Among multiple subtypes of tissue or cell, subtype-specific differentially-expressed genes (SDEGs) are defined as being most-upregulated in only one subtype but not in any other. Detecting SDEGs plays a critical role in the molecular characterization and deconvolution of multicellular complex tissues. Classic differential analysis assumes a null hypothesis whose test statistic is not subtype-specific, thus can produce a high false positive rate and/or lower detection power. Here we first introduce a One-Versus-Everyone Fold Change (OVE-FC) test for detecting SDEGs. We then propose a scaled test statistic (OVE-sFC) for assessing the statistical significance of SDEGs that applies a mixture null distribution model and a tailored permutation test. The OVE-FC/sFC test was validated on both type 1 error rate and detection power using extensive simulation data sets generated from real gene expression profiles of purified subtype samples. The OVE-FC/sFC test was then applied to two benchmark gene expression data sets of purified subtype samples and detected many known or previously unknown SDEGs. Subsequent supervised deconvolution results on synthesized bulk expression data, obtained using the SDEGs detected from the independent purified expression data by the OVE-FC/sFC test, showed superior performance in deconvolution accuracy when compared with popular peer methods. An important but frequently underappreciated issue is how best to define a cell or tissue subtype-specific expression pattern. Ideally, a subtype-specific expression pattern would be composed of individual features that are most-upregulated in the cell or tissue subtype of interest while in no others 8.Molecular characterization often applies gene expression profiling to a complex biologic system that includes some molecular features that are expressed by all cell or tissue types in the system (such as housekeeping genes)9, the expression patterns of detected SDEGs could serve as the supervising information. However, detecting SDEGs using molecular expression profiles of purified/isolated tissue or cell subtypes remains a challenging task10. For example, the most frequently used methods rely on the extension of an ANOVA model where the null hypothesis states that samples in all subtypes are drawn from the same population. Consequently, ANOVA detects genes differentially expressed across any of the subtypes and can identify many false positive SDEGs (subtype-nonspecific classic DEGs) that may not conform to the SDEG definition (Supplementary Information). One-Versus-Rest Fold Change (OVR-FC) is another popular method based on the ratio of the average expression in a particular subtype to that of the average expression in all other samples (rest)12, and OVR t-test is occasionally used to assess the statistical significance of the detected genes13. However, a gene with a low average expression value in the rest is not necessarily expressed at a low level in every subtype in the rest. Expectedly, simulation studies show that Marker Gene Finder in Microarray data (MGFM) outperforms OVR t-test14. Alternative strategies include One-Versus-One (OVO) t-test and Multiple Comparisons with the Best (MCB)15 that use additional pairwise significance testing or the confidence intervals of OVO statistics16.SDEGs play a critical role in molecularly characterizing and identifying tissue or cell subtypes. For example, to support supervised deconvolution of complex tissues6. To assess the statistical significance of such a test, we propose a scaled test statistic (OVE-sFC) together with a mixture null distribution model. Because the expression patterns of non-SDEGs can be highly complex, a tailored permutation test is used to estimate the corresponding distribution under the null hypothesis.To address the critical problem of the absence of a detection method explicitly matched to the definition of SDEGs, here we introduce One-Versus-Everyone Fold Change (OVE-FC) test to detect SDEGs among many subtypes. Previously, the OVE-FC test was proposed as a means to detect SDEGs and improve multiclass classification, where the selection is based on whether the mean of one subtype is significantly higher or lower than the mean from each of the other subtypesj is expressed at the highest and second highest levels, respectively14,14, and matches well the definition of SDEGs18. Conceptually, the null hypothesis for non-SDEGs, and the alternative hypothesis for SDEGs, can be described as  method for fully unsupervised deconvolution19 (marker genes that reside near the vertices of the scatter simplex). To assess the statistical significance of OVE-FC tests and to leverage the information across subtypes or genes, we assume that Consider the measured expression level mentclass2pt{minimpes see “” sectionWe first validate the performance of OVE-sFC test on extensive simulation data, in terms of type 1 error rate and False Discovery Rate (FDR) control. We then demonstrate the detection power of OVE-FC/sFC in a comprehensive set of scenarios and in comparison with top peer methods using the partial area under the receiver operating characteristic curve (pAUC) as the performance measure. We show the utility of OVE-FC/sFC using benchmark public data, and then assess performance both by comparing with known SDEGs and by the accuracy of supervised deconvolution that uses the expression patterns of de novo SDEGs detected by OVE-FC/sFC.This work aims solely to detect SDEGs among multiple subtypes of interest, no bulk experiment or dataset is involved. All tests use the molecular expression data derived from purified/isolated subtypes, where the subtype can be a tissue subtype, cell subtype, or biological process. The supervised deconvolution case study provides one application that uses SDEGs detected as explicitly defined. The main objective of the proposed OVE test is to reduce the high false positive rates of existing methods while ensuring high sensitivity, particularly when involving a large number of multiple tests.p values. If the type 1 error is either too conservative or too liberal, the p value is inflated by either too many false positive or false negative estimates, the test loses its intended meaning, and the data become difficult to interpret correctly.To test whether our OVE-sFC test can detect SDEGs at appropriate significance levels, we assessed the type 1 error using simulation studies under the null hypothesis “” section8). Using the simulation data sets with various parameter settings, we show that in all scenarios the empirical type 1 error produced by OVE-sFC test closely approximates the expected type 1 error , we simulated a comprehensive set of scenarios to compare the power of OVE-sFC and peer methods to detect SDEGs. Simulation data are again generated by modifying the expression levels of real gene expression data, where a portion of the genes are designated as SDEGs that are upregulated specifically in one of the participating subtypes, with fold change drawn in certain ranges. To recapitulate the characteristics of real expression data, we used parameter values that are close to that estimated from real data, such as proportions of various non-SDEG expression patterns. To retain the mean–variance trend in RNAseq data, we sampled variance directly from the real RNAseq data 21.False Discovery Rate (FDR) control is an important issue when assessing detection power in large-scale multiple testing. For a well-designed significance test, the objective is to maximize power while maintaining the FDR below an acceptable level. To test whether the q-value reflects the actual FDR, ‘fdrtool’ was used to estimate the q-value for each geneExperimental results show that both overall and subtype-specific OVE-sFC tests achieve a well-controlled FDR that matches the q-value cutoff Figure , S6. In 17, Fig. For pAUC, the OVE strategy in OVE-FC/sFC achieved the highest power in detecting SDEGs Figs. –S3, as dWhile the OVE test aims to reduce high false positive rates produced by the existing methods, it shall also ensure high detection power (sensitivity). While the percentage of ideal SDEGs is expected to be small when compared with that of non-SDEGs, a high TPR is required to ensure sufficient accuracy of a supervised deconvolution and subtype enrichment analysis (two major utilities of SDEGs). The experimental results shown that, with the desired > 0.9 sensitivity as seen in Fig. When the sample size is small, the OVE-sFC test statistic leverages information across genes by estimating a priori variance via the limma method. This approach stabilizes the variance estimate for each gene. Furthermore, the OVE-sFC test statistic estimates the parameters of the limma model from all subtypes, producing better results than by applying a t-test independently with the limma model for each subtype pair. For small sample size cases, our results show that OVE-sFC clearly outperforms OVO t-test Figs. , S3. Not22. The constituent subtypes are composed of seven different human immune cells that were isolated from healthy human blood: B cells, CD4 + T cells, CD8 + T cells, NK cells, monocytes, neutrophils, and eosinophils. Because Roche and HUG used the same protocols for cell isolation and sample processing from two independent panels of donors, the derived gene expression profiles allow the use of a cross-validation strategy.To detect SDEGs associated with human immune cells, we applied the OVE-sFC test to two gene expression microarray data sets acquired from isolated/purified subtypes, GSE28490 (Roche) and GSE28491 (HUG)23. We also applied a Bonferroni multiple testing correction and a more stringent p value < 0.001; the number of SDEGs account for 10.7% and 2.7% of all probesets in the Roche and HUG data