Despite advances in allogeneic hematopoietic cell transplantation, acute graft-versus-host disease (aGVHD) remains its leading complication, yet with heterogeneous outcomes. Here, we analyzed aGVHD phenotypes and clinical classifications in depth in large, multicenter cohorts involving 3019 patients and addressed prevailing gaps by developing data-driven models. We compared, tested and verified these along with all conventional classifications in independent cohorts and found that data-driven grading outperformed conventional grading in Akaike information criterion and concordance index metrics. Data-driven classifications refined aGVHD assessment with up to 12 severity grades, which were associated with distinct nonrelapse mortality (NRM) and confirmed the key role of intestinal aGVHD. We developed an online calculator for physicians to implement principal component-derived grading (PC1). These results provide substantial insight into the evaluation of aGVHD phenotypes and multiorgan involvement, which relegates the exclusive reporting of overall aGVHD severity grades in transplant registries and clinical trials. Data-driven aGVHD grading provides an expandable platform to refine classification and transplant risk assessment. Acute GVHD severity grading is based on target organ assessments. Here, the authors show that data-driven grading can identify 12 distinct grades with specific aGVHD phenotypes, which are associated with clinical outcomes, and that their method outperformed conventional gradings. It’s clinical grading, leveraging the physician’s assessment of 3 target organs , was introduced by Glucksberg et al.2, later revised by the Keystone GVHD Consensus conference3, by the International Blood and Marrow Transplant Registry (IBMTR)5, the University of Minnesota7 and by the Mount Sinai aGVHD International Consortium (MAGIC)8. Today, in particular, multiorgan involvement and therapy resistance remain a challenge in aGVHD assessment. Inconsistent assessment practices between HCT centers and unwitting use of different grading systems further reduce the comparability of data10. During the last decade, many efforts to improve aGVHD assessment and outcome prediction have focused on the identification of universal12 and organ-specific aGVHD biomarkers15. Indeed, biomarker combinations can predict 6-month nonrelapse mortality (NRM), aGVHD mortality17, and overall survival (OS) in aGVHD patients18 but are not universally available. Accumulating evidence of complex aGVHD biology19 conflicts with the quest for a simple assessment and classification for clinical practice.Acute graft-versus-host disease (aGVHD) remains the major cause of early morbidity and nonrelapse mortality (NRM) after allogeneic hematopoietic stem cell transplantation (HCT)21 and aGVHD24 after HCT. Given these recent insights, prevailing discrepancies in conventional aGVHD classification practice, and substantially varying survival outcomes of patients with the same aGVHD severity grade, we hypothesized that a data-driven approach could shed light on the strengths and limitations of aGVHD classifications and respond to ongoing issues such as multiorgan involvement, heterogeneous phenotypes and their relation to outcomes. We leveraged several data science methods , hierarchical clustering (Hclust), K-means clustering, uniform manifold approximation and projection (UMAP) and density-based spatial clustering of applications with noise (DBSCAN) on clinical aGVHD organ assessments to address these issues in a large multicenter cohort of HCT patients with aGVHD. These grading methods resulting from our work were independently validated and tested  and grading practices may improve the understanding of aGVHD and support optimal treatment strategies, we standardized reporting between centers via full documentation of aGVHD organ involvement while assembling a multicenter aGVHD dataset and analyzing it to an unprecedented extent. Using unsupervised learning methods, we then developed several data-driven aGVHD grading systems and compared their severity indexing along with that of conventional aGVHD grading systems via different performance indices.n = 3019). Aiming for a proportional split of 2/3 and 1/3 between the training set and the independent test set, aGVHD patients from two centers were used for training  and three independent centers for testing . The cohorts’ baseline characteristics were balanced for age, sex, recipient cytomegalovirus-positive serostatus (CMV R+), donor type, and TBI and are detailed in Supplementary Table This large, multicenter dataset included contemporary HCT patients diagnosed with aGVHD from 5 major German HCT centers n = 309. Aiming3) possible combinations, with zero corresponding to the absence of aGVHD in the given organ). Due to a linear variation in the data  according to PC1 and tested their separation on the PC1 axis by coloring for MAGIC . Indeed, Hclust successfully dissected the training data into four clusters with significantly distinct OS  and silhouette coefficient  on the data to address heterogeneity, and the results are detailed in the Supplementary Notes and Supplementary Figs. For the development of data-driven aGVHD grading systems using unsupervised learning, we gathered data on individual patients’ organ involvement in a multidimensional data space , with organ-specific aGVHD severity represented in the range from 0 to 4) with the intention to represent the maximum of the clinical variance of aGVHD  into groups with significantly distinct OS values (p < 0.0001). Starting from the day of aGVHD diagnosis, the NRM curves also revealed significant differences , which graded, e.g., combinations of GI and other organs at a lower severity than single GI stage 1 involvement  than the remaining grade III MAGIC patients. Similar heterogeneity was observed for Consensus grade III patients , skin aGVHD