with MSI‐H CRCs, but tubular adenomas were not correlated with MSI‐H CRCs.We acknowledge that there are several limitations to our study. First, the subjects of comprehensive gene expression in this study were only SSA/Ps. In the serrated pathway, microvesicular HPs (MVHPs) are thought to be precursor lesions of SSA/Ps, and SSA/Ps acquire MSI accumulation of DNA methylation leading to MSI‐H CRCs via SSA/P with cytological dysplasia. If comprehensive gene expression analysis of each MVHP, SSA/Ps with cytological dysplasia, and MSI‐H cancers can be performed, it might be possible to obtain results approaching the mechanism of oncogenesis by comparing with the results of SSA/Ps in this study. However, the prevalence of SSA/Ps with cytological dysplasia is very low, and detection of SSA/Ps with cytological dysplasia is difficult. Furthermore, the dysplastic area of SSA/Ps with cytological dysplasia did not occupy the entire lesion, and it is difficult to correctly obtain endoscopic biopsy specimens from dysplastic areas based on endoscopic findings. We should compare SSA/Ps, SSA/Ps with cytological dysplasia, and MSI‐H CRCs and confirm whether SSA/Ps progress to MSI‐H CRCs. Second, the cases of SSA/Ps in which we performed comprehensive gene analysis were scarce. Third, we use the name “SSA/P" in this study. In 2019, the revision of the WHO classification changed the name of SSA/P to SSL. Strictly speaking, these two are not identical, but we think our results from SSA/P can mostly apply to understanding SSL based on the similarity of SSA/P and SSL. In fact, the name “SSA/P” is still widely used in the world. Fourth, we believe that it is necessary to investigate the Beta‐catenin localization and ERK‐phosphorylation in order to evaluate the functional effects of the changes in APC and BRAF transcript levels. We would like to make this an issue for future study.In conclusion, our study demonstrates that the gene expression profiles of SSA/Ps are strongly correlated with those of MSI‐H CRCs and that downregulation of CDX2 expression is essential for the first step in the tumorigenesis of SSA/P.Conception and design: Daisuke Ohki, Nobutake Yamamichi, Shuta Tomida. Development of methodology: Daisuke Ohki, Nobutake Yamamichi, Yoshiki Sakaguchi, Yu Takahashi, Natsuko Kageyama‐Yahara, Mitsue Yamamichi, Chihiro Takeuchi. Data analysis and interpretation: Daisuke Ohki, Nobutake Yamamichi, Yoshiki Sakaguchi, Shuta Tomida, Natsuko Kageyama‐Yahara, Mitsue Yamamichi, Yasuhiro Sakai, Kouhei Sakurai. Writing, review, and/or revision of the manuscript: Daisuke Ohki, Nobutake Yamamichi, Yoshiki Sakaguchi, Shuta Tomida, Chihiro Takeuchi, Natsuko Kageyama‐Yahara, Mitsue Yamamichi, Yasuhiro Sakai, Kouhei Sakurai, Yosuke Tsuji, Kazuhiko Koike and Mitsuhiro Fujishiro.All authors have no conflict of interest.This study was approved by the Research Ethics Committee of the Graduate School of Medicine and Faculty of the University of Tokyo (review number: 11537‐(1)).This study was registered in the University Hospital Medical Network Clinical Trial Registry (UMIN000027365).Written informed consent was obtained from all the patients.Tables S1‐S7Click here for additional data file.