sets, respectively  score calculated from ideal SDEGs-guided supervised deconvolution to quantify the proportional abundance of each subtype (Supplementary Information). The correlation coefficient between the estimated scores and the true proportions was used to assess the accuracy of several SDEGs selection methods.Accurate and reliable detection of ideal SDEGs has a significant impact on the performance of many supervised deconvolution methods that use the expression patterns of ideal SDEGs to score constituent subtypes in heterogeneous samplesBoth OVE-FC and OVE-sFC were applied to three independent data sets acquired from the purified subtype expression profiles (GSE28490 Roche), purified subtype RNAseq profiles (GSE60424), and classified single-cell RNAseq profiles (GSE72056), respectively. Ideal SDEGs were detected by six different methods including OVE-FC, OVE-sFC, OVR-FC, OVR t-stat, OVR t-test, and OVO t-test, and then used to supervise the deconvolution of realistically synthesized mixtures with ground truth.The proportions of constituent subtypes were estimated by the CAM scores derived from expression levels of top-ranked SDEGs for each subtype. Supervised deconvolution results show that OVE-sFC, OVE-FC and OVO t-test achieved the highest correlation coefficients between the CAM score and the true proportions when compared with other methods Figs. a, S10.FiTo create a more biologically realistic case involving higher between-sample variations, we synthesized a set of n = 50 in silico mixtures by combining the subtype expression profiles from bootstrapped samples in the RNAseq data set according to pre-determined proportions. Again, supervised deconvolution results show that the ideal SDEGs detected by OVE-FC or OVE-sFC or OVO t-test achieved superior deconvolution performance Figs. b, S11.Using the more challenging case of RNAseq data , we repeated the simulations where in silico mixtures were synthesized by combining subtype mean expressions (GSE28491 HUG); ideal SDEGs were detected from the downsampled RNAseq profiles in GSE60424 (n = 3). Three purified samples were randomly selected for each subtype and analyzed by the six methods. In terms of ideal SDEG-guided deconvolution, OVE-sFC strongly outperforms OVO t-test. OVE-sFC also outperforms OVE-FC for phenotypically closer cell types (CD4 + T and CD8 + T cell types)  selected, Fig. on Table , is a go18, motivated by the need to obtain such SDEGs to supervise in silico tissue deconvolution19 and/or tissue subtype characterization9. This is a particulary important goal where the measured data are mixtures of the genes expressed by many of the subtypes present in the samples and the SDEGs are used to estimate both the proportions of each subtype in individual heterogeneous samples and the averaged subtype-specific expression profiles.Interpreting an expression profile of complex tissues requires knowledge of both the relative abundance of the different cell or tissue subtypes and their unique molecular characteristics. Understanding the relative contribution of individual cell or tissue subtypes in complex samples can illuminate pathophysiologic mechanisms, biologic responses to various stimuli, or transitions in phenotype—especially when cell–cell and cell–matrix interactions in a complex system are necessary conditions for appropriate cell or tissue function. The SDEG expression patterns of relevant cells or tissues can be used to support supervised deconvolution to estimate the relative prevalence of these cell or tissue subtypes. Our present work on SDEGs is restricted to the widely adopted SDEG definitionp values can accurately estimate both subtype proportions and expression profiles; thus, these SDEGs can serve as effective molecular markers , sample size, and differential expression (fold change) between two subtypes expressed at the highest levels. Our experimental results show that OVE-sFC test maintains type 1 error rates closely matched to the expectations with varied effects Figure , and tenp values of OVE-sFC is assumed. This assumption holds when all genes are non-SDEGs and the estimate of the null distribution is sufficiently accurate. OVE-sFC works best when all assumptions in the model are valid. For example, while the proposed permutation scheme does not require the data to be normally distributed under the null hypothesis, OVE-sFC assumes that samples are drawn from a distribution with the same ‘shape’ for different genes. This assumption ensures that the null distributions across genes can be combined with variance-based standardization. When data distributions deviate significantly from a common shape, limma-voom/vooma/voomaByGroup variance models can be used to accommodate unequal variances by appropriate observational-level weights26. When data distributions deviate significantly from normality, a permutation ANOVA can be used to estimate the null hypothesis components of the mixture distribution. Figure 27 and DESeq228 can be adopted when needed.In our study, most of the assumptions applied are widely accepted because they are close to reality. In the simulation study to validate the type 1 error rate produced by OVE-sFC under the null hypothesis, a uniform distribution of the empirical p values are estimated) while OVE-sFC provides a significance assessment and can improve FDR control. Secondly, OVE-sFC improves detection power in some of the more challenging experimental conditions. Detecting SDEGs with accurate p values is an attractive feature of OVE-sFC that can help restrain the FDR to its expected level. Indeed, our experimental results show that OVE-sFC test outperforms OVE-FC in the more challenging cases involving nonideal SDEGs .ANOVA has been the most commonly used method to test differences among the means of multiple subtypes, often in conjunction with a post-hoc Tukey HSD test to compare all possible pairs of means5. OVE-FC/sFC can detect down-regulated SDEGs by reversing the comparison rule5. There are alternative definitions of ‘informative genes’ for different analytical purposes, such as when the goal is sample classification. In our earlier work on multiclass classification6, we have shown that upregulated SDEGs selected by OVE-FC are sufficient to achieve multiclass classification and can often improve classifier performance over alternative informative gene subsets of the same size.In addition to the SDEGs discussed here (genes uniquely up-regulated in a specific subtype), the counterpart of subtype-specific down-regulated genes (genes uniquely down-regulated in a specific subtype) are also of biological interest30.In the present study, we have chosen to introduce a method focused on univariate analysis. Our method does not consider the network structure among the genes or gene sets. For the future work, we will explore the possibility of networked SDEG detection, laveraging the latest advances in gene set analysis approaches based on multivariate tests19 are required. An advantage of unsupervised deconvolution is that it can identify both the cell/tissue subtype proportions and their specific expression patterns, albeit with potentially less fidelity, when neither is known a priori or measured from the same sample.Lastly, when subtype-specific expression patterns are unknown, unsupervised deconvolution techniques such as CAMmth component of the mixture null hypothesis We propose the following mixture distribution of the OVE-sFC test statistic sis Fig. 4\documenThis mixture null distribution model is proposed to model unknown but potentially complex expression patterns of non-SDEGs under the null hypothesis. The permutation scheme(s) estimates such a mixture null distribution. The main advantage of the proposed permutation scheme(s) is its flexibility and comprehensiveness, which closely match the mixture null distribution of various types and combinations. With varying proportions of different non-SDEG types, the OVE-sFC test can maintain the type 1 error rate close to the expected level with the help of the proposed permutation scheme(s) and the conditional probability of each non-SDEG type .The null distribution of OVESEG-test statistics under p values of candidate SDEGs are estimated using the learned ‘mixture’ null distributionP is the number of permutations, J is the number of participating genes, p value associated with gene j is calculated by:p values when considering all subtypes together . In contrast, OVE-sFC exploits all subtypes in estimating the variances. The benefit of using all subtypes for modeling is significant in challenging cases with higher variance, smaller sample size, and more subtypes (Supplementary Information).The OVR-FC uses a simple test defined bym values, mimicking all types of non-SDEGs under the participating null hypotheses Among the 10,000 simulated genes, a portion are housekeeping genes that take the baseline expression levels across all subtypes under Among the 10,000 simulated genes, ratios of non-SDEG patterns were consistent with the estimation from the base real dataset; microarray data GSE28490 or RNAseq data GSE60424. 100 SDEGs were mimicked with their upregulations sampled from a fold change range , or . Variances were sampled from base real dataset according to gene expression levels, preserving the potential mean–variance trend (Supplementary Information).In these data sets, each cell subtype consists of at least five samples, excluding a few outliers Table . FollowiFive subtypes  were included in synthesizing n = 50 in silico mixtures, where purified subtype mean expression data from the GSE28491 HUG dataset were combined according to pre-determined proportions with additive noise, simulating heterogeneous biological samples (Supplementary Information).Supplementary Infomations.


The goal of this study was to assess the dose decision tool for the achievement of target exposure of busulfan in children undergoing hematopoietic cell transplantation (HCT).Population pharmacokinetic (PK) studies demonstrate model-based dosing for busulfan that incorporates body size and age improve clinical target attainment as compared to weight-based regimens. Recently, for clinical dosing of busulfan and TDM, our institution transitioned to a cloud-based clinical decision support tool  and non-compartmental analysis (NCA) estimation using the trapezoidal rule for estimation of AUC following TDM. Cohort B: Initial doses for busulfan were estimated by a first-generation PK model and NCA estimation of AUC following TDM. Cohort C: Initial doses were calculated by an updated, second-generation PK model available in the dose decision tool with an estimation of AUC following TDM.Patients (N = 188) were grouped into cohorts A, B, or C based on the method for initial dose calculation and estimation of AUC: The percent of individuals achieving the exposure target at the time of first PK collection was higher in subjects receiving initial doses provided by the model-informed precision dosing platform  versus subjects receiving initial doses based on either of the two other approaches . Similarly, the percent of subjects achieving the targeted cumulative busulfan exposure (cAUC) in cohort C was 100% vs. 66% and 88% for cohort A and B, respectively. For cAUC, the variability in the spread of target attainment (%CV) was low at 4.1% for cohort C as compared to cohort A (14.8%) and cohort B (17.1%).Achievement of goal exposure early on in treatment was improved with the updated model for busulfan and the Bayesian platform. Model-informed dosing and TDM utilizing a Bayesian-based platform provides a significant advantage over conventional guidelines for the achievement of goal cAUC exposure. Busulfan is a bifunctional alkylating agent commonly used in conditioning regimens prior to hematopoietic cell transplantation (HCT) for the treatment of a variety of childhood diseases, including both malignant and non-malignant disorders. Busulfan has a narrow therapeutic index with improved rates of engraftment and lower drug-related toxicity associated with a cumulative area under the curve (cAUC) of approximately 75–100 mg*h/L . Due to Historically, wide-spread clinical practice for busulfan dosing has followed the FDA-approved drug label, with an initial busulfan dose estimation based on actual body weight . This “cwww.insight-rx.com) for the routine clinical dosing of busulfan and TDM. This easy-to-use Bayesian-based platform helps clinicians individualize busulfan therapy at the point of care using an updated population PK model of busulfan. The primary goal of this study was to assess the performance of the model-informed precision platform for achieving the predefined patient-specific busulfan targeted exposure as compared to older conventional or first-generation model-based strategies.More recently, numerous PK studies have demonstrated population PK models where busulfan clearance (CL) parameter incorporates patient covariates such as body size and age provide improved clinical target attainment when compared to weight-based regimens alone . Here, wAll patients and/or guardians provided written informed consent to participate in the routine TDM of busulfan as part of their specific transplant protocol. Consent for participation in the PK analysis was waived as part of the University of California San Francisco Committee on Human Subjects' Research approval process. Eligibility criteria for busulfan PK analysis in this study included (1) subjects between 1 and 26 years of age at the time of HCT; (2) subjects met institutional and protocol specific eligibility criteria for allogeneic HCT that included intravenous busulfan therapy; and (3) patient-specific busulfan plasma time-concentration data were available for analysis. Patients underwent HCT for a wide variety of malignant and non-malignant pediatric disorders. Diagnosis is provided in Patient were grouped into cohorts A, B, or C based on the method used for initial dose calculation. Estimation of individual AUC and subsequent dose recommendation were as follows:Cohort A: Initial doses were determined based on the conventional dosing algorithm as outlined in the manufacturers' package insert and non-compartmental analysis (NCA) estimation using trapezoidal rule for estimation of AUC following TDM. Updated individualized doses for days 2–4 were calculated by scaling the previous dose with the ratio of obtained AUCobs and predefined AUCtarget using the equation and solving for new dose as follows: Dose administered in mg/AUCobs = new dose in mg/desired AUCtarget.Cohort B: Initial doses for busulfan were based on a first-generation PK model as previously described  for each patient was derived from the integration of the concentration over time, using the empirical Bayes estimates of individual CL over the entire treatment course as follows:th day of therapy was extrapolated using the individual PK parameter estimates determined from TDM performed with the first 3 days of treatment.Target attainment was defined as the achieved cAUC divided by the target cAUC for the patient, multiplied by 100%. This calculation was done retrospectively on the collected TDM data for all cohorts, also for those cohorts that were not using model-based dose individualization (A and B). Given time limitations required for bioanalytical assessment of plasma concentrations by mass spectrometry, PK assessments for the majority of subjects was performed on only the first 3 of 4 days of therapy. Only for a few patients sampling was performed on day 4 as well. Thus, for most patient's exposure on the 4obs to the predefined individual AUCtarget was calculated for both PK1 AUCobs/AUCtarget and the entire course of therapy defined by cAUCobs/cAUCtarget. One-way analysis of variance with post hoc Bonferroni adjustment for multiple comparisons was used to compare differences in PK1 among the cohorts. Results are expressed as median (range) and a p-value of <0.05 was considered to be statistically significant. Finally, the percentage of subjects achieving 80–120%, less than 80%, or greater than 120% of the predefined busulfan target at the time PK1 assessment were calculated and presented.To assess the performance of the model-informed precision dosing software as compared to other cohorts the ratio of individual AUCobs/AUCtarget and cAUCobs/cAUCtarget are shown in obs/AUCtarget for cohort C was closest to one at 0.93 (0.51–1.8), followed second by cohort B [0.85 (0.39–2.1)] and lastly cohort A [0.64 (0.38–1.10)]. A similar trend for the ratio closest to one was also shown with cohort C for cAUCobs/cAUCtarget when dose estimation was performed by the dose decision tool as compared to cohort A or B. The improvement shown in cohort C in achieving the predefined target exposure was statistically significant as compared to cohorts A and B  versus conventional guidelines or older PK model at 25% and 50% for cohort A and B, respectively. Similarly, the percent of subjects achieving the cAUCtarget was highest in cohort C (100%). For individuals with a busulfan cAUCobs outside the predefined therapeutic range, the PK1 exposure was more often sub-therapeutic. Subtherapeutic 1st dose PK assessments AUCobs (defined as % of subjects with <80% of the predefined 1st dose AUC target) occurred in 75% of patients in cohort A and 43% for cohort B, as compared to only 16% in cohort C.obs/cAUCtarget in pediatric HCT patients, as compared to conventional weight-based methods. This improvement in busulfan exposure increases our ability to achieve the predefined individual therapeutic window early on in the treatment course, which is expected to improve clinical outcomes. Our analysis also demonstrates the importance of continuous learning with improved therapeutic target attainment through a process that incorporates model evaluation and re-estimation of model parameters , achievement of target exposure early on in treatment, preferably with the first dose, is crucial. Most centers do not have the ability to measure busulfan levels through an “on site” clinical laboratory, limiting the ability to perform early dose modifications. As shown in this analysis, a clinical decision support platform that can enable model-informed precision dosing can generate initial doses for busulfan that improves the chance of achieving therapeutic targets with the first dose. Early target attainment directly leads to reduction in the number of PK assessments with additional doses, enhancing patient safety by minimizing blood loss and decreasing the need for repeated accessing of indwelling IV catheters. This is in comparison to traditional PK methodologies, such as non-compartmental analyses, which requires a substantial number of blood collections to accurately estimate PK parameters. In contrast, the model-informed precision dosing platform supports the use of more innovative blood collection strategies, such as D-optimality-based or sparse sampling, to limit blood collections. This enhances patient safety by reducing turn-around time for reporting PK results from external labs, allowing for dose modifications earlier in therapy and overall requiring fewer blood collections.Our institution began using (preliminary versions of) the model-informed precision dosing tool for busulfan approximately 5 years ago. This has allowed clinicians to quickly determine a patient-specific initial busulfan dose based on the child's age and weight. Clinicians also determine dose modifications based on TDM irrespective of the dosing interval or goal exposure. The implementation of this dosing platform has been very successful, and clinicians have found it easy to learn and use. One primary advantage of this particular platform was that, in addition to individualized dosing, the population PK model could be rapidly updated and refined as new data was entered into the system, further improving model accuracy and precision. Using this approach, the model estimates were updated to better describe busulfan exposure in both neonates and children undergoing HCT, resulting in a significantly improved fit (cohort C) as compared to the first-generation population PK model supported by the software (cohort B). The current analysis demonstrates the importance of continuous learning through external model validation and the re-estimation process of PK parameters  to improAlthough the implementation of the model-informed precision dosing platform significantly improved clinical target attainment for patients receiving busulfan, limitations remain. Even with the application of model-informed precision dosing, especially given the fact that busulfan shows considerable between-day variability, there will be a proportion of patients who will fail to achieve optimal exposure with dose 1, thus necessitating repeat blood collections and dose modifications. No model is perfect and continuous learning with model updates within the applied patient population is still required. Additional clinical or patient-specific covariates which are not accounted for in the current model may be important determinants of busulfan CL. These include specific disease or diagnoses, genetic variants in drug metabolizing enzymes involved in busulfan metabolism, and drug interactions including enzyme inducers or inhibitors . At our target. Continuous learning through model evaluation and re-estimation of PK parameters with additional data is critical to further improve precision dosing in applied populations with population-derived models.In summary, this work reinforces the clinical utility for a Bayesian-based, model-informed precision platform and TDM of busulfan over historical methods for achievement of cAUCThe control stream for the final PK model has been provided in the The studies involving human participants were reviewed and approved by UCSF IRB Committee. Written informed consent to participate in this study was provided by the participants' legal guardian/next of kin.PS, SG, RK, BW, SK, CD, and JL-B designed the study, enrolled patients, searched the published work, analyzed and interpreted data, wrote the report, reviewed the manuscript, and approved the final draft.This study was funded by an anonymous donor (JL-B).SG and RK are cofounders of and have equity in InsightRx. JL-B currently serves as a scientific consultant to InsightRX.The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


One of the most appreciated consequences of immunosenescence is an impaired response to vaccines with advanced age. While most studies report impaired antibody responses in older adults as a correlate of vaccine efficacy, it is now widely appreciated that this may fail to identify important changes occurring in the immune system with age that may affect vaccine efficacy. The impact of immunosenescence on vaccination goes beyond the defects on antibody responses as T cell-mediated responses are reshaped during aging and certainly affect vaccination. Likewise, age-related changes in the innate immune system may have important consequences on antigen presentation and priming of adaptive immune responses. Importantly, a low-level chronic inflammatory status known as inflammaging has been shown to inhibit immune responses to vaccination and pharmacological strategies aiming at blocking baseline inflammation can be potentially used to boost vaccine responses. Yet current strategies aiming at improving immunogenicity in the elderly have mainly focused on the use of adjuvants to promote local inflammation. More research is needed to understand the role of inflammation in vaccine responses and to reconcile these seemingly paradoxical observations. Alternative approaches to improve vaccine responses in the elderly include the use of higher vaccine doses or alternative routes of vaccination showing only limited benefits. This review will explore novel targets and potential new strategies for enhancing vaccine responses in older adults, including the use of anti-inflammatory drugs and immunomodulators. Human aging is associated with a general decline in physiological functions and increased susceptibility to disease. A dysregulation of the immune system, known as immunosenescence, is characteristic of aging and has been linked with negative clinical outcomes in older adults . One of While most studies report antibody responses as a correlate of vaccine efficacy, it is now widely appreciated that this may fail to identify important changes occurring in the immune system with age that may affect vaccine efficacy , 7. The Changes affecting both innate and adaptive immune function with age may lead to impaired vaccine responses in older people. Immunosenescence is primarily linked to the involution of primary lymphoid organs (bone marrow and thymus), resulting in depletion of the peripheral pool of naive B and T cells . To main+ T cell cytolytic activity upon ex vivo influenza challenge, CMV-seropositivity was associated with impaired cytolitic responses to influenza, measured by granzyme B levels in virus-challenged T cells  to overcome the low effectiveness of standard vaccines in the elderly . Data frAlternatively, the use of high-dose influenza vaccines in individuals over 65 years has also been shown to induce higher antibody titers and seroprotection rates compared to standard-dose vaccine , leadingAnother approach to improve influenza vaccine immunogenicity in older people is the use of alternative routes of vaccination. Most vaccines are delivered by intramuscular or subcutaneous injection, bypassing the mucosal immune compartment. Intranasal and intradermal routes for influenza vaccination have been developed with the aim of enhancing immunogenicity, particularly cell-mediated and mucosal immunity. Although studies suggest that intradermal influenza vaccination may enhance immunogenicity compared to standard intramuscular vaccines in persons over 65 years of age , pooled + T cell responses measured by IFN-gamma production and by cytotoxicity assays in vitro  infection. Although the reactivation of VZV can occur throughout life, the risk increases substantially with age and in conditions associated with a decline in T cell immunity. A live-attenuated VZV vaccine (Zostavax®) is approved for older adults to boost VZV-specific cell-mediated immunity (CMI). Evidence that the vaccine is partially effective in older patients comes from the Shingles Prevention Study that demonstrated a reduction in the incidence of herpes zoster and post-herpetic neuralgia by 51% and 67%, respectively . However+ T cells and an early IFN-gamma response that promotes vaccine immunogenicity  has been recently approved to prevent herpes zoster in older adults. It consists of recombinant VZV glycoprotein E and a liposome‐based AS01B adjuvant system. This system consists of two adjuvants, 3-O-desacyl-40-monophosphoryl lipid A (MPL) and QS-21 formulated in a liposomal delivery system (AS01B) . MPL is genicity . Interesgenicity . The effgenicity  and 89.8genicity . While lentified . A meta-entified . An addientified  and in tentified .+ T helper cells resulting in the generation of memory B cells specific for the polysaccharides  has been used for many years in older adults and is still the first choice in many countries. However this vaccine does not generate adequate immunological memory, as purified polysaccharides do not induce persistent antigen-specific memory B cells . Furthercharides . A largecharides . It is scharides .Antibody responses to tetanus and diphtheria vaccines are also suboptimal in old age. In addition to reduced antibody concentrations in the elderly, protection is short-lasting and a second booster after 5 years did not lead to additional long lasting immunity in older people .Overall, immune responses to currently recommended vaccines are suboptimal in older people. Despite the important successes achieved with strategies currently in place to improve vaccine responses in the elderly, most available vaccines still fail to elicit long-lasting immune responses and insufficiently trigger cell-mediated and mucosal immunity. Therefore, novel approaches should be explored to enhance immunogenicity and efficacy of vaccines in this population.+ T cells against conserved internal influenza proteins are important for limiting virus replication and disease severity -gamma and IL-10 ratio, granzyme B levels) measuring cellular immune responses to influenza challenge performed better than antibody titers as correlates of vaccine efficacy in older adults  response to influenza virus challenge, both of which have been shown to correlate with protection against influenza in older adults  are attractive vaccine targets as they can link both innate and adaptive immunity by mediating TCR-dependent and independent (innate-like) functions . A commo+ T cells. We have recently shown that as T cells differentiate toward senescence they become less responsive to TCR conventional signaling while acquiring innate-like functions  in cancer, new avenues of research are open for the use of these immunomodulators in other settings, including vaccination , 160. In vaccine . Ex vivoesponses . A studyesponses  althoughesponses . While mesponses , 165 or esponses  monoclonesponses , 167 theResponses to vaccination vary widely across individuals and are generally poorer in particular groups including not only the elderly but also individuals with autoimmune diseases, HIV infection  and cancThe discussion about the impact of aging on immunity and vaccination is particularly relevant at the moment as the COVID-19 pandemic placed again the spotlight on the vulnerability of older adults to emerging infectious diseases. Epidemiological data reveals that individuals over 60 years of age are disproportionately affected by SARS-CoV-2 infection experiencing the most severe forms of disease and the highest hospitalization rates –180. Age+ and CD8+ T cells, with increased frequencies of highly differentiated CD8+ T cell “EMRAs” and exhausted PD1+ CD8+ T cells, providing evidence for the association between an immunosenescent phenotype and disease severity. Other studies have shown that severe COVID-19 disease correlated with elevated serum concentrations of inflammatory cytokines including interleukin-6 (IL-6), granulocyte colony-stimulating factor (G-CSF), IP-10, MCP1, macrophage inflammatory protein 1α (MIP1α) and tumor necrosis factor (TNF)  –191. Amoor (TNF)  providinor (TNF) . Accumulor (TNF) , 194 indor (TNF) , 196. Asor (TNF)  and is por (TNF) . Thus, ior (TNF) .Despite the important successes achieved with current vaccines, most available vaccines still fail to elicit long-lasting immunity in older adults. Current vaccine strategies must evolve to be able to enhance cell-mediated and mucosal immunity in addition to inducing long-lasting antibody responses. However, to date most clinical trials leading to vaccine approval in older adults rely entirely on antibody responses as correlates of protection and thus novel correlates of vaccine effectiveness are needed that fully reflect the changes occurring with age in the immune system. The use of system vaccinology approaches can aid researchers in identifying signatures that predict protective immune responses and this information can be used for optimization of current vaccination strategies. Responses to vaccination vary widely across individuals and baseline immune profiles matter to determine the outcome of vaccination. Recent data suggests that excessive baseline inflammation is deleterious and may hamper immune responses and thus novel approaches aimed at reducing inflammation may offer novel opportunities to improve vaccine responses in older individuals. Yet the prevailing view is that adjuvants improve vaccine responses by promoting local inflammation. Thus more research is needed to understand the role of inflammation in vaccine responses and to reconcile these seemingly paradoxical observations. It could be speculated that the effects of systemic versus local inflammation are distinct and that the beneficial effects of anti-inflammatory drugs on vaccine response result from the systemic reduction of the low-level chronic inflammation. Additionally, chronic immune activation may be associated with desensitization or tolerance to new antigenic stimulation resulting in poor immune responses. Thus stronger adjuvants may be needed to overcome this tolerogenic state and alleviate the consequences of chronic inflammation. There is a need to develop newer and more specific adjuvants, able to fine tune immune responses and selectively stimulate pathways that lead to long-lasting immune protection. As our understating of immunosenescence and inflammaging increases new individualized approaches could point towards the development of more effective vaccines for older individuals.BP has done the literature search and writing. AA and X-NX contributed for the writing and revision of the manuscript. All authors contributed to the article and approved the submitted version.BP is funded by the Joint Research Committee of Chelsea and Westminster Hospital NHS Foundation Trust and Imperial College London, UK. AA was supported by the Medical Research Council (MRC) Grand Challenge in Experimental Medicine (MICA) Grant (MR/M003833/1). X-NX was supported by the Department of Health and Social Care using UK Aid funding and is managed by the Engineering and Physical Sciences Research Council ; Note: the views expressed in this publication are those of the author(s) and not necessarily those of the Department of Health and Social Care).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


IntroductionDilated cardiomyopathy has been associated with remarkably high mortality despite guideline-directed therapy. This study compares the all-cause mortality rate between a cardiac contractility modulation group and a standard therapy group in patients with dilated cardiomyopathy who were monitored via follow-up for 12 weeks or more.Materials and methodsWe conducted a systematic search of Medline (PubMed) and Cochrane Central Register of Controlled Trials for abstracts and fully published studies (from inception to October 2018). We searched for articles comparing cardiac contractility modulation device therapy with standard therapy for patients with dilated cardiomyopathy between September 1, 2018, and October 30, 2018.Only fully published randomized clinical trials comparing all-cause mortality outcomes of device therapy and standard therapy for patients with dilated cardiomyopathy were included in our meta-analysis. A total of 673 studies were identified. Studies that were systematic reviews or meta-analyses, study designs or protocols, trials on other regimens, wherein medical therapy was not compared, or wherein the primary outcome of mortality was not assessed, were excluded.Data were abstracted by two independent reviewers. A random-effect model using the Mantel-Haenszel method calculated the weighted risk ratio (RR). Statistical analyses were performed using Review Manager 5.3 . The primary outcome of interest was a comparison of all-cause mortality between the two groups when patients were monitored via follow-up for 12 weeks or more.Results2 = 0%).Four fully published randomized clinical trials met the inclusion criteria of our analysis. A random-effect model using the Mantel-Haenszel method calculated the weighted RR. Our analysis included a total of 930 patients. The cardiac contractility modulation therapy group showed no significant reduction in all-cause mortality compared to the standard therapy group . However, the trend was toward device therapy. Tests for statistical heterogeneity did not show any significant heterogeneity (P = .82, IConclusionsCardiac contractility modulation device therapy is not associated with significant all-cause mortality reduction in patients with dilated cardiomyopathy. Our meta-analysis underscores the need for a large randomized controlled trial on the efficacy of cardiac contractility modulation in a population with dilated cardiomyopathy who are ineligible for cardiac resynchronization therapy. Heart failure with reduced ejection fractions (HFrEF) accounts for 50% of patients with heart failure. The definition of HFrEF has varied, with guidelines of left ventricular (LV) ejection fraction (EF) of < 35%, < 40%, or ≤ 40%. Remarkably high morbidity and mortality are associated with HFrEF despite standard medical and device therapy in the modern era . CardiacA new electrical device, the cardiac contractility modulation (CCM) device, was proposed for enhancing ventricular contractility strength independent of the synchrony of myocardial contraction ,6. PreclCCM includes an implantable pulse generator, the Optimizer™ system . The pulse generator delivers highly specialized nonexcitatory electric signals to the myocardium in the right ventricular septum during the absolute refractory period. The resulting enhancement in contractility involves changes in cardiomyocyte Ca2+ handling and normalizing of the messenger ribonucleic expression of heart failure (HF)-related genes ,10. SeveSearch strategyWe conducted a systematic review of the literature and the meta‐analysis of randomized clinical trials according to established methods and standards recommended by the Cochrane Collaboration and the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) statement ,16. We cData extraction and quality assessmentData were abstracted by two reviewers (YI and MN) independently. Only fully published articles were used for the data collection. Fully published randomized controlled trials (RCTs) were assessed for mortality data, and a minimum follow-up period of 12 weeks or more. Data were abstracted onto Microsoft Excel spreadsheets. The quality of the studies was evaluated using the risk of bias assessment table by Review Manager 5.3 . We assessed the design, conduct, and analysis of the trial using a 3-point scale: low risk of bias, high risk of bias, or unclear. Assessment of risk of bias for each trial included the following questions: (i) Was the allocation sequence adequately generated? (ii) Was the allocation adequately concealed? (iii) Was knowledge of the allocated intervention adequately prevented  throughout the trial? (iv) Were incomplete outcome data adequately addressed for every outcome? (v) Were the trial reports free from selective outcome reporting? (vi) Was the trial apparently free of other problems that could put it at risk of bias? Publication bias was assessed for the primary outcome of mortality using a funnel plot.Data analysis2 statistic, according to the Cochrane Handbook. Publication bias was assessed for the mortality outcomes using a funnel plot. The primary outcome of interest was the comparison of all-cause mortality between the two groups.Review Manager 5.3 was used for statistical analyses. Because of the large amount of heterogeneity in the randomized clinical trials, we used a random-effects model to calculate weighted risk ratio (RR) using the Mantel-Haenszel method  of improvement between treatment and control groups were calculated, and Forest plots were constructed). Heterogeneity between studies was assessed using the IA total of 673 studies were identified. Among these, 648 studies were excluded because they were non-randomized studies. Twenty-five articles were assessed for eligibility criteria. Three fully published randomized clinical trials and one cross-over study were included for the final analysis. Studies that were reviews, systematic reviews or meta-analyses, study designs, rationales or protocols, trials including other outcomes, or featured a follow-up with patients for less than 12 weeks were excluded . A visual assessment of a funnel plot of the outcome of mortality did not identify any notable asymmetry suggestive of publication bias , and not in the group switched from sham to active therapy . TherefoThe Borggrefe et al. study was designed on the premise of the Multisite Stimulation in Cardiomyopathies (MUSTIC) trial of CRT ,18. The There was no increase in the ventricular arrhythmias, ICD shocks, or anti-tachycardia pacing in patients having both ICD and CCM devices ,13.CCM implantation did not show a significant change in the all-cause mortality compared with optimal medical therapy; however, the overall trend was towards device therapy. The cardiac contractility modulation device has been associated with more efficacy at a certain level. It may also behave like CRT when it comes to reverse remodeling and may take longer a follow-up to detect significant changes in the outcomes. CCM has not been associated with an increase in ventricular arrhythmias, ICD shocks, or anti-tachycardia pacing in patients having both ICD and CCM devices.Our meta-analysis showed that implantation of the cardiac contractility modulation device did not show a significant reduction in the all-cause mortality when compared with an optimal medical therapy group. Our study underscores the need for large scale RCTs for the measurement of all-cause mortality as well as cardiovascular mortality.


Eleclazine (GS-6615) is a putative antiarrhythmic drug with properties similar to the prototypical atrial-selective Na+ channel blocker ranolazine that has been shown to be safe and well tolerated in patients.Atrial-ventricular differences in voltage-gated Na+ currents.The present study investigated atrial-ventricular differences in the biophysical properties and inhibition by eleclazine of voltage-gated Na+ currents  were recorded at room temperature (∼22°C) from rat isolated atrial and ventricular myocytes.The fast and late components of whole-cell voltage-gated NaINa activated at command potentials ∼5.5 mV more negative and inactivated at conditioning potentials ∼7 mV more negative than ventricular INa. There was no difference between atrial and ventricular myocytes in the eleclazine inhibition of INaL activated by 3 nM ATX-II (IC50s ∼200 nM). Eleclazine (10 μM) inhibited INa in atrial and ventricular myocytes in a use-dependent manner consistent with preferential activated state block. Eleclazine produced voltage-dependent instantaneous inhibition in atrial and ventricular myocytes; it caused a negative shift in voltage of half-maximal inactivation and slowed the recovery of INa from inactivation in both cell types.Atrial INa. The more negative voltage dependence of INa activation/inactivation in atrial myocytes underlies differences between the 2 cell types in the voltage dependence of instantaneous inhibition by eleclazine. Eleclazine warrants further investigation as an atrial-selective antiarrhythmic drug.Differences exist between rat atrial and ventricular myocytes in the biophysical properties of  Compared with the voltage-gated Na+ channel current (INa) of ventricular myocytes, atrial INa inactivates and activates at more negative potentials, with more rapid onset, and recovers more slowly from inactivation.,12However, despite the effectiveness of class Ic antiarrhythmic drugs in the treatment of AF, the Cardiac Arrhythmia Suppression Trial showed that these drugs carried an increased mortality in patients with myocardial infarction, precluding their use in such individuals.+ channels.+ channels through binding to the local anesthetic binding site within the Na+ channel vestibule and is relatively selective for the late Na+ current (INaL).+ channels arises through a preferential block of the activated state and trapping of the drug in the inactivated state in combination with atrial-ventricular differences in (1) the voltage dependence of INa activation and inactivation and (2) resting membrane potential and diastolic interval (DI).,,IKr) and delays ventricular repolarization.,IKr is desirable. It can be anticipated that selective inhibitors of INaL that show preferential block of the activated state with rapid rates of association and dissociation would also show an atrial-selective inhibition of the fast component of INa at higher rates.,INaL inhibitor with little activity against IKr, has been shown to have an atrial-selective action against action potential duration, postrepolarization refractoriness, and the maximum upstroke velocity of the action potential, although whether the atrial-selective action of the drug extends to fast INa itself remains unclear.,+ channel isoforms and high brain penetrance make it unattractive for development as an antiarrhythmic drug.The antianginal agent ranolazine (Ranexa) is a prototypic example of a drug with atrial-selective action against voltage-gated NaINaL blocker with properties similar to ranolazine that has been reported to be safe and well tolerated and to shorten the QTcF interval in patients with long QT3 syndrome.,INa in a use-dependent manner consistent with preferential activated state block with little effect on IKr,INa and its inhibition by ELE in rat cardiac myocytes.In contrast, eleclazine  is a selective Detailed methods are available in supplemental information online.Guide for the Care and Use of Laboratory Animals.,Rat left ventricular and left atrial myocytes were isolated as described previously using procedures approved by the University of Bristol Animal Welfare and Ethics Board in accordance with UK legislation and the + currents were recorded at room temperature using the patch clamp technique. The fast component of the Na+ current (INa) was recorded using symmetrical internal and external [Na+] (5 mM) whereas the late Na+ current (INaL) was recorded using 70 mM external and 5 mM internal [Na+]  and CV were measured in Langendorff-perfused rat hearts as described previously.INa.,ELE -one) was a gift of Dr James T. Milnes . ELE was used at 10 μM to produce use-dependent inhibition of fast P < .05. Curve fitting was performed by nonlinear least squares using Igor Pro v6 .Data are presented as the mean ± standard error of the mean. The limit of statistical confidence was INa in both atrial and ventricular myocytes , consistent with their smaller size. The current density–voltage relations of each cell type were fitted by a modified Boltzmann relation  approximately 5.5 mV more negative than that of ventricular INa . Atrial INa inactivated at more negative voltages than the current in ventricular cells, with significant differences evident between the 2 cell types in the range from -100 mV to -80 mV  of atrial cells was ∼7 mV more negative than that of ventricular myocytes  activated on depolarization to -20 mV from atrial , the atrial INaL density normalized to capacitance as an index of membrane surface area was almost 2-fold greater in atrial than in ventricular myocytes . Superfusion of the cells with 3 nM sea anemone toxin (ATX-II) caused a marked increase in INaL in both atrial and ventricular myocytes . The ATX-II-activated INaL was inhibited by ELE in a concentration-dependent manner in both atrial and ventricular myocytes (IC50) by ELE  of -120 mV  with voltage-gated Na -120 mV . The efforter DI A and B. orter DI . The useorter DI C. Howeve -120 mV D. To exate cells . There wte cells C. Howevete cells D. In conVhalf,inact) in atrial and ventricular myocytes  of 5–30 ms and a slow time constant (τs) of 100–220 ms  ∼2.5 ms and a slow phase with τs ∼180 ms . Subsequent perfusion with ELE (1 μM) in the continued presence of CCh resulted in recovery of ERP to ∼60% of the control value (P < .05). On the other hand, neither CCh nor ELE had significant effect on CV  in Langendorff-perfused rat hearts A. Perfusct on CV B. Taken + currents: atrial INa was activated at command potentials ∼5.5 mV more negative and inactivated at conditioning potentials ∼7 mV more negative than ventricular INa, the activation time-to-peak INa following depolarization to voltages of -50 to -30 mV was also shorter in atrial than in ventricular myocytes, and the recovery of INa from inactivation was significantly slower in atrial than in ventricular myocytes. In these respects, the differences in INa between rat atrial and ventricular cells in the present study were similar to those reported previously in cardiac myocytes from various species.,INa density in atrial compared to ventricular myocytes, there was no difference in INa density between the 2 cell types in the present study.,,INaL was greater in atrial than in ventricular myocytes. Atrial-ventricular differences in the inhibition of INa by ELE were also evident: (1) in addition to marked use-dependent inhibition that was not significantly different between the 2 cell types, ELE caused an instantaneous inhibition of INa in atrial and ventricular myocytes that was dependent on membrane potential, and consequently arose at more negative membrane potentials in atrial myocytes than in ventricular myocytes; and (2) there was an atrial-selective slowing of the fast time constant of recovery from inactivation. To the best of our knowledge, this represents not only the first report of atrial-ventricular differences in the effects of ELE on INa from any species, but the first report of atrial-ventricular differences in inhibition of peak INa by any INaL inhibitor with rapid kinetics other than ranolazine. Consistent with inhibition of peak INa, ELE partially reversed the shortening in atrial ERP induced by the muscarinic agonist CCh, indicating an atrial antiarrhythmic action of the drug. On the other hand, it is unclear whether the effect of ELE was atrial-selective.Clear atrial-ventricular differences were found in the biophysical properties of rat cardiac voltage-gated Na+ channels with unusually rapid kinetics, interacting with the local anesthetic binding site and showing marked selectivity for INaL relative to fast INa.INaL by ELE, indicating similar affinity of ELE for atrial and ventricular Na+ channels. Our data are consistent with the inhibition of INaL by ELE via open channel block, as suggested in previous reports.INa and INaL by ELE has been shown to be voltage-dependent so that the IC50s for inhibition of the ATX-II-activated INaL in atrial and ventricular myocytes in the present study  were comparable with the value reported previously in rabbit ventricular myocytes at a corresponding HP of -80 mV (260 nM).INa from rabbit ventricular myocytes and recombinant human Nav1.5 channels,,INa inhibition evident during the repeated pulse protocol in the present study , consistent with trapping of the drug by the inactivation gate impeding dissociation of ELE from the channel. The degree of instantaneous inhibition by ELE in atrial and ventricular myocytes at an HP of -100 mV, at which there was very little INa activation in either cell type, was striking. From an HP of -120 mV, the instantaneous inhibition of INa was markedly reduced in both cell types, becoming negligible in ventricular myocytes. Although a hydrophobic pathway for access of neutral drugs to the local anesthetic binding site of Na+ channels has been suggested, the relatively large size of ELE (molecular weight ∼415.4 g.mol-1), comparable to ranolazine, argues against significant access via that route.,The accentuation of use-dependent inhibition of fast ,Given the use-dependent action of ELE, its preference for the activated state, and rapid dissociation from the noninactivated sodium channel, the less negative resting membrane potential, differences in action potential morphology, and consequent shorter diastolic interval of atrial relative to ventricular myocytes may contribute to an atrial-selective action of ELE.INa (or INaL) in the kinetics of drug binding/dissociation, the more negative voltage dependence of INa activation and inactivation underlies an atrial-selective instantaneous inhibition of INa by ELE. The present study provides further evidence to support the contention that INaL inhibitors have differential effects on atrial and ventricular INa. However, additional future investigation is now required to establish whether the actions of ELE on atrial INa form the basis for an atrial-selective antiarrhythmic action. Chamber-specific human induced pluripotent stem cell–derived cardiomyocytes (hiPSC-CM) represent an attractive potential human model for validation of the atrial-selective action of antiarrhythmic drugs. However, though differentiation protocols are available to drive hiPSCs towards an atrial- or ventricular-like phenotype, iPSC-CM express both fetal (exon 6A) and adult (exon 6) isoforms of SCN5A, leaving the relevance of the data from studies using these models open to question.Although there was no evidence of any difference between atrial and ventricular


Recent findings challenge the prior notion that the cerebellum remains unaffected by Alzheimer’s disease (AD). Yet, it is unclear whether AD exacerbates age-related cerebellar grey matter decline or engages distinct structural and functional territories. We performed a meta-analysis of cerebellar grey matter loss in normal ageing and AD. We mapped voxels with structural decline onto established brain networks, functional parcellations, and along gradients that govern the functional organisation of the cerebellum. Importantly, these gradients track continuous changes in cerebellar specialisation providing a more nuanced measure of the functional profile of regions vulnerable to ageing and AD. Gradient 1 progresses from motor to cognitive territories; Gradient 2 isolates attentional processing; Gradient 3 captures lateralisation differences in cognitive functions. We identified bilateral and right-lateralised posterior cerebellar atrophy in ageing and AD, respectively. Age- and AD-related structural decline only showed partial spatial overlap in right lobule VI/Crus I. Despite the seemingly distinct patterns of AD- and age-related atrophy, the functional profiles of these regions were similar. Both participate in the same macroscale networks , support executive functions and language processing, and did not exhibit a difference in relative positions along Gradients 1 or 2. However, Gradient 3 values were significantly different in ageing vs. AD, suggesting that the roles of left and right atrophied cerebellar regions exhibit subtle functional differences despite their membership in similar macroscale networks. These findings provide an unprecedented characterisation of structural and functional differences and similarities in cerebellar grey matter loss between normal ageing and AD. This isHowever, it is unclear if these AD-related changes exacerbate existing negative effects of ageing on the cerebellum or whether they additionally target regions less vulnerable to normal ageing processes. Moreover, a direct comparison of the functional characterisation of regions affected by ageing and AD is also still lacking. Here we combine a coordinate-based meta-analytic approach to identify the most consistent patterns of grey matter loss across studies with multiple complimentary functional mappings to advance our understanding of cerebellar vulnerability to normal ageing and Alzheimer’s disease .The importance of the cerebellum for multiple cognitive, affective and motor domains is increasingly being recognised , as is iAn important question concerns the interpretation of these structural findings with respect to potential consequences for function. There are now multiple maps of cerebellar functional organisation: a) an atlas with discrete functional boundaries within the cerebellum derived from task-based fMRI , b) a maAll of these approaches provide complimentary information about cerebellar functional organisation: the network-based approach puts cerebellar regions into context with the functional characterisation of the neocortex ; the disYet, in most studies, the interpretation of implications of age- or AD-dependent structural decline for cerebellar function is based on the location of the identified cluster within a given lobule . While vHere, we used the discrete and network-based maps in combination with the gradient-based approach which allowed us to place our meta-analytic structural imaging findings on multiple functional maps and to compare those derived from ageing with those from AD. The use of gradients can highlight even subtle functional differences between neuroanatomical regions vulnerable to AD and normal ageing , which c22.1For a meta-analysis of cerebellar grey matter decline in healthy ageing, we carried out a systematic literature search on Pubmed and PsycInfo using search terms related to ageing and structural neuroimaging in the title and/or abstracts of peer-reviewed records that were published until October 1st 2019. Inclusion criteria required 1) an analysis that compared grey matter volume in healthy young (<40 years) and older participants (60 + years), and 2) availability of coordinates of regions with grey matter decline . Studies were excluded if 1) participants had psychiatric or neurological conditions, 2) the cerebellum was excluded from the analysis, 3) the study used confounding factors besides covariates sex, age and education in the analysis, and 4) the study reanalysed previously published data already included in our meta-analysis. We extracted sample size, participant demographics, coordinates of cerebellar grey matter loss and information regarding the statistical analysis from each included study. All coordinates reported in Talairach space were converted to MNI space using the icbm2tal transform employed by the conversion tool provided by GingerALE (brainmap.org).N = 18 studies were identified for inclusion in the meta-analysis. Input for the analysis were coordinates of age-related decreased cerebellar grey matter volume or density and the sample size of each study. We also conducted an updated analysis of cerebellar grey matter decline in late-onset AD in n = 13 studies based on our previous research  and associations between cerebellar grey matter and cognitive performance see Appendix B  for AD.2.2http://brainmap.org)  using version 2.3.6 of GingerALE (map.org) . In the p < .05 for cluster-level family-wise error correction (i.e. the cluster-level inference option on GingerALE), which provides the best compromise between sensitivity and specificity (p < .001 (uncorrected), which is one of the two thresholds recommended by GingerALE  based meta-analysis does not provide information about the likelihood or prevalence of cerebellar atrophy in older adults and AD but rather characterises the pattern of lobular grey matter loss in cases where cerebellar atrophy is indeed present.2.3We used the SUIT toolbox to create multiple cerebellar maps, which are created by unfolding and flattening the cerebellar surface to obtain a 2D representation . Note thTo put our structural findings into context, we used three maps of