alone was the least effective in distinguishing patient cohorts with respect to outcome. Accordingly, the PC1 loadings plots of the training cohort  and concordance index (Ci). The lowest—and therefore best—AIC was found among the data-driven grading systems Fig. . Among tThis study is the first to systematically evaluate conventional aGVHD grading along with data-driven methods and presents results from the development, validation, and independent test of the first data-driven aGVHD grading systems. Via extensive comparisons of the different strategies, this study answers the question of which domains data-driven classifications reveal advantages in over conventional classifications and vice versa. Our results shed light on the complexity of clinical aGVHD phenotypes, dissect the impact of multiorgan involvement and may improve the stratification strategies of future clinical trials to assign novel drugs to best-fitting recipients.25, multiorgan involvement and treatment resistance remain key challenges to the current aGVHD treatment setting, and heterogeneity in reporting is one of the issues. Past efforts to standardize aGVHD grading practices26 and achieve comparability between HCT centers have positively impacted quality assurance in the HCT community. Our data demonstrate that data-driven grading of aGVHD is feasible, can be implemented via a digital application and reveals several advantages over conventional grading. Data-driven grading also facilitates physicians in managing the complexity of aGVHD phenotypes by weighting and combining multiorgan involvement and finally reducing it to a single score. Overall, data-driven grading outperformed conventional classifications in performance indices. However, it is insufficient to evaluate grading systems based on a single quality measure. Hence, our judgment was made considering all the evidence generated in this study, including several performance metrics, proportional distribution and repartition of aGVHD phenotypes in grading categories. This extensive comparison identified several clinically relevant strengths and weaknesses of each grading system, as detailed in the results. Importantly, Consensus grading clearly underestimated the importance of GI involvement, particularly in stage 4 GI aGVHD, and hence is used with decreasing frequency in the HCT community. However, it is still referred to as today’s standard in the reporting of HCT data to transplant registries, which likely impairs benchmarking. Our data showed that MAGIC grading performed best among the examined conventional grading systems. Nevertheless, this study also revealed some shortcomings that remained unnoticed. For instance, MAGIC grade III assembles a diverse set of aGVHD phenotypes, which would likely profit from reclassification, as some of these are associated with significantly better outcomes, and MAGIC is very similar to other systems, particularly the Minnesota grading system. Despite the unquestionably important role of GI involvement in aGVHD, our data indicate that MAGIC grading may overestimate its impact. Patients with GI stage 1 are categorized into MAGIC grade II, and patients with GI stage 2 and no other organ involvement are considered grade III. The impact of multiorgan involvement is structurally underestimated with this logic. PC1 grading addressed both issues by attributing a high yet not exclusive weight to GI involvement while integrating patients’ multiorgan aGVHD phenotypes. Additionally, for refined grading steps , PC1 grading always considers multiorgan involvement at each grade. The challenge of implementing refined data-driven grading steps in clinical practice can be eased via digital tools, such as our provided online calculator (www.gvhd.online), and can yield more precise diagnoses allowing future trials to potentially adapt treatments to the severity of aGVHD. Despite the apparent complexity of the data, they exhibited a linear variation in the multidimensional space. In a higher dimensional dataset, i.e., with more features including biomarkers, nonlinear methods may add further value to data-driven aGVHD grading.Despite new drugs and preventive strategiesThis study has strengths and limitations. It included an unprecedented cohort size and level of detail in the assessment of aGVHD with effective data-driven methods for aGVHD assessment, which are prepared for further adaptations to the needs of precision medicine. However, its geographical setting in Europe may have limited ethnic diversity. Due to the enrollment period, the cohorts included only 1-2% of patients receiving posttransplant cyclophosphamide (PTCy); nevertheless, data-driven methods evaluating aGVHD phenotypes are equally applicable in the PTCy setting, while the clinical outcome association remains to be confirmed. GVHD treatment data were not reported in detail. In its present form, the PC1 algorithm may slightly underestimate the gravity of isolated single organ stage 4 aGVHD involvement for the skin or liver; however, this limitation is unlikely to restrain clinicians from treating aGVHD and may be overcome with even larger datasets. Data-driven grading currently uses clinical aGVHD assessments but may also be extended by integrating biomarkers or other data sources from precision medicine.This study provided a detailed analysis of all aGVHD grading systems and pioneered and demonstrated the utility of data-driven grading, particularly PC1 grading. These results support HCT registries in policy change to inform more comprehensively on aGVHD. HCT centers should not only report the overall aGVHD grade to registries but also provide each organ’s involvement for optimal benchmarking. Clinical trials should report more details on the involvement of specific organs, heterogeneity, and distribution of aGVHD phenotypes in their cohorts, data which may be analyzed by these tools to improