The detection of beneficial microbes living within perennial ryegrass seed causing no apparent defects is challenging, even with the most sensitive and conventional methods, such as DNA genotyping. Using a near-infrared hyperspectral imaging system (NIR-HSI), we were able to discriminate not only the presence of the commercial NEA12 fungal endophyte strain but perennial ryegrass cultivars of diverse seed age and batch. A total of 288 wavebands were extracted for individual seeds from hyperspectral images. The optimal pre-processing methods investigated yielded the best partial least squares discriminant analysis (PLS-DA) classification model to discriminate NEA12 and without endophyte (WE) perennial ryegrass seed with a classification accuracy of 89%. Effective wavelength (EW) selection based on GA-PLS-DA resulted in the selection of 75 wavebands yielding 88.3% discrimination accuracy using PLS-DA. For cultivar identification, the artificial neural network discriminant analysis (ANN-DA) was the best-performing classification model, resulting in >90% classification accuracy for Trojan, Alto, Rohan, Governor and Bronsyn. EW selection using GA-PLS-DA resulted in 87 wavebands, and the PLS-DA model performed the best, with no extensive compromise in performance, resulting in >89.1% accuracy. The study demonstrates the use of NIR-HSI reflectance data to discriminate, for the first time, an associated beneficial fungal endophyte and five cultivars of perennial ryegrass seed, irrespective of seed age and batch. Furthermore, the negligible effects on the classification errors using EW selection improve the capability and deployment of optimized methods for real-time analysis, such as the use of low-cost multispectral sensors for single seed analysis and automated seed sorting devices. Lolium perenne L.) is used for forage and turf in temperate regions throughout the world, including Northern Europe, the Pacific Northwest of the USA, Japan, South-Eastern Australia and New Zealand , after the establishment of the PLS-DA model. The pre-processing method utilised includes detrending, weighted least squares baseline algorithm (baseline), orthogonal signal correction (OSC) and mean centring. The baseline pre-treatment iteratively performs baseline fitting to each spectrum and determines the variables above the baseline while limiting the negative signals. Mean centring calculates the mean of each column (variable) and subtracts this from the column. It indicates the deviation from the spectral mean for each row (seed) from the original data matrix. The additional pre-treatment methods that were trialled include orthogonal signal correction (OSC), extended multiplicative scatter correction/signal correction (EMSC) and derivatives. OSC achieves the removal of excessive background by filtering from the spectral matrix X, the component that is not correlated to Y, i.e., it removes the uninformative component from the response variable Y [The calibration set was composed of 1005 samples for E+  hyperspectral imager covering the 400–700 nm range, thus having similar spectral and spatial resolutions. A classification accuracy of 94.4% of healthy and contaminated corn kernels (germ side) was also achieved based on aflatoxin threshold levels of 20 ppb and 100 ppb, respectively. Lee et al. [Senthilkumar et al.  reportede et al.  describeIdentification of effective wavelengths (EW) removes redundancy and collinearity of spectral data and allows the use of low-cost multispectral cameras in place of hyperspectral cameras. It also increases the data-processing speed and reduces the need for high-end computing infrastructure, processing power and storage. There are many variable selection methods for NIR-HSI spectral data. In this study, Genetic Algorithm (GA) was used to select optimal wavelengths, along with PLS-DA as a classifier for effective waveband selection. GA is inspired by natural evolution and natural genetics that is used to select the most effective waveband combination based on the “survival of the fittest” approach , where aThe number of wavebands used for classification was reduced to 75 from 288 using the GA-PLS-DA model . The 75 Wallays et al.  describeThese studies indicate that GA-PLS-DA is an effective technique for the selection of wavebands and reduce redundancy in hyperspectral images for the identification of various traits in small seed and grain samples. In this study, hyperspectral waveband selection could allow for the subsequent development of low-cost multispectral sensors for online measurement.The raw NIR spectral data plot of 5 perennial ryegrass cultivars—Trojan, Alto, Rohan, Governor and Bronsyn—is shown in The number of wavebands used for classification was reduced to 87 from 288 using the GA-PLS-DA model. The 87 wavelengths are the most effective wavelength combination selected using a combination of detrend, baseline, derivative, OSC and mean centre pre-processing  compared to model performance using 87 selected wavebands based on C-SVM shows that there is no extensive compromise in the overall accuracy of 89.1%.Cultivar identification performed in other seed applications has also shown 80–100% levels of calibration and prediction accuracy . A studyThe classification accuracies of previous studies are comparable to the current study for the varietal classification of seeds, indicating traditional classifiers and deep learning algorithms are effective statistical methods for discrimination. It is noteworthy that in the present study, at least 90% and 89.1% classification accuracy were achieved based on full wavelengths and effective wavelengths, respectively, of perennial ryegrass seed cultivars. The minor reduction in classification accuracy based on EW is similar to some of the previous studies described and is likely due to a reduction in collinearity between wavebands. Moreover, the elimination of effects from seed age and batch in the multivariate models developed in this study indicates the potential to identify other cultivars and associated endophytes of perennial ryegrass seed of any age and batch. The study investigated non-destructive, rapid, seed-based diagnostics of perennial ryegrass using NIR-HSI technology. E+/E− seed from five different cultivars and of varying ages was effectively discriminated. Accurate cultivar discrimination was achieved using five cultivars  of perennial ryegrass that also varied in endophyte status and age of the seed. A PLS-DA, C-SVM and ANN-DA model was developed using averaged NIR spectra for each seed, encompassing 288 discrete wavelengths using optimal pre-treatment algorithms developed on a PLS-DA model. The best discrimination accuracy for E+/E− was the PLS-DA model, which yielded an 89% overall accuracy. Effective wavelength selection using GA-PLS-DA on the NIR spectral matrix for classes E+/E− reduced wavebands to 75 and resulted in a minor compromise to the overall accuracy (88.3%) based on PLS-DA. Classification models were generated on these same spectra for cultivars . The ANN-DA model performed better than C-SVM and PLS-DA, with a 90% overall accuracy. Effective wavelength selection using GA-PLS-DA reduced the wavebands to 87, and the C-SVM model performed the best, with no extensive compromise in model performance, revealing an 89.1% overall accuracy.Thus, hyperspectral-NIR reflectance imaging is promising for the discrimination of seed with endophyte strain NEA12 from seed without endophyte as well as cultivars . The established imaging pipeline has not only the potential to be applied to other perennial ryegrass cultivars and endophytes but other pasture grass species, such as tall fescue and its associated endophytes. The limited loss of accuracies in using effective wavelengths also demonstrates practical deployment using low-cost multispectral sensors for single seed analysis.


Genome-wide association studies (GWASs) have identified numerous genetic variants associated with attention-deficit/hyperactivity disorder (ADHD), which is considered highly genetically heritable. However, because most of the variants located in the non-coding region of the human genome, the onset of ADHD requires further exploration.The risk genes involved in ADHD were identified by integrating GWAS summary data and expression quantitative trait locus (eQTL) data using summary-data-based Mendelian randomization (SMR) method. We then used a stratified linkage disequilibrium score regression (LDSR) method to estimate the contribution of ADHD-relevant tissues to its heritability to screen out disease-relevant tissues. To determine the ADHD-relevant cell types, we used an R package for expression-weighted cell type enrichment (EWCE) analysis.By integrating the brain eQTL data and ADHD GWAS data using SMR, we identified 247 genes associated with ADHD. The LDSR applied to specifically expressed genes results showed that the ADHD risk genes were mainly enriched in brain tissue, especially in the mesencephalon, visual cortex, and frontal lobe regions. Further cell-type-specific analysis suggested that ADHD risk genes were highly expressed in excitatory neurons.The study showed that the etiology of ADHD is associated with excitatory neurons in the midbrain, visual cortex, and frontal lobe regions. Attention-deficit/hyperactivity disorder (ADHD) is a commonly diagnosed neurodevelopmental disorder which is usually characterized by inattention, impulsivity, and hyperactivity. It has been reported that approximately 5% of children and 2.5% of adults in worldwide population were affected by ADHD . MoreoveCurrently, ADHD is diagnosed in clinics using the DSM-5 or ICD10. Furthermore, clinical therapeutics for ADHD usually require long-term care, and the recurrence of symptoms is common . The GWAS summary statistics data are available for download from the Psychiatric Genomics Consortium website (https://www.med.unc.edu/pgc/results-and-downloads).Attention-deficit/hyperactivity disorder genome-wide association study data were obtained from the meta-analysis by Demontis et al. , which ihttps://yanglab.westlake.edu.cn/software/smr/#DataResource), which contained cis-eQTL information using RNA-seq expression and genotype data of 2,865 brain cortex samples from 2,443 unrelated European individuals. Qi et al.  to filter out results with PHEIDI < 0.01.We applied SMR to integrate ADHD GWAS data and eQTL data to identify the ADHD risk genes. In the SMR analysis, ADHD-relevant SNPs were used as instrumental variables (IVs) to test the causal effect of the exposure (gene expression) on the outcome (ADHD) . Detailei et al.  meta-anai et al. , CMC  (All risk genes were uploaded to the Synapse Gene Ontology (SynGO) website   for furtt-statistics was first calculated for the specific expression in the target tissue during the LDSC-SEG analysis. The genes were then arranged in descending order according to the t-statistics, and those within the top 10% were defined as the tissue-specific gene set. As an additional step, a 100 kb window was added to both sides of the transcription region of the genes in the tissue-specific gene set to construct tissue-specific genome annotations. The LDSC-SEG analysis was then applied to the different annotated groups to estimate the contribution of various tissues or cells to the target phenotypic heritability. Detailed information about the theoretical principle, model hypothesis, and algorithm implementation of the LDSC-SEG analysis is provided in the original publication   method was used to identify disease-relevant tissues using gene expression data from different tissues and GWAS summary statistics . For eaclication . We downdscores) , 21. Allhttps://github.com/NathanSkene/EWCE/. PEWCE < 0.05 was considered as significant.Single-cell transcriptome expression data are used to generate a probability distribution genes list containing the average expression in a cell of interest. The gene expression level is then estimated using the target gene set to check whether it is higher than that of randomly chosen genes in the cell of interest . We usedCAMK1D, a member of the calcium/calmodulin-dependent protein kinase 1 family that is responsible for the growth of hippocampal neurons dendrites; KCTD16, a subunit of the gamma-aminobutyric acid-B receptor, which is involved in the excitability of dendrites; and CTNNB1 alongside the transcription factor LEF1/TCF, which promote the expression of genes responsible for developmental processes, such as neurogenesis and synaptic plasticity , visual cortex (P = 0.02), and frontal lobe (P = 0.02)  . This rePEWCE = 1.6 × 10−3) and excitatory neurons in deep layer 2    22). Th. ThPEWCE = 0.04)  23). Ta. TaPEWCEAttention-deficit/hyperactivity disorder is a polygenic and complex heritable disorder, whose heritability is consisted of many common variants with small effects and relatively small number of rare variants with large effects. Most common variants identified by GWAS were located in non-coding regions , 6, withIn this study, we collected ADHD GWAS data, brain eQTL data, tissue expression profile, and cortical single-cell sequencing data to identify the ADHD-associated risk genes, relevant tissues, and cell types. We screened out 336 ADHD-associated risk genes, including multiple neurodevelopment-related genes and some of these genes, like KIZ and CTNNB1, were also indicated to be related to ADHD in previous studies , 29. TheThe LDSC-SEG results for the integrated tissue expression profile and ADHD GWAS data revealed that multiple brain regions were involved in the onset ADHD. Although the results were not adjusted by multiple correction, the most significant tissues were located in the brain. Therefore, we consider our results reliable. However, because of the high similarity in expression profiles among various brain tissues, we were unable to identify specific ADHD-associated brain tissues using the current methods.Although hundreds of risk genes for ADHD have been identified using SMR analysis, identifying the specific brain regions in which these risk genes exert its function requires further exploration because of cellular heterogeneity. Previous studies have shown that, in contrast to neurological disorders, GWAS data of psychiatric disorders map primarily onto neurons, rather than glial cells , 30. Thivia the regulation of the “core genes.” According to this notion, the majority of genes identified in our study likely belong to the “core genes.” In addition, we screened out multiple ADHD-associated risk genes that were also involved in neurodevelopment, which demonstrated that ADHD is a neurodevelopmental disorder  can be found in the article/W-QW and HS designed the study and drafted the manuscript. Y-JC, X-WL, and RZ analyzed the data. YL and X-WL revised the manuscript and provided expert consultation on the design of the study. All authors critically reviewed the manuscript and approved of it in its final form.This research was supported by Wuhan Municipal Health Research Fund (WG17M01 to YL).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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The interactome networks provide an insight into the mechanisms of cell functions under physiological and pathological conditions, which are critical for the discovery/development of the molecular targets for diagnostics or therapeutic applications  interactions. Throughout the past 2 decades, scientists have been trying to build up entire interactome networks of protein–protein interactions in different cells. It has been reported that a human cell may contain ∼130,000 binary interactions between proteins . There aications .For this second volume of this Research Topic, we have selected a series of articles that highlight technological advances for studying interactome. We hope these articles will provide useful information and protocols will be beneficial in facilitating the development of this important field.Hassan et al. report on the synthesis and molecular docking analysis of novel heterocyclic-scaffold-based indole moiety as antimicrobial agents.Molecular docking has been used in the characterization of interactions between proteins and biomacromolecules to determine the selectivity and binding affinity. As we know, protein–protein docking is one of the pivotal tools in computational biology, and with the development of computation technology , docking analysis offers valuable information for fundamental studies of molecular interactions and provides a structural basis for drug design. In this Research Topic, A biomarker refers to a biomolecule found in bodily fluids, cells, or tissues that indicates a normal or abnormal disease condition. Biomarker discovery is critical to the development of clinical diagnostics and therapeutics. Interactome-based biomarker discovery can be achieved by Mass Spectrometry, NMR, SPR, and bioinformatics analysis.Ding et al. report on nine genes that act as novel prognostic biomarkers based on integrated bioinformatics analyses of single-cell and bulk transcriptome data. Xian et al. discuss the development of a sensitive method of identifying specific marker peptides using liquid chromatography-tandem mass spectrometry with multiple reaction monitoring (LC-MS/MS-MRM) analysis.Two articles in this special Research Topic examine biomarker discovery. In their study, Eden et al. describes a novel approach to AD drug discovery by covalent fragment inhibition on intramembrane proteolysis. Zhou et al. report on the interaction between heparin and amyloid-beta peptide using heparin tetrasaccharides.Neurodegenerative diseases, such as Alzheimer’s disease (AD), Parkinson’s disease (PD), and Huntington’s disease (HD) are serious dementia disorders. Interactome mapping offers a network of neurodegenerative-disease-related proteins, as Gelbach et al. presents a detailed kinetic and structural analysis of the interactions of different SARS-CoV-2 S-protein RBDs with heparin, information that should be useful in anti-COVID-19 research.The COVID-19 pandemic is not over and will likely persist into the foreseeable future. Numerous mutations of SARS-CoV-2 have been identified, including Alpha, Beta, Gamma, Delta, and Omicron variants, with increased infectivity, immune evasion, and reinfection. Surface plasmon resonance (SPR) has been used in COVID-19-related basic studies and drug and vaccine development. The study by Chen et al. reported a novel competitive biolayer interferometry (BLI) method to measure the binding affinity between heparin and PF4, which provided a deeper understanding of the heparin-PF4 interaction and a useful protocol for quality control in the production of heparin-related therapeutics.Heparin-induced thrombocytopenia (HIT) is a heparin-related immune complication in heparin clinical applications. It is caused by antibodies directed to a complex of heparin and platelet factor 4 (PF4).


Phagocytosis is crucial in tumor surveillance and immune function. The association between phagocytosis and the outcomes of breast cancer patients has not been well-determined. In this study, data were downloaded from the cancer genome atlas (TCGA) and gene expression omnibus (GEO) databases to investigate the role of phagocytosis in breast cancer. Data from the TCGA and GEO databases were used to investigate the prognostic role of phagocytosis in breast cancer. Then, we performed pathway enrichment analysis, copy number variation (CNV) and single-nucleotide variant (SNV) analyses, immune infiltration analysis, calculation of tumor purity, stromal score, and immune score, and consistent clustering. We also constructed a phagocytosis-regulators-based signature system to examine its association in survival and drug response. The genomic and expression differences in the phagocytosis regulators in breast cancer were systematically analyzed, explaining the widespread dysregulation of phagocytosis regulators. Using the investigated association of phagocytosis regulators with the prognosis and tumor immune environment, we constructed a prognostic model based on phagocytosis regulators. We discovered that patients with high risk scores had a poor prognosis and were negatively associated with immune functions. The model had preferential predictive performance and significantly consistent drug-resistance prediction results. Our findings suggest that the phagocytosis-factors-based scoring system can be used as a novel prognostic factor, serving as a powerful reference tool for predicting prognosis and developing methods against drug resistance. In the past ten years, the research on the heterogeneity of breast cancer has made great progress, and a series of treatment methods has been proposed for breast cancer with different molecular phenotypes .The clasAt the same time, the emergence of immunotherapy, especially immune checkpoint inhibitors, has provided a new way of thinking for treating solid tumors . AlthougThe phagocytosis of macrophages is an important part of the immune regulation of the immune system, and the severe dysfunction of macrophages also participates in the occurrence and development of tumors. Here, by analyzing the phagocytosis regulators of phagocytes, we constructed a signature that can predict patient prognosis and immunotherapy efficacy, and we used unsupervised machine learning methods to verify the accuracy and application value of this signature.The process of this study is presented in Here, we extracted 29 phagocytosis factors from two articles of PMID: 34497417 and PMID: 30397336 [p-value <0.001 , and C TLA-4 and proinflammatory factors, interleukin-1 alpha , IL-1 β, IL-6, IL-8/CXCL8, and IL-18, we explored the high and low expression of genes included in the signature based on the high and low groups of signatures. We also analyzed the differences in the expression of immune checkpoints C and thep < 0.0001).Furthermore, in clear cell renal cell carcinoma (PMID32472114) , we analBased on the mutation data of TCGA-BRCA, we analyzed the mutation differences in the high- and low-risk score groups. We observed that the mutation rate of the TP53 gene was significantly higher in the high-risk group than in the low-risk group . After ap for drugs < 0.05, we finally identified 27 drugs associated with THE risk score. Notably, none of the drugs showed a negative correlation between IC50 and risk score, suggesting that risk scores have consistent universality in predicting chemotherapeutic drug resistance  . Among tThis project involved two parts: a training set and a validation set. The training set included the TCGA-BRCA dataset, and the validation set contained data from four GEO datasets: GSE20685, GSE21653, GSE25066, and GSE96058. In addition, the immunotherapy dataset EGAS00001004353 was prepared for later analysis.https://portal.gdc.cancer.gov/ (accessed on 16 March 2022). Log2 (TPM + 1) was used for all analyses involving TCGA transcript data. GEO data were downloaded from https://www.ncbi.nlm.nih.gov/geo/ (accessed on 16 March 2022) [sub.ega-archive.org/datasets/ (accessed on 16 March 2022) [We used the TCGA-BRCA dataset to collect transcriptomic, mutational, copy number variation, and informative clinical data. The data source was Xena , and thech 2022) . Datasetch 2022) .The data are summarized in Pathway enrichment analysis was performed using the R package clusterProfiler , and ssGSNV analysis was performed based on the R package maftools package . The mutCNV was performed using Gistic2 . The speSamples were subjected to immune infiltration analysis using the R packages C IBERSORT , QuantisTumor purity, stromal score, and immune score were calculated using the R package estimate . Here, wHub-based mRNA consensus clustering of tumor samples in the TCGA-BRCA dataset was performed using the consensusClusterPlus package . For thep < 0.05. Genes with coefficients not equal to 0 were screened and included in the final model. We defined the risk score as the sum of the product of the lasso coefficient and the gene expression level.We used the cv.glmnet function of the glmnet package  to perfohttps://CRAN.R-project.org/package=survminer (accessed on 16 March 2022)). Analysis was performed using default parameters. AUC was analyzed using the R package timeROC (https://CRAN.R-project.org/package=timeROC (accessed on 16 March 2022)).KM survival analysis and plotting were performed using the R packages survival and ggsurvplot ).We downloaded the drug sensitivity data for approximately 1000 cancer cell lines from Genomics of Cancer Drug Sensitivity (GDSC) (cancerrxgene.org). Taking the antitumor drug IC50 in cancer cell lines as the drug response index, we used Spearman correlation analysis to calculate the correlation between drug sensitivity and the risk score and considered the absolute value of Rs > 0.2 and PCA analysis was performed using the R built-in function prcomp.https://CRAN.R-project.org/package=circlize (accessed on 16 March 2022)). Sankey diagrams were drawn using the R package ggalluvial. Nomograms were made using the R package nomogram [Circus diagrams were drawn using the R package circlize .The Wilcoxon test was used for comparison between groups. The validity of the model was verified with the receiver operating characteristic (ROC) curve. We divided the samples by the median risk score. Survival curves were drawn using the Kaplan–Meier method for predictive analysis, and the log-rank test was used to determine the significance of differences. To assess whether the risk score was an independent predictor, we performed a multivariate cox regression model analysis with age, sex, and stage as variables. Correlation analysis was performed using Spearman or Pearson correlation. All statistical analyses were two-sided, and In conclusion, in our study, we constructed a meaningful signature based on the macrophage phagocytic factor genes for breast cancer patients, which showed significant value in predicting the OS of breast cancer patients. These results indicate the need for future research on and immune-therapy-based interventions for breast cancer patients.


Immunotherapy has redefined the treatment of cancer patients and it is constantly generating new advances and approaches. Among the multiple options of immunotherapy, bispecific antibodies (bsAbs) represent a novel thoughtful approach. These drugs integrate the action of the immune system in a strategy to redirect the activation of innate and adaptive immunity toward specific antigens and specific tumor locations. Here we discussed some basic aspects of the design and function of bsAbs, their main challenges and the state-of-the-art of these molecules in the treatment of hematological and solid malignancies and future perspectives. Regardless of efforts from the scientific community, options to treat cancer patients in advanced stages achieving complete response with low recurrence are limited. For that reason, the search of effective alternatives to treat cancer has increase in the last years. Currently, some alternatives that are effective in the treatment of other conditions are now being studied as an alternative to treat cancer patients. Monoclonal antibodies are known to have a positive impact on many conditions such as autoimmune disorders, cardiovascular, pulmonary, and even infectious diseases . Even thThe first application of bsAbs in cancer immunotherapy was focused on leading T cells toward tumor cells by the interaction between the extracellular subunit of CD3 on T cells and cancer-related antigens. The bsAbs ease the interaction of the major histocompatibility complex (MHC) with its cognate T-cell receptor (TCR) resulting in a proper T-cell priming and activation. Despite this, some adverse effects of these drugs such as cytokine release syndrome or liver toxicity and other limitations such as a short half-life have been reported. For that matter a vast quantity of clinical trials with these molecules is being conducted .Nevertheless, bsAbs still represent a novel and effective approach to treat cancer patients because they target molecules expressed on the surface of cancer cells (tumor-associated antigens [TAAs]) and bind to specific receptors that are located on effector cells of the immune system  5,6]. F,6. F5,6]Currently, an important number of bsAbs are being studied in many clinical trials, showing positive results in a specific group of tumoral cells and a prolonged antitumoral response. Particularly, some malignancies such as lymphomas seem to have a better antitumoral response with bsAbs, in comparison with myeloid neoplasias or solid tumors . For solDespite the breakthrough that these bsAbs are represented in the field of cancer immunotherapy, there are still many questions to be answered and challenges to be solved about the safety, efficacy, and range of possible treatable tumors. Here, we review some basic aspects of the bsAbs and their functions, along with their common use in the current clinical practice.Antibodies are molecules made of different structural and functional parts. These parts are combined to create molecules with unique affinity, specificity, and interaction properties. The special structure-function of these macromolecules is beyond the scope of this review; however, understanding some basic principles is essential to comprehend the pharmacology behind bsAbs .From a structural point of view, a bsAbs is made of two identical light chains (LCs) and two identical heavy chains (HCs). Each domain, between the LC and HC has disulfide bonds. The structural conformation creates three zones: two antigen-binding fragments (Fab) and one crystallizable fragment or Fc. Both Fab regions bind to molecular targets, the same epitope. On the other hand, the Fc region attaches to receptors such as Fcγ receptors (FcγRs), C1q, and neonatal Fc receptor (FcRn), mediating its effector functions ,11.Previously, it was mentioned that although bsAbs contain two Fab regions, these only bind to the same epitope in an antigen, defining monospecificity. As the name suggests, bsAbs are bispecific, because they bind to two antigens. Structurally, there are two principal types of bsAbs: (1) single-chain variable fragment (scFv) antibodies and (2) full-length IgG-based antibody. In the past time, three techniques were used for their creation bispecific T-cell engager (BiTE), dual-affinity retargeting proteins (DARTs) and tandem diabodies (TandAbs) . CurrentMechanisms of action are diverse. First, the process of binding immune cells with tumor cells, leads to suppression of malignant cells’ ability to escape the immune response. Second, bsAbs decrease the expression of certain molecules and the release of immune suppression mediators. Additionally, bsAbs also block targets such as PD1, CTLA-4, LAG-3, IL-23, TNF-a, and others and they also stimulate immune cells, those mechanisms act synergistically ,14.From a pharmacokinetic (PK) view the properties of bsAbs oscillate due to their different compositions. The Fc region plays a key role in bsAbs PK. It is reported that bioavailability is lower by oral administration, so other ways of administration are better choices.With respect of the distribution, three parameters affect this variable: extravasation, distribution within a tissue, and elimination/clearance. Extravasation occurs when macromolecules have a high volume of distribution (Vd) and tend to remain in the tissues. Additionally, it is known that intracellular catabolism and renal clearance, both influenced by Fc region, increase the molecular weight of some molecules leading to slow clearance. After that, those molecules bind to FcRn, escape acidic endosomes, and return to the circulation or to the interstitial space. In the case of specific elimination, bsAbs bind to specific antigens on cell surfaces mediating its clearance in a process named target-mediated drug disposition (TMDD). In an attempt to integrate some of the previous concepts, scFvs vs. full-length IgG-based bsAbs have different molecular weights; this distinction determines the route of clearance and the time in circulation and route of administration ,16.BsAbs pharmacology is complicated, many situations and variables affect its pharmacodynamics and pharmacokinetics. Understanding the design, development, and properties of these molecules is fundamental for the development of new molecules .Among all the antibody-centered cancer therapy, T-cell engaging bispecific antibodies (T-biAbs) have a promising role in future cancer therapeutics. These antibodies use the main principle of two different binding arms of the bispecific antibodies. One of the binding sites recognizes the invariable CD3 subunits of cytotoxic T lymphocytes (CTLs) and the other one recognizes certain tumor antigens. Therefore, the T-biAb can activate CTLs bypassing the MHC pathway and redirecting this activation to attack specific cancer cells . CurrentIn 1989 Gross and Eshhar et al. were the first ones to approach the concept of T-cell reactivation against tumor cells. At that time, they combined monoclonal antibodies and T-cell receptors to promote immune activation . HoweverFor a better understanding of the T-biAbs mechanism of action on immune effector cells, it is important to have in mind the usual adaptive immune response. T-cell activation depends on the linkage between the T-cell receptor (TCR)/CD3 complex and the major histocompatibility complex (MHC)/peptide complex and on the interaction of co-stimulatory receptors and their ligands . In contFurthermore, some studies reported that T-bsAb increased T-cell proliferation in the tumor and recruitment from the periphery to tumor tissues, leading to a significant amount of tumor-infiltrating T cells after treatment ,27,28. IIt is important to highlight that our understanding of the exact mechanism of the activity of effector T cells engaged by T-bsAbs is still insufficient. For example, it is not fully understood if the presence of preexisting T cells inside the tumor is necessary for peripheral T-cells recruitment by T-bsAbs .As previously mentioned, bispecific antibodies are an intelligent strategy to put close IECs and their intended target cell. Antitumor effects can be provided directly or indirectly by innate or adaptive immune cells. Immune effector cells comprise an arsenal of supportive and cytotoxic cells that can arrest a threat from its beginning, clearing out infections or cells with early malignant properties, or at least slowing down the process while the adaptive immune system is appropriately recruited .Effector mechanisms of the innate immune system can be enhanced by using biAbs . Most daIn vitro experiments have shown that trifunctional biAbs were effective in inducing specific cytotoxicity of melanoma cells, with proper T-cell priming measured by the upregulation of CD69 and downregulation of CD62L (naïve T-cell marker). The rationale of trifunctional biAbs is to preserve the Fc region in the antibody structure . When thOn the other hand, in the in vivo setting, biAbs with preserved Fc regions have shown to be counterproductive, as FcγR is also expressed by other innate immune system cells such as macrophages and NK cells, inducing overactivation of the immune system with further severe adverse events such as cytokine release syndrome (CRS) . MoreoveNK cells have also been addressed in biAbs research. NKs are highly cytotoxic, less prone to exhaustion, and do not require binding to an MHC-Epitope complex. The standard effector mechanism exploited in monoclonal antibody therapy for cancer is antibody-dependent cellular cytotoxicity (ADCC). This exact mechanism has been shown to be critical in using biAbs, even in the absence of an Fc domain. NK cells are one of the most efficient IECs in surveying and executing tumor cell cytotoxicity. Engaging NK cells to malignant cells has been proven to be effective in reducing tumor size in animal models at a greater extent than regular mAb therapy . NaturalNovel approaches with NK cells include engagers targeting CD16, especially the CD16A isoform (FcγRIIIA). Currently, most NK cell engagers are directed against antigens expressed in hematological malignancies , a trend that is also seen in other immunotherapies such as CAR-T cells and CAR-NK cells ,39,40,41Antitumor immunity is one the main mechanisms of cancer control under micro-homeostatic conditions. A wide array of cells, signaling peptides, and membrane-bound proteins are involved in the building machinery of surveillance for malignancy in healthy cells. CD8+ T cells and NK cells are the main orchestrators of this mechanism. Nevertheless, evolutionary events inside potentially malignant cells can induce transcriptomic regulatory mechanisms that might allow them to evade immune surveillance ,43.Some of these regulatory pathways include molecules such as CD80/86 and PD-L1, which respectively bind to CTLA-4 and PD1, two of the primary immune checkpoints. When attached to their receptors, these molecules can induce a switch off in T cells, making them dormant and further modifying the tumor microenvironment (TME), creating the perfect place for continued growth and progression. By restoring and enhancing these dormant cells, dramatic treatment responses can be achieved. These have been shown in the past decade with the introduction of multiple mAbs immune checkpoint inhibitors that target PD1, PD-L1, and CTLA-4 . ImportaThe tumor microenvironment also induces important changes in other tumor-infiltrating cells, including macrophages, DCs, myeloid-derived suppressor cells, and plasma cells. From these cells, DCs are particularly important. It has been shown that reactivating DCs inside the tumor can restore CD8+ T-cell function and induce other anticancer changes in the TME .Approaching immune restoration using biAbs is a relatively new field; most literature is recent and experimental, with promising results potentially translational into the clinic. Liu et al. performed an animal in vivo study using a biAb directed against CD3e (T-cells), and PD-L1. Analysis of their data showed that dramatic responses obtained in multiple syngeneic tumor models were due to restoring CD8+ T-cell activity when bsAbs were targeting PD-L1 in the membrane of DCs, inhibiting negative regulation and enhancing the stimulation via cytokines and co-stimulatory molecules. These data are intriguing as no tumor-specific antibody was used, but instead, a “generalist” approach of immune checkpoint blockade was done .A similar approach was used by Kraman et al., using a biAb directed against LAG3 and PD-L1. LAG3 is another critical immune checkpoint and maker of T-cell exhaustion. Results showed high antitumoral activity in murine syngeneic models . Cui et Currently, T-biAbs are used as immunotherapy in cancer treatment. There are two approved delivery strategies for T-biAbs-based therapies: delivery of Y-biAbs as recombinant proteins or in vivo production.T-biAbs as recombinant proteins are composed of two linked antibody-binding regions that simultaneously recognize two antigens . One of In this delivery strategy, recombinant proteins with a short circulatory half-life (T-biAbs in tandem single-chain variable fragment recombinant format) and long circulatory half-life (T-biAbs with Fc domain format) are administered as continuous intravenous (IV) infusion or as repeated high- dose bolus injections respectively .On this topic, it is worth highlighting that some limitations to this type of delivery have been reported. First of all, the high cost of therapy, is derived from the production process and the usually long treatment. Furthermore, it the difficulty to achieve sustained plasma levels, high enough to be effective and low enough to be not toxic . MoreoveTo seek the balance between efficacy and safety, in vivo gene therapy was developed. It is known that modified oncolytic viruses eliminate tumor cells and stimulate systemic immune response without harming healthy cells and tissues . It is kThe mechanism of action of the latter delivery system has shown advantages over the former. One of the advantages is that it is a cheaper alternative because it obviates the need for manufacturing and administering purified T-biAbs. Additionally, in some cases the in vivo production maintains an effective antibody concentration, so no concerns about long-term storage and rapid renal clearance arise ,61.There is solid and growing evidence about the use of T-biAbs in hematologic malignancies. This is possible because most hematologic neoplasms fulfill two important features for an effective biAbs therapy. The first one is that antigens from hematologic malignancies are mainly (or only) expressed on malignant cells, leading to a reduction of on-target/off cancer toxicity. The second one is that the antigen is strongly associated with the malignant phenotype, leading to a reduction of antigen loss variants .According to the anterior principle, the approach of T-biAbs focuses on targeting CD3 on T cells (CD3ε fragment) and an antigen commonly expressed in tumor cells. For example, for B-cell malignancies, some T-BiAbs target CD19 and CD20. CD19 persists the entire course of the B-cell development. This overexpressed target allows the lysis of malignant cells and avoids the attack of the normal lymphocytes .The most remarkable drug of this kind is blinatumomab. This antibody is made of two scFv combined in one protein chain . The hisBesides the patients’ positive outcomes under blinatumomab treatment, some concerns related to the main adverse effects (AE) are still present. Among the most dangerous AE, neurological affections are the most common cause of interruption of the drug. Neurotoxicity symptoms include headache, tremor, confusion, disorientation, and other more life-threatening symptoms such as seizures or stupor. Other significant AEs include CRS, produced because of T cell and macrophages activation, and infectious and hematologic toxicity ,69. In aHowever, many other hematologic neoplasms could benefit from this kind of immunotherapy. Once again, by targeting a common antigen on the tumor cell’s surface, the therapeutic effort focuses on malignant cells with little or no on-target off-tumor toxicity. For example, for acute myeloid leukemia (AML), CD123 is one of the over-expressed antigens targeted by novel drugs such as flotetuzumab (MGD006) or vibecotamab (XmAb1405) with positive results in phase I/II and phase I studies respectively ,71. TherFor other neoplasms as multiple myeloma (MM), some possible targets for immunotherapy include B-cell maturation antigen (BCMA), G protein-coupled resector 5D (GPR5D), CD38, and Fc receptor-like 5 (FCRL5) . Anti-BCAs it was mentioned earlier, since the approval of blinatumomab in 2014, T-biAbs have become an essential section in the investigation of hematologic malignancies. However, it is not the case for solid malignancies. There are some challenges in developing T-biAbs for solid tumors, one of them the hypoxia-induced immunosuppression in the tumor microenvironment, as a successful T-biAb depends on activation of CTL targeting CD3 .Nevertheless, a large number of molecules that target antigens expressed on solid tumor malignant cells are under investigation see . TargetsEpCAM is a conserved type I transmembrane protein, and it is highly expressed in some malignancies, lung cancer included . MoleculIn regards to GPC3, a heparan-sulfate proteoglycan expressed over the 65% of hepatocellular carcinoma and related to poor prognosis , is an iAmong other redirecting T-cell activation therapies against cancer cells, chimeric antigen receptors (CAR) expressed by T cells (CAR-T) represent a revolution in immunotherapy. The approval of tisagenlecleucel (tisa-cel) and axicabtagene ciloleucel (axi-cel) in 2017 by FDA marked a turning point in cancer treatment . These cCAR-Ts put together two of the three necessary signals to T-cell priming, the TCR/CD3 signals, and the costimulatory receptors/mediators. This allows the cell to recognize user-defined cell surface tumor-associated antigens. However, similar to other immune therapies, CAR-T cells have some AEs. Among them we can mention the off-target toxicity , tumor lysis syndrome, and CRS.A novel strategy called CAR-T switches has been developed to avoid these undesirable side effects that could be quite harmful. These switches focus on recruiting and activation of immune cells by a bispecific adapter protein. The adaptor, conformed as a monoclonal antibody, can target the tumor antigen and activate the dormant CAR-T with a protein located in one of its N- or C-terminal region .These switches allow control of the CAR-T cells, improve their specificity, and avoid unpredictable reactivity. There are three perspectives to switch design: suicide, endogenous, and exogenous switches. The suicide switches are molecules exposed to CAR-T cells; they are activated by administering an external drug or molecular mediator . The endogenous switches comprehend molecular strategies of the immune synapsis such as target-antigen recognition or expression of immune regulation singles such as PD-1 or CTL-4 (i.e SynNotch switches). The exogenous switches include antibodies or derived proteins with multiple binding sites that could lead to a more specific union of the CRA-T cell with its target .BiTAbs have been demonstrated to be a groundbreaking alternative in immune therapy and a vanguard option that combines the engineering of molecular biology and the biological activity of the immune system. These drugs represent a more individual and specific treatment for cancer patients providing a “personalized” attack on malignant cells. However, there is still a lot of information to be elucidated in relation to this kind of immunotherapy. The complexity of the pharmacokinetics and pharmacodynamics of these drugs represents a change for future application. Finally, the possible adverse effects related to the nature of its mechanism of action should be addressed in incoming studies. Nevertheless, the evidence is promising and growing, and maybe these pharmacological agents represent the next and safer generation for cancer treatment.


Hereditary amyloidogenic transthyretin (ATTRv) amyloidosis is a rare autosomal dominantly inherited disorder caused by mutations in the transthyretin (TTR) gene. The pathogenetic model of ATTRv amyloidosis indicates that amyloidogenic, usually missense, mutations destabilize the native TTR favouring the dissociation of the tetramer into partially unfolded species that self-assemble into amyloid fibrils. Amyloid deposits and monomer-oligomer toxicity are the basis of multisystemic ATTRv clinical involvement. Peripheral nervous system (autonomic and somatic) and heart are the most affected sites. In the last decades, a better knowledge of pathomechanisms underlying the disease led to develop novel and promising drugs that are rapidly changing the natural history of ATTRv amyloidosis. Thus, clinicians face the challenge of timely diagnosis for addressing patients to appropriate treatment. As well, the progressive nature of ATTRv raises the issue of presymptomatic testing and risk management of carriers. The main aim of this review was to focus on what we know about ATTRv so far, from pathogenesis to clinical manifestations, diagnosis and hence patient’s monitoring and treatment, and from presymptomatic testing to management of carriers. Hereditary amyloidogenic transthyretin  amyloidosis is caused by mutations in the transthyretin (TTR) gene and is an autosomal dominantly inherited, debilitating, progressive and, if left untreated, fatal multisystem disorder. Prevalence of the disease is highly variable between the endemic and non-endemic countries and the global prevalence was estimated to be 10,186 persons  [The main aim of this review is to provide an overview on ATTRv amyloidosis from pathogenesis to clinical manifestations, diagnosis and hence patient’s monitoring and treatment and from presymptomatic testing to management of carriers.TTR is a homotetrameric protein with a backup carrier role of thyroxine (T4) in the plasma and cerebrospinal fluid, and by associating with the retinol-binding protein, it also mediates the transport of vitamin A. It is encoded by a small gene (chromosome 18q12.1) comprising only four exons. The monomers, formed after the cleavage of a 20 amino acid signal peptide, are composed of 127 amino acids arranged in eight antiparallel β-sheets; traditionally, the amino acid numbering refers to the mature protein. The homotetramer contains two T4-binding sites and binding of T4 contributes to its structural stability. Mutant and wild-type TTR may give rise in various tissues and organs to extracellular amyloid deposits formed by bundles of β-sheet fibrillar protein identified by apple-green birefringence under a polarized light microscope, after staining with Congo red, and by rigid unbranched fibrils 10–12 nm in diameter on electron microscopy [TTR amyloidosis is a conformational disease and the pathologic protein aggregation is largely due to reduced folding stability. The pathogenetic model of ATTRv amyloidosis indicates that amyloidogenic, usually missense, mutations destabilize the native TTR favouring the dissociation of the tetramer into partially unfolded species that self-assemble into amyloid fibrils. The amyloidogenic potential of TTR variants correlates inversely with their thermodynamic stability.Among over 130 mutations identified, the vast majority are pathogenic; a minority non-amyloidogenic, exceptional variants are protective in compound heterozygosity with pathogenic mutations.Small molecule drugs such as tafamidis act as TTR stabilizers binding to unoccupied T4-binding sites. In ATTRv, amyloid deposits occur prevalently in the somatic and autonomic peripheral nervous system (PNS) and heart, though they may also involve kidneys, eyes, leptomeningeal vessels, joints and ligaments. This tissue specificity is elusive; endogenous factors such as glycosaminoglycans or the chemico-physical milieu might promote the amyloid deposition . Due to The heterogeneity of the amyloidogenic pathways may explain the distinct biochemical composition of amyloid fibrils which are formed by C-terminal fragments (type A fibrils) in ATTRwt and in the majority of late-onset ATTRv and by full-length monomers (type B fibrils) in the early-onset V30M ATTRv amyloidosis. Such different compositions contribute to genotypic-phenotypic correlations and impact the sensitiveness of diagnostic procedures such as staining of the tissue biopsy by Congo red, which has a higher affinity for type B fibrils, or non-invasive techniques for amyloid imaging .Amyloid fibrils may cause tissue damage by direct compression or obstruction as it is obvious for carpal tunnel syndrome, vitreous opacities and spinal canal stenosis. The PNS involvement is more likely caused by the neurotoxicity exerted by non-fibrillar oligomers and protofibrils . DiffusiIn ATTRv amyloidosis, the polyneuropathy has a length-dependent axonal pattern and affects variably both the large and small myelinated as well non-myelinated small fibres. In bioptic specimens, amyloid deposits predominate in the endoneurial blood vessels; deposits and axonal loss have an asymmetric distribution between and within the fascicles. Ultrastructural changes of the endothelial indicate a microangiopathy with a disruption of the blood-nerve barrier which may allow the entry of circulating TTR into the endoneurial space . In the From pathology to symptomsAmyloid deposits and monomers/oligomers toxicity are the basis of ATTRv clinical presentation. PNS (somatic and autonomic) and heart are the most affected sites. Therefore, peripheral sensory-motor neuropathy, dysautonomia and cardiomyopathy, often in combination, are the common phenotypes .Clinical heterogeneity is only partly explained by genetic mutation differences. The most frequent mutation worldwide, V30M, has either early-onset  or late-onset , for still unknown reasons –10.Early-onset V30M ATTRv is characterized by a small-fibre neuropathy with neuropathic pain, other positive sensory symptoms, algo-thermal sensory loss at distal limbs; only later touch and deep sensory loss and motor involvement become evident, with a length-dependent distal-to-proximal progression . AutonomLate-onset V30M ATTRv has a different clinical picture: the neuropathy affects small and large fibres since the beginning, with sensory loss to all modalities, early muscle wasting and weakness starting from distal sites , 10. AutThe disease course, lethal if left untreated after a mean of 7–10 years, is more rapid in the late-onset variety . The difE89Q, F64L) are also frequent, sharing similarities with the late-onset V30M type, including onset age. T49A and E89Q show fast progression; F64L is relatively less rapid; I68L is predominantly cardiopathic [In non-endemic countries, including Italy, there are many other mutations, some e.g. E8Q, F64L aiopathic .Several patients show clinical and/or electrophysiological features of bilateral carpal tunnel syndrome, related to amyloid deposits in the transverse carpal ligament, sometimes preceding by years polyneuropathy onset . Less coNephropathy rarely occurs with proteinuria, renal failure, recurrent urinary infections . Ocular PNS involvement is the presenting complaint in most cases of ATTRv. The main challenge for clinicians in evaluating a neuropathic patient is when to suspect ATTRv in order to catch early the diagnosis. In regions where ATTRv amyloidosis is non-endemic, diagnosis can be delayed by 3–4 years . The impOverall, ATTRv neuropathy is a progressive length-dependent axonal polyneuropathy involving small (sensory and autonomic) and large (sensory and motor) nerve fibres , 22.A preferential and early involvement of small fibres is typical of early-onset V30M ATTRv phenotype . The iniOn the other side, in late-onset ATTRv phenotypes (V30M and most of non-V30M), pathological evidence demonstrates early involvement of all types of nerve fibres even though the impairment of the largest fibres usually overcomes the smallest ones , 22.Therefore, clinicians may face a first scenario including a neuropathic patient complaining of dysautonomia. In such a case, though alternative diagnosis may be considered, genetic testing for ATTRv amyloidosis should not be delayed , 23, 24.Another scenario, more challenging for clinicians and more common in non-endemic areas, includes sporadic patients with late-onset phenotype that present with a sensory or sensory-motor length-dependent axonal polyneuropathy.In such a case, electrophysiological features may be similar to several other neuropathies including those dysmetabolic (e.g. diabetes mellitus), toxic, nutritional, paraneoplastic, infectious or late-onset Charcot-Marie-Tooth disease. Laboratory screening test for peripheral neuropathy is needed even though comorbidities as diabetes may coexist with ATTRv amyloidosis , 26.The most striking feature of ATTRv neuropathy in differential diagnosis is its progressive course. On average, patients with early-onset form switch from FAP-1 to FAP-2 stage of disease in 5.6 years and from FAP-2 to FAP-3 in 4.8 years. In patients with late-onset form, the progression is even faster and requires 2–4 years for switching from FAP-1 to FAP-2 and 2–3 years from FAP-2 to FAP-3 , 28.This is also important in differential diagnosis from chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) that represents the most common misdiagnosis –32. ThisTherefore, ATTRv patients, usually in more advanced stage of disease, may be mistaken for CIDP, but a careful reading of electrophysiological findings reveals that slow nerve conduction velocity is associated with axonal loss and accordingly with a severe reduction of compound muscle action potential amplitudes –32. Unre99mTc-DPD, 99mTc-HMDP, or 99mTc-PYP [Phe64Leu) should be considered [Another challenging misdiagnosis encompasses paraproteinemic neuropathies, i.e. amyloid light-chain (AL) amyloidosis and POEMS syndrome , 38, tha9mTc-PYP  may be unsidered . On the nsidered .Once the diagnosis of ATTRv amyloidosis has been reached, additional investigations are required to evaluate the extent and severity of organ involvement.To monitor the polyneuropathy disability, useful tools in clinical practice include the FAP staging system and the polyneuropathy disability (PND) score . HoweverAlnylam and the mNIS + 7Ionis, specifically designed to assess disease impairment and progression in hATTR amyloidosis clinical trials, better quantify sensory abnormalities over the whole body, nerve conduction abnormalities and autonomic function [In a trial published in 2013, the NIS + 7, which combines clinical assessment with seven electrophysiological tests, was used to better characterize and quantify neuropathic impairment . In recefunction .Other useful clinical scales include the Composite Autonomic Symptom Scale-31 (COMPASS-31) questionnaire and the Compound Autonomic Dysfunction Test (CADT) questionnaire for assessment of autonomic symptoms; the Rasch-built Overall Disability Scale (R-ODS) survey for evaluation of activities of daily living; Charcot-Marie-Tooth Neuropathy scale (CMTNS) and its clinical component CMT Examination Score (CMTES) for monitoring neuropathy progression; the Norfolk Quality of Life-Diabetic Neuropathy (QoL-DN) questionnaire to estimate quality of life; the 6-min walking test, the 10-m walking test and handgrip strength test (dynamometer) to assess specific motor function –45.Traditional nerve conduction studies are performed to monitor the evolution and the severity of a peripheral neuropathy . Even ifCardiac investigations in ATTRv amyloidosis are mainly aimed at detecting a possible infiltrative (hypertrophic) cardiomyopathy and, above all, any potential serious conduction disorders that may require the implantation of a prophylactic pacemaker to decrease the risk of sudden death. Useful investigations for cardiac assessment include echocardiogram, 24-h Holter monitoring and echocardiography with strain imaging; cardiac magnetic resonance imaging (MRI) and intracardiac electrophysiological studies, even if not always available, are useful when necessary .Cardiac serum biomarkers, specifically brain natriuretic peptide (BNP) or its N-terminal prohormone (NT-proBNP) and cardiac troponins (T or I), are useful and have a prognostic value in amyloid cardiomyopathy . NT-proBOnce the genetic diagnosis is confirmed, an ophthalmological assessment should be carried out as well. When ocular manifestations are present, the frequency of ophthalmological evaluations varies depending on severity of eye involvement and should include measurement of visual acuity and of intraocular pressure, Schirmer test, ocular fundus and slit-lamp examination .Renal evaluation is also crucial, and usually based on measurement of serum creatinine, proteinuria and microalbuminuria, and on the estimated glomerular filtration rate (eGFR) .Finally, a modified version of the body mass index (mBMI) that corrects for the effect of hypoalbuminaemia provides a marker of nutritional status, which is, to some extent, influenced by the duration and severity of gastrointestinal symptoms and malabsorption in hATTR patients .Protocols for pre-symptomatic genetic testing (PST) of late-onset inherited disorders are available since many years, including that for genetic testing and management of individuals at risk for ATTRv –54.The main purpose of all these protocols is to provide with participants a multidisciplinary team and whole information to protect them against psychosocial consequences of the test results. All PST protocols aim to combine the respect for the autonomy with the maximum benefit, supporting the at-risk individual in the decision-making process and helping her/him to cope with the results.All relatives of patients with ATTRv should be considered as possible carriers of the familial mutation and, if they are willing to undergo genetic testing, they should be directed to an expert multidisciplinary team. The whole process should involve teams with expertise in genetic counselling, in providing accurate interpretation of molecular results and in disease-specific management and follow-up. Due to the possible psychological impact of the test results, a psychologist with expertise in genetic counselling must be available from each team.Although all adult patient’s relatives can undergo ATTRv testing, the potential benefits of PST are greater for siblings than for the offspring. In fact, siblings, especially those that are close to the predicted age of disease onset (PADO) , are at All adult at-risk individuals who may wish to take the test should be given updated and relevant information in order to make an informed voluntary decision. Pre-test counselling should include information not only about the entire testing process, but also about the post-test follow-up.In general, a minimum interval (e.g. 1 month) between the pre-test counselling session and the decision whether to take the test is habitually recommended to give the person enough time in order to make an informed and autonomous decision. The decision to take the test is the unique choice of the person concerned.Disclosure of PST results should be done preferably within 4 weeks from blood sample collection. Nevertheless, the proband should have the choice to ask for more time delay before receiving the results or also decide not to be given the results at all .Test result should be given in person to the individual who requested the PST. As a rule, the counselling team should not communicate any information concerning the test and its results to third parties without the explicit permission of the person tested.If the genetic analysis is positive, the multidisciplinary team must address the subject to the appropriate follow-up program, already discussed before the test, and based on the family mutation and the his/her actual age.Compared with PST for other late-onset untreatable diseases, the protocol for ATTRv genetic testing has undergone some changes to make it more up-to-date. In fact, in the last years, the ATTRv therapeutic scenario has dramatically changed thanks to the availability of new drugs which are able to treat the disease. Since all therapies are maximally effective in the early stages, the request for PST has largely increased as the possibility to access a therapy balances or outweighs the risk of the psychological consequences of a positive test result. In fact, nowadays, clinicians can offer individuals with positive test result a close monitoring , promptiElucidation in molecular pathogenic mechanisms and progress in pharmacological technologies led to an unexpected therapeutic revolution in ATTRv amyloidosis. A wide spectrum of targeted therapies already obtained market access and some others are close to achieve it , 59.Until recently drugs, symptomatic relief and orthotopic liver transplant were the only options for ATTRv with the most favourable results in early-onset V30M patients .Recently, new agents have been developed to suppress the production of both amyloidogenic wt and TTRv as well as fibril formation. The landscape of current pharmaceutical approaches for ATTRv includes TTR stabilizer, TTR silencers and TTR disruptors.Tafamidis meglumine  was the first specific drug approved for stage 1 ATTRv-PN on the basis of an 18-month double-blind placebo-controlled study followed by an open label extension . Later oDiflunisal, a non-steroidal anti-inflammatory drug, reduced the progression of neuropathy irrespective of mutation and severity of disease at baseline . Safety Epigallocatechin-3-gallate (EGCG), the major catechin found in green tea, appears to be able to prevent fibril formation “in vitro” and in cell culture and to disrupt pre-formed fibrils “in vitro” and in animal models . Two stuTolcapone stabilizes three leptomeningeal TTR variants, and because it crosses the blood-brain barrier, it has been proposed as a therapy for leptomeningeal amyloidosis .AG10 was well tolerated and induced a significant stabilization of TTR in ATTR-CM .ClinicalTrials.gov Identifier NCT03860935; ATTRibute-PN, ClinicalTrials.gov Identifier: NCT04418024).Two-phase three studies, in ATTR-CM and ATTRv-PN, respectively, are still ongoing  or antisense oligonucleotide (ASO) provided a therapeutic revolution, showing evidence that disease progression can be slowed, and perhaps reversed –44.Both patisiran (a siRNA) and inotersen (a second-generation ASO) are approved by the EMA and FDA for ATTRv-PN.ClinicalTrials.gov Identifier: NCT03728634), and a phase 3 is ongoing.A phase 1/2 study with a new GalNac-conjugated ASO (ION-682884) has been initiated  are not approved for ATTRv, although they both showed interesting results in experimental studies and combination of oral doxycycline and TUDCA stabilizes the disease for at least 1 year in ATTRv and wt , 75. A pSeveral monoclonal antibodies against TTR epitopes have been tested “in vitro” as potential new drugs .Dezamizumab is a fully humanized monoclonal IgG1 anti-SAP antibody that triggers immunotherapeutic clearance of amyloid. Amyloid load reduction was reported in the liver, spleen, and kidney following his administration in AL and ATTR amyloidosis .ClinicalTrials.gov Identifier: NCT03336580.A phase 1 clinical trial with PRX004 is undergoing. Improved knowledge of pathogenetic mechanisms and the development of efficacious drugs are rapidly changing the history of ATTRv amyloidosis. Thus, the progressive nature of ATTRv emphasizes the need for timely diagnosis and intervention in patients and raises the future challenge of when treating the carriers.


The objective was to (i) assess the long-term cost-effectiveness of acceptance and commitment therapy (ACT), a workplace dialog intervention (WDI), and ACT+WDI compared to treatment as usual (TAU) for common mental disorders and (ii) investigate any differences in cost-effectiveness between diagnostic groups.An economic evaluation from the healthcare and limited welfare perspectives was conducted alongside a randomized clinical trial with a two-year follow-up period. Persons with common mental disorders receiving sickness benefits were invited to the trial. We used registry data for cost analysis alongside participant data collected during the trial and the reduction in sickness absence days as treatment effect. A total of 264 participants with a diagnosis of depression, anxiety, or stress-induced exhaustion disorder participated in a two-year follow-up of a four-arm trial: ACT (N=74), WDI (N=60), ACT+WDI (N=70), and TAU (N=60).For all patients in general, there were no statistically significant differences between interventions in terms of costs or effect. The subgroup analyses suggested that from a healthcare perspective, ACT was a cost-effective option for depression or anxiety disorders and ACT+WDI for stress-induced exhaustion disorder. With a two-year time horizon, the probability of WDI to be cost-saving in terms of sickness benefits costs was 80% compared with TAU.ACT had a high probability of cost-effectiveness from a healthcare perspective for employees on sick leave due to depression or anxiety disorders. For participants with stress-induced exhaustion disorder, adding WDI to ACT seems to reduce healthcare costs, while WDI as a stand-alone intervention seems to reduce welfare costs. Mental health disorders are among the main contributors to the global years lived with disability  and are th edition, defined as a “syndrome conceptualized as resulting from chronic workplace stress that has not been successfully managed” , workplace dialog intervention (WDI), and a combination of ACT and WDI (ACT+WDI) compared to a control group receiving treatment as usual (TAU), for individuals on SA due to common mental disorders. The aims were to (i) estimate the economic attractiveness of the interventions using one- and two-year follow-up data and (ii) explore heterogeneity in the cost-effectiveness between the interventions when randomly provided to patients with either depression or anxiety disorders or with chronic stress-induced exhaustion disorder. The study was undertaken in the region of Stockholm in Sweden.The original study was designed as an RCT with 352 participants randomized into four conditions; ACT, WDI, ACT+WDI, and TAU. In the last follow-up assessment, 24 months after randomization, 264 participants agreed to participate. The study was registered at clinicaltrials.gov (Dnr NCT01805583) and approved by the Regional Ethical Review Board in Stockholm (Dnr 2012/2109-31/5). Participants had to fulfill diagnostic criteria for depression (F33), anxiety disorder (F32), or stress-induced exhaustion disorder (F43.8) according to the Swedish version of the International Statistical Classification of Diseases and Related Health Problems (ICD-10). Further, inclusion criteria were: age 18–60 years, employed, and on SA at the time for inclusion in the study. Exclusion criteria were: SA for >12 months, active suicide ideation, severe depression, history of bipolar disorder or psychosis, substance abuse or dependence, unemployment or self-employment, and insufficient comprehension of the Swedish language. More detailed information can be found in earlier publications , 20.Treatments were administered over three months. ACT treatment consisted of six 1-hour sessions with a psychologist, targeting all core ACT therapeutic processes, including acceptance, mindfulness, self as context, defusion, values clarification and, committed action. Homework exercises with relevant content were suggested after every session. WDI-treatment consisted of three steps: (i) the participant interview including open questions regarding the perception of causes of SA and factors that may facilitate RTW, (ii) the supervisor interview regarding causes and facilitators and, (iii) the three-party convergence dialog meeting, aiming at agreeing on a rehabilitation plan. ACT+WDI-treatment combined the two above-mentioned strategies administered by two separate therapists. TAU was defined as regular visits to a general practitioner for administration of SA and any other treatment that is recommended for common mental disorders within the primary care in Sweden.Data for the cost-effectiveness analysis  were colwww.sjweh.fi/article/4012) table S1. Sickness benefits costs were collected from the Swedish Social Insurance Agency (SSIA), comprising the total amount of insurance benefits paid to each participant during follow-up.Intervention costs for the treatment alternatives were established in a previously published study . Total tThe health outcome of interest was SA days. SA data were obtained from the registry of the SSIA. SA days were calculated for every participant during the one- and two-year follow-ups by adding up full-time and part-time SA to create full-day equivalents. The interventions aimed to reduce SA days; thus a negative difference in health outcome between the intervention and comparison indicates a relative improvement in health outcome. Consequently, an incremental effectiveness estimate of -1 means that a new alternative is associated with one less SA day compared to TAU. Additionally, reduction in SA days is meaningful for decision-makers, and they can establish the WTP intuitively for one avoided SA day .Incremental costs and incremental effects for each intervention compared with TAU were estimated using ordinary least squares (OLS). Incremental costs were calculated separately for healthcare costs at every assessment point and for total sickness benefits costs at one- and two-year follow-ups. Incremental effects (reduction in SA days) were calculated at one- and two-year follow-ups. Regression calculations were adjusted for age, sex, education level, birthplace, previous grade of SA and marital status. More details are presented in the online supplementary material.Missing data for the frequencies of healthcare use were imputed using predictive mean matching (PMM) based on gender, age, level of education, diagnosis, country of origin, and received sick benefits prior to the start of the interventions. Cost-effectiveness results were summarized on cost-effectiveness planes. Confidence intervals (CI) for the estimates were created using non-parametric bootstrapping. The likelihood of each intervention being more favorable compared to TAU was presented using cost-effectiveness acceptability curves (CEAC) across a range of WTP thresholds . CEAC reAll the analyses were conducted from a healthcare perspective and a limited welfare perspective for the whole sample of study participants and separately for two subgroups: (i) participants with stress-induced exhaustion diagnosis (F43.8) and (ii) participants with depression or an anxiety disorder diagnosis (F32 and F41). The results are presented for the whole sample and the subgroups as mentioned above.A trial flow diagram is presented in There were no significant differences at baseline between the four groups regarding descriptive data, proportions of disorders, outcome measures, or sickness benefit payment, see The results of incremental analyses are presented in Overall, there were few differences between intervention groups. There were no statistically significant differences in healthcare costs, sickness benefit costs, or outcome in SA days between any intervention group and TAU . BootstrCost-effectiveness acceptability curves in From a healthcare perspective , a–b, thFrom the limited welfare perspective , c–d, noWhen the analyses were conducted separately for two diagnostic subgroups – depression or anxiety disorders, and stress-induced exhaustion disorder – new patterns emerged.For the participants with depression or anxiety disorders, the ACT intervention significantly reduced healthcare costs during one- and two-years follow-up, but not SA days see . The WDIFor the participants with stress-induced exhaustion disorder see , WDI redFrom the limited welfare perspective , g–h, thAn overall analysis, including both healthcare and welfare costs, is presented in the supplementary material.This study reports on full economic evaluation of three RTW interventions for participants on SA with a diagnosis of depression, an anxiety disorder, or stress-induced exhaustion disorder, conducted alongside a randomized trial with a two-year follow-up. The results of the cost-effectiveness analyses from the healthcare and limited welfare perspectives for the total sample revealed no significant differences between the interventions. However, ACT demonstrated a high probability (90%) of reducing healthcare costs at both one-year and two-year follow-up. For ACT+WDI, the probability of healthcare costsaving improved from 60% in year one to 85% in year two. The probability of cost-effectiveness decreased with increasing WTP values, reflecting the broad uncertainty in the cost-effectiveness results. None of the interventions were more effective in reducing costs or SA, as compared with TAU. The subgroup analyses suggested important differences between diagnostic subgroups concerning healthcare costs. There was a high probability that the ACT intervention saves healthcare cost for patients with depression or anxiety disorders and ACT+WDI was the best alternative for stress-induced exhaustion disorder in terms of reduction in healthcare costs. From the welfare perspective, none of the treatment alternatives were better than TAU for depression or anxiety disorders. However, the WDI intervention was promising for stress-induced exhaustion disorder, mostly due to reduction in SA.The results of this study supports the ICD-11 classification of stress-induced exhaustion disorder as an occupational phenomenon, given that a work-oriented intervention seems to better match the needs of participants with stress-induced exhaustion disorder and contributes to less SA. This is in line with a previous study that also found a short intervention focusing on ability to RTW cost-effective for a subgroup of participants with stress-related mental disorder . AltogetFor depression and anxiety disorders, ACT may reduce healthcare costs, potentially indicating that this therapy could be better suited to the needs of this subgroup. In line with previous research, psychotherapy seems to be a more cost-effective treatment option for depression from the healthcare perspective . HoweverAlthough SA due to common mental disorders implicates significant costs to societies, there are very few robust economic studies of RTW interventions , and folIn our previous economic evaluation alongside this randomized controlled trial of ACT, WDI, ACT+WDI, and TAU , we usedIn the present study, most of the differences between the intervention groups in both costs and effects were non-significant. In health economic evaluations, there is less emphasis on statistically significant differences between groups compared to other types of evaluations. Generally, most cost-effectiveness studies are underpowered. That is why we focused on the presentation of uncertainty based on estimation rather than hypothesis testing, using non-parametric bootstrapping, the incremental net-benefit statistic, and the presentation of cost-effectiveness acceptability curves .SA days is a highly relevant outcome in insurance medicine and for employers, given that the primary cost driver is production loss when it comes to SA . In thisThe subgroup results suggest hypotheses for future studies. ACT stands out as a cost-effective treatment option in terms of healthcare costs for depression and anxiety disorders, but not for stress-induced exhaustion disorder. For stress-induced exhaustion disorder, WDI seems cost-effective from the welfare perspective, but not for depression or anxiety disorders. The cost-effectiveness of tailoring the treatment for individuals with different needs and diagnoses merit further research.This full economic evaluation shows that ACT may likely be cost-effective for employees on sick leave due to depression or anxiety disorders in terms of saving healthcare costs. Adding WDI to ACT seems to increase the cost-effectivenss of ACT for stress-induced exhaustion disorder. From the welfare perspective, stand-alone WDI interventions may be cost-effective for employees on sick leave due to stress-induced exhaustion disorder.


DNA methylation is an important epigenetic modification that is known to regulate gene expression. Whole-genome bisulfite sequencing (WGBS) is a powerful method for studying cytosine methylation in a whole genome. However, it is difficult to obtain methylation profiles using the WGBS raw reads and is necessary to be proficient in all types of bioinformatic tools for the study of DNA methylation. In addition, recent end-to-end pipelines for DNA methylation analyses are not sufficient for addressing those difficulties.Here we present msPIPE, a pipeline for DNA methylation analyses with WGBS data seamlessly connecting all the required tasks ranging from data pre-processing to multiple downstream DNA methylation analyses. The msPIPE can generate various methylation profiles to analyze methylation patterns in the given sample, including statistical summaries and methylation levels. Also, the methylation levels in the functional regions of a genome are computed with proper annotation. The results of methylation profiles, hypomethylation, and differential methylation analysis are plotted in publication-quality figures. The msPIPE can be easily and conveniently used with a Docker image, which includes all dependent packages and software related to DNA methylation analyses.https://github.com/jkimlab/msPIPE and https://hub.docker.com/r/jkimlab/mspipe.msPIPE is a new end-to-end pipeline designed for methylation calling, profiling, and various types of downstream DNA methylation analyses, leading to the creation of publication-quality figures. msPIPE allows researchers to process and analyze the WGBS data in an easy and convenient way. It is available at The online version contains supplementary material available at 10.1186/s12859-022-04925-2. DNA methylation entails attachment of methyl groups to a base of DNA, especially cytosine in the dinucleotide CpG sites. DNA methylation regulates gene expression and contributes directly to disease conditions. For example, DNA methylation directly affects carcinogenesis , 2 and gMany methods have been developed for DNA methylation sequencing, including those based on restriction enzymes , affinitDNA methylation analysis using WGBS has been performed via multiple steps, including read quality control, read mapping to reference genome sequences, and methylation calling. Computational tools such as TrimGalore!  and FastDespite the development of the computational tools dealing with sequencing data, studying DNA methylation is still a research challenge because it requires the knowledge of bioinformatics. The investigators also need to select and organize appropriate reference genome sequences and their annotation information because most of the DNA methylation analyses are performed using the reference genome. To alleviate these difficulties, several pipelines have been developed to analyze methylation sequencing data , 29–32. In this study, we present a new end-to-end pipeline of DNA methylation analysis for WGBS data. This pipeline, named msPIPE, consists of multiple steps: (i) pre-processing, (ii) alignment & methylation calling, and (iii) methylation analysis & visualization. Using msPIPE, users can obtain the results of various analyses in text format and publication-quality figures. Additionally, the use of msPIPE is facilitated by Docker, which obviates the need for requisite packages or software. The msPIPE supports all reference genome assemblies available in the R package BSgenome (v1.62.0) . ApplicaThe msPIPE pipeline consists of pre-processing, alignment & methylation calling, and methylation analysis & visualization steps Fig. . It geneThe msPIPE is implemented using Python, Perl, and R. The pipeline requires other software programs; however, the user can easily install and use it via Docker image . This DoIn this step, input data for methylation analysis is prepared and required pre-processing is done. This step consists of preparing the reference genome sequences, annotation files, and high-quality WGBS reads for analyses. For the given UCSC assembly name of a reference, a corresponding genome sequence file and a gene annotation file are automatically downloaded from the UCSC Genome Browser database . Note thThe msPIPE can receive multiple fastq files of single-end or paired-end reads for all sample replicates. All input fastq files are processed separately given that WGBS reads are trimmed by TrimGalore! (v0.6.0)  using ‘-The downloaded reference genome sequences are changed to bisulfite-converted reference genome sequences by converting C to T and G to A using Bismark (v0.20.0) (the bismark_genome_preparation module)  or BS-SeIn the alignment step, pre-processed WGBS read sequences are aligned to the bisulfite-converted reference genome sequences. For this alignment, two programs, Bismark  with ‘--In the methylation calling step, methylated genomic regions are identified by using the alignments of the WGBS read sequences. When Bismark is used, methylation calls are generated for CpG, CHG, and CHH context using the bismark_methylation_extractor module with ‘--no_overlap --comprehensive --gzip --CX --cytosine_report’ options based on the WGBS read mapping files generated in the previous step. Alternatively, if BS-Seeker2 is used, methylation calls are generated for all CX contexts using the bs_seeker2-call_methylation.py program with ‘--sorted --rm-overlap’ option. The output files of BS-Seeker2 were then converted to the files with the same format as the ones of Bismark using in-house Python script.In this step, called methylated regions are used to perform downstream analyses and visualize their results. The methyl-C calls obtained in the previous steps with CX  context are used as input for various methylation analyses and the creation of publication-quality figures. This step consisting of three sub-steps, methylation profiling, hypomethylated region analysis, and differential methylation analysis, as described below.In this sub-step, two types of methylation profiles including methylation patterns for CX context and functional annotated regions are analyzed and plotted for each target sample. For this, sample-level merged methylation calls are generated by combining all methyl-C calls from all sample replicates at the same position on the reference genome. First, using the sample-level merged methylation calls, methylation profiles are obtained by calculating methylation levels for each CX context. The methylation level for each base position comprising methylation calls is defined by the ratio of the counts of methylated Cs to the total counts of both methylated and unmethylated Cs. These methylation profiles are plotted as a bar plot with the average methylation level, and as a histogram with the methylation level distribution of each CX context for each sample. Whole genome-scale methylation profile is plotted into the Circos plot with three different tracks using the R package circlize (v0.4.13) . The aveIn this sub-step, hypomethylated regions (HMRs), which are contiguous genomic regions with lower methylation level than neighboring regions, are identified by using the R package MethylSeekR (v1.34.0)  by automWhen pairs of samples for pairwise comparison of methylation are set, the analysis of differentially methylated regions (DMRs) is performed for each comparison set in this sub-step. DMRs are defined as the genomic regions with different methylation level between two samples which can be called as case and control respectively. DMRs can be further divided into hypomethylated (with relatively lower level of methylation) or hypermethylated (with relatively higher level of methylation) regions. Specifically, when the methylation level of a genomic region in the case is lower than the level in the control, the genomic region in the case is defined as the hypomethylated DMR. In the opposite case, the genomic region in the case is defined as the hypermethylated DMR. The analysis of DMRs can be performed using either methylKit  or BSmoomsPIPE and similar pipelines for methylation analysis , 46, 47 The msPIPE was applied to publicly-available human (accession number: PRJEB28044)  and mousTo assess the applicability of msPIPE, methylation analyses were performed using the published human and mouse WGBS datasets (see Implementation). Pre-processing, mapping to bisulfite-converted genome sequences, and methyl-C calling were performed sequentially.Trimming for adaptor and low-quality sequences was performed for all input WGBS reads. The quality of each trimmed read was computed using FastQC program. Additionally, all reports were summarized as an html file using MultiQC program. For example, the statistical data of read quality for all human and mouse WGBS reads after pre-processing were summarized together (Fig. After pre-processing, the various methylation profiles for human and mouse samples were generated. First, the methylation level of each C called using the Bismark package was calculated and summarized with genomic and CX context. For the genomic context, the average methylation levels of each functional region were obtained. For the human old sperm dataset, the average methylation level of the promoter, mostly known to be located in CpG islands , was lowWe performed the differential methylation analysis between control and case as young versus old for all three pairs of samples: human blood, human sperm, and mouse rod. In the human dataset, the total number of DMCs with a q-value of 0.5 or less was 244 in blood and 34,514 in sperm samples (Additional file In the previous study for the human WGBS dataset , gene onThe results of human DMC analyses derived from msPIPE revealed additional findings. Among the human sperm samples, 393 differentially methylated genes with one or more DMCs in the promoter were identified (Additional file We present an end-to-end WGBS analysis pipeline, msPIPE, used to perform bioinformatic analyses ranging from input read pre-processing to downstream analysis. When the input WGBS read sequencing files and the UCSC assembly name of a reference are given, the user can conveniently obtain methylation profiles, publication-quality figures, differentially methylated regions, and related genes for a given comparison pair. In the comparison with existing nine pipelines, msPIPE was found to perform better in terms of supported types of analyses, supported optional tools, and a convenient way for the preparation of reference genome data. The msPIPE is implemented using the Docker image, which obviates the need to install all dependent packages and software. Especially, specific R packages dependent on different UCSC assembly versions of references for all kind of species provided by the R package BSgenome are automatically imported along with sets for running msPIPE. Therefore, msPIPE can be used as a convenient and effective tool for methylation analysis of WGBS data.Additional file 1. Supplementary figures.Additional file 2. Supplementary tables.