the functional organisation of the cerebellum that have been derived on the basis of cerebellar functional activation and cortico-cerebellar connectivity patterns: 1) the Buckner networks based on intrinsic connectivity derived from resting-state fMRI showing the membership of different cerebellar subregions to one of the established functional connectivity networks of the brain , 2) the 2.4https://xaviergp.github.io/littlebrain/). LittleBrain maps the voxels identified in our structural analysis onto gradients that capture low-dimensional properties of cerebellar functional organization that has previously been described using a non-linear dimensionality reduction method called diffusion map embedding on Human Connectome Project functional resting-state data  and transmodal cognitive processing such as cerebellar default mode network regions on the other (Crus I/II and lobule IX). Gradient 2 isolates attentional processes moving along a task-focused to task-unfocused functional axis . One endAfter identifying regions of grey matter loss, we created plots of the position that each of the voxels with grey matter loss in aging, AD and the Aging-AD conjunction held along the three functional gradients. Furthermore, each voxel was colour-coded according to its participation in the cerebro-cerebellar resting-state networks identified in W > 0.8, p < .001), differences between the AD and ageing gradient values were tested using permutation testing of differences in rank sums. Gradient values were assigned to the AD and ageing group randomly and the rank sums between the real observed and random differences between the two groups were tallied. The reported p-value for the permutation test represents the probability of obtaining the observed differences in gradient values between the true AD- and true age-related voxels from random group assignments of each voxel in the permutation procedure.Gradient values were extracted for further statistical analyses to determine whether the distribution along each gradient for the ageing and AD effects differed from one another. Due to non-normality of the true gradient value distributions  and completely overlapping distributions have 1 =U 0 (null effect)  .The distributions of gradient values were visualised using violin plots in ggplot2 in RStudio version 1.0.153 .2.5The robustness of our results for the ageing and AD analyses, respectively, to the removal of studies was tested using a jackknife procedure, in which the meta-analysis was carried out without a given study. As a result, 18 one-study removed analyses were carried out for the ageing dataset and 13 such analyses were carried out for the AD dataset. We also tested whether the difference in the distribution of AD gradient values and the jackknife analysis gradient values remained robust to the removal of any one study. Our results regarding age- and AD-related atrophy regions and differences in gradient values between ageing and AD remained robust across jackknife analyses (for details see Appendix D).33.1p < .020). Cluster 1 was situated in right Crus II. Cluster 2 encompassed parts of right Crus I and lobule VI. Cluster 3 was in left Crus II. The fourth cluster of grey matter volume reduction was in vermal lobule VI, encroaching upon left hemispheric lobule VI. The fifth cluster was located in lateral left posterior hemisphere with peaks in Crus II and Crus I, with some extension into lobules VIIb and VIII.The ageing analysis involved 18 studies with 64 coordinates of cerebellar grey matter atrophy across 2441 subjects . Cluster 1 included regions of right Crus I and II. Cluster 2 comprised regions of lobule VI and Crus I. The inclusion of the additional studies in this analysis compared to our previous results increased the extent but did not have a substantial effect on the location of the peak coordinates  and encompassed both task-focused and task-unfocused domains . Gradient 3 values for ageing included both minimum and maximum values, reflecting the distribution of age effects across the two hemispheres in cognitive territories of the cerebellar cortex . According to the overlap of age-related grey matter loss and the A comparison of the clusters of age-related grey matter reduction from our meta-analysis with the network connectivity patterns derived from Buckner and colleagues  showed tM = 3.381, SD = 2.427), while motor regions are spared. The range of Gradient 2 values implicates both task-focused and unfocused processing regions in AD (M = 0.220 SD = 0.929). Gradient 3 values for AD were negative, reflecting the right lateralisation of grey matter decline . According to the overlap of age-related grey matter loss and the The regions affected by AD also participate in DMN and the frontoparietal network. Higher Gradient 1 values highlight the involvement of cerebellar cognitive regions in this disease , reflecting the involvement of only the right (AD) as opposed to left and right (ageing) cerebellar hemispheres in each group. This finding could not be identified only based on macroscale brain network membership  meta-analysis to identify consistent patterns of cerebellar grey matter atrophy across 18 studies of healthy ageing. We further compared age-related decline to that observed in 13 studies of Alzheimer’s disease. Age and AD exhibited grey matter decline in posterior cerebellum in Crus I/II and lobule VI, albeit in largely non-overlapping subregions of these lobules. The most striking finding was the strict right lateralisation of grey matter loss in AD compared to bilateral decline in healthy ageing.We used three complimentary mappings of the cerebellum to characterise the functional profile of the regions with grey matter loss in ageing and AD: the known intrinsic brain networks based on resting state fMRI , the tasDespite only a small spatial overlap of regions with age- and AD-related cerebellar grey matter loss, both exhibit a strong bias towards cognitive as opposed to motor processing (Gradient 1) and involvement across the task-focused to unfocused continuum  would be described with the same gradient values. However, left and right hemispheric areas of nonmotor processing  lie on two opposing ends of the spectrum .These findings suggest that regions with grey matter loss in ageing and AD do not only reflect differences in spatial localisation to the left and right hemispheres, but also qualitative differences in the functions carried out by the left and right homologues of posterior cerebellar cortex. They point to a dissociation between the functional connectivity fingerprint of the two homologues of posterior cerebellar lobules and highlight their differential vulnerability to AD and age, respectively. In contrast, the intrinsic functional connectivity networks based on resting-state fMRI grouped both regions into the same networks  and even healthy older adults with subjective memory complaints . This maThere is mixed evidence with respect to the vulnerability of the cerebellum to amyloid beta. Some argue that the cerebellum is mostly resistant to amyloid pathology until later stages of Alzheimer’s disease . Others Longitudinal studies that could track the evolution of cerebellar volume and function across the AD-continuum are needed to better understand the role of the cerebellum in functional decline and its interplay with other brain areas. Differential subregional vulnerability to AD pathology or to normal ageing may be due to downstream influences resulting from cerebro-cerebellar synergism . Structu4.3It is surprising that we did not find clusters of significant age-related grey matter loss in anterior motor regions of the cerebellum. Prior evidence has shown volumetric decline of motor regions in normal ageing which correlates with motor deficits . HoweverIt should be noted though, that this apparent limitation of the coordinate-based meta-analysis also presents an advantage. Our meta-analytic method does not require lobular boundaries as a constraint, which would be detrimental to the interpretation of functional implications given that anatomical borders do not translate neatly to boundaries between functional domains . These rGiven that the majority of AD studies in our analysis included mild to moderate AD cases, we could not conduct subgroup analyses based on disease severity. We would expect, however, that grey matter atrophy in AD occurs in a network-based fashion : posteriAs discussed above, prior studies and our findings converged to point to right regions of lobule VI and Crus I/II as particularly vulnerable to age, AD genetic risk and actual AD cases. AD may exacerbate the downward trajectory of this region already observed in healthy ageing shown here. Alternatively, the studies that found significant age-related grey matter loss in these regions may point out early declines that will later manifest as AD. Our data are limited in that they cannot test this possibility given the lack of longitudinal data in our analysis.It is not clear to what extent cerebellar structural decline has clinical relevance for behavioural deficits in AD patients. As mentioned above, cerebellar deficits alone may not be sufficient to result in scores below the cut-off point for normal functioning in standard AD screenings because they are masked by the large number of test items that are insensitive to cerebellar function . It is pFinally, our findings may be of relevance for studies aiming to determine optimal targets for neuromodulatory therapeutic approaches in ageing and AD. Non-invasive modulation of cerebellar regions has been shown to have network- and task-specific effects on connected neocortical regions . Targeti4.4Structural and functional analyses combined paint a picture of divergent and convergent patterns of cerebellar vulnerability to age and AD. The meta-analysis highlights vulnerability of posterior cerebellum to AD and ageing , suggesting that some aspects of the age-related downward trajectory of grey matter may be exacerbated by AD pathology. The strict right lateralisation of AD atrophy compared to bilateral effects in healthy ageing was striking. Notably, besides being located in the same lobules, the subregions of structural atrophy for AD and ageing were mainly non-overlapping. Nonetheless, regions with vulnerability to AD and ageing exhibited similar functional profiles: they participated in the same large-scale discrete functional networks, were involved in working memory, attention and language processing, and were located in similar positions along major functional gradients (cognitive vs. motor and degree of task focus). Despite these similarities, differences along Gradient 3 allowed for the observation of age-AD divergence along alternative dimensions of cerebellar functional hierarchies as exemplified by different preferences along the tertiary cerebellar gradient  and showed that only regions with age-related grey matter decline were involved in affective processes. These findings show subtler differences in the functional fingerprint of regions impacted by AD and ageing that the standard categorical parcellations of brain networks was not able to detect. Our study provides an unprecedented characterisation of structural and functional localisation differences and similarities in cerebellar atrophy between ageing and AD. They also show how the use of multiple functional maps of the cerebellum is synergistic in interpreting the implications of regional grey matter loss. More research is needed to better understand 1) how age and pathology impact cerebellar computational processes, 2) how cerebellar interactions with other brain regions may influence cognitive decline or preservation in healthy ageing and AD, and 3) the role of subregional cerebellar grey matter loss in the neuropsychology of AD.Helena M. Gellersen: Conceptualisation, Data curation, Methodology, Software, Validation, Formal analysis, Investigation, Visualisation, Project administration, Writing - original draft, Writing – review & editing. Xavier Guell: Conceptualisation, Methodology, Software, Visualisation, Writing – review & editing. Saber Sami: Conceptualisation, Methodology, Writing – review & editing, Supervision.


Systemic light-chain (AL) amyloidosis is caused by a small B cell, most commonly a plasma cell (PC), clone that produces toxic light chains (LC) that cause organ dysfunction and deposits in tissues. Due to the production of amyloidogenic, misfolded LC, AL PCs display peculiar biologic features. The small, indolent plasma cell clone is an ideal target for anti-CD38 immunotherapy. A recent phase III randomized study showed that in newly diagnosed patients, the addition of daratumumab to the standard of care increased the rate and depth of the hematologic response and granted more frequent organ responses. In the relapsed/refractory setting, daratumumab alone or as part of combination regimens gave very promising results. It is likely that daratumumab-based regimens will become new standards of care in AL amyloidosis. Another anti-CD38 monoclonal antibody, isatuximab, is at an earlier stage of development as a treatment for AL amyloidosis. The ability to target CD38 on the amyloid PC offers new powerful tools to treat AL amyloidosis. Future studies should define the preferable agents to combine with daratumumab upfront and in the rescue setting and assess the role of maintenance. In this review, we summarize the rationale for using anti-CD38 antibodies in the treatment of AL amyloidosis. Light-chain (AL) amyloidosis is caused by a small B cell clone producing an immunoglobulin light chain that causes target organ toxicity and deposits in tissues in the form of amyloid fibrils . The cliThe current treatment of AL amyloidosis targets the underlying clonal disease to reduce the supply of the amyloid light chain . Other aIn the vast majority of cases, the amyloid clone is composed of plasma cells (PCs), and agents and regimens used in multiple myeloma are also employed in AL amyloidosis. In a smaller subset of patients, the amyloid clone has the characteristics of a marginal zone lymphoma or a lymphoplasmacytic clone ,11,12. TThis small clone is striving to counteract the intrinsic cellular stress produced by misfolded light chains. It has been shown that amyloidogenic light chain (LC) production is associated with distinctive organellar feature and expression patterns indicative of cellular stress . These cHigher CD38 expression in AL amyloidosis is associated with the worst event-free survival probably because it is associated with more severe cardiac involvement, as shown by higher serum NT-proBNP concentrations .The first anti-CD38 monoclonal antibody becoming available in multiple myeloma was daratumumab, and in a couple of years, a few prospective trials and many retrospective studies assessed its role also in AL amyloidosis. Daratumumab is a fully human IgG1κ monoclonal antibody directed against CD38 that acts both as a PC-depleting agent and as an immuno-modulator . EngagemDaratumumab is labeled for the treatment of newly diagnosed and relapsed refractory MM patients and is available for both intravenous and subcutaneous injections. On 15 January 2021, the US Food and Drug Administration (FDA) granted accelerated approval to daratumumab and hyaluronidase-fihj in combination with bortezomib, cyclophosphamide, and dexamethasone (DARA-CyBorD) for the treatment of newly diagnosed adult patients with light-chain (AL) amyloidosis .The role of daratumumab in upfront treatment of patients with AL amyloidosis was explored in the recently completed randomized phase III ANDROMEDA trial NCT03201965). The randomized part of this trial was preceded by a safety run-in study to assess the tolerability of the addition of subcutaneous daratumumab to CyBorD . The tre01965. ThHematologic and organ responses are very strong predictors of overall survival in AL amyloidosis, and these unprecedentedly high response rates strongly support daratumumab-CyBorD as a novel standard of care for upfront treatment of patients with this disease . MoreoveTwo phase II clinical trials evaluated daratumumab as a rescue therapy for patients with AL amyloidosis ,41. MoreIn a phase II prospective trial, Sanchorawala et al. treated 22 patients with previously treated AL amyloidosis with single-agent daratumumab . OverallRetrospective studies of daratumumab in relapsed/refractory patients with AL amyloidosis also addressed daratumumab-based combinations. The two largest studies were published by the Heidelberg  and PaviOverall, the published trials and retrospective series indicated that daratumumab is highly effective also in relapsed/refractory patients with AL amyloidosis, with apparently no remarkable differences between single-agent and combination therapies.Our review of safety data of daratumumab in AL amyloidosis is based on prospective studies, due to possible underreporting of adverse events in retrospective series. Chemotherapy safety is an especially relevant issue in systemic AL amyloidosis because the hematologic malignancy needs to be effectively and rapidly targeted in patients with often severe amyloid-related multiorgan dysfunction and damage.In the two phase II clinical trials in relapsed refractory patients, single-agent daratumumab was administered intravenously at the dosage of 16 mg/kg. In the study by Sanchorawala et al., grade 3 or 4 adverse events were observed in 91% of patients who received a median of 31 infusions . The mosTargeting CD38 on plasma cells emerges as a new additional option in the treatment of AL amyloidosis. Daratumumab grants unprecedented high hematologic response rates both in combination with CyBorD in the upfront setting and as a rescue agent alone or in combination with bortezomib and lenalidomide. The recently completed randomized phase III ANDROMEDA trial has set daratumumab-bortezomib combinations as the new standard of care in AL amyloidosis. Moreover, while accessibility of daratumumab increases, many more daratumumab-naïve patients will receive this antibody as a rescue treatment. In the meantime, other CD38-targeting strategies are being tested in AL amyloidosis. For instance, the early results of a phase II trial (NCT03499808) of isatuximab  in AL amyloidosis were presented at the 2020 meeting of the American Society of Hematology . In 35 rWhile the advent of daratumumab and possibly other CD38-targeting approaches will rapidly change the management of AL amyloidosis, the availability of this powerful agent is opening new challenges.(1)In the relapsed/refractory setting, the efficacy of single-agent daratumumab does not appear to be lower than that of daratumumab combinations. However, it is not clear whether this also applies to treatment-naïve patients in the upfront setting when response rates have the greatest impact on survival. At present, we have no data to allow abandoning bortezomib in this setting in the general population, but single-agent daratumumab can be an appealing option in subjects with contraindications to bortezomib, such as peripheral neuropathy.(2)Is maintenance with daratumumab needed in subjects who respond to daratumumab-CyBorD? In general, there are no data to support maintenance treatment in AL amyloidosis. This can be reasonable in patients who fulfil the criteria for multiple myeloma. However, unfortunately, the ANDROMEDA study was not designed to answer this question because all the patients enrolled in the daratumumab-CyBorD arm received maintenance with single-agent daratumumab.(3)How should we treat patients who relapse after upfront daratumumab? If relapse occurs at a reasonable time after daratumumab discontinuation, rechallenge with the monoclonal antibody might be an option. Belantamab mafodotin is a first-in-class, BCMA-targeted antibody-drug conjugate that showed efficacy in myeloma patients relapsed/refractory to anti-CD38 antibodies . A study(4)Another rescue therapy in the future could be represented by the applicability of chimeric antigen receptor T cell (CAR-T) immunotherapies that have shown interesting results in relapsed/refractory MM. The feasibility of this novel treatment strategy in AL amyloidosis is already under evaluation and needs further investigations ,64.While the first phase III trials have just been completed in AL amyloidosis, we are understanding that our increased knowledge and our improved ability to treat patients are disclosing new needs and asking new complex questions that will require even larger trials. New studies are needed to address these relevant questions, and collaboration between academia and pharmaceutical industries will be necessary to design future trials.


In vivo biodistribution studies in subcutaneous tumour-bearing mice similarly showed favoured accumulation of PANC-1 Exo in self-tissue (i.e. PANC-1 tumour mass) over the more vascularised melanoma (B16-F10) tumours, suggesting intrinsic tropism of PC-derived Exo for their parent cells. This study provides a simple, universal and reliable surface modification approach via click chemistry for in vitro and in vivo exosome uptake studies and can serve as a basis for a rationalised design approach for pre-clinical Exo cancer therapies.Exosomes (Exo)-based therapy holds promise for treatment of lethal pancreatic cancer (PC). Limited understanding of key factors affecting Exo uptake in PC cells restricts better design of Exo-based therapy. This work aims to study the uptake properties of different Exo by PC cells. Exo from pancreatic carcinoma, melanoma and non-cancer cell lines were isolated and characterised for yield, size, morphology and exosomal marker expression. Isolated Exo were fluorescently labelled using a novel in-house developed method based on copper-free click chemistry to enable intracellular tracking and uptake quantification in cells. Important factors influencing Exo uptake were initially predicted by Design of Experiments (DoE) approach to facilitate subsequent actual experimental investigations. Uptake of all Exo types by PC cells (PANC-1) showed time- and dose-dependence as predicted by the DoE model. PANC-1 cell-derived exosomes (PANC-1 Exo) showed significantly higher uptake in PANC-1 cells than that of other Exo types at the longest incubation time and highest Exo dose.  It. Itin vius study . It was [in vivo . CD47 extastasis . Treatmetastasis . The cliin vitro and in vivo. We have also demonstrated that DoE is a useful and reliable tool for a multivariable study design and prediction of important factors governing uptake of different exosome types by PC cells. This has enabled us to validate exosome dose and incubation time as important factors that can positively influence exosome uptake into PC cells regardless of their cell sources. We also reported the preferential in vitro uptake of self-exosomes in a PC context. This preferential uptake of self-exosomes by PC cells was also recapitulated in vivo, and that the expression of CD47 on the exosomes is crucial for the manifestation of such favoured uptake in vivo. Findings from this work would serve as the framework for future rational design of exosomes as nanocarriers for delivery of therapeutics against the different forms of PC and other cancer contexts.In this work, we have reported a novel yet simple, reliable and universal method to fluorescently label exosomes without prior engineering on parent cells for tracking and quantification of their intracellular uptake Click here for additional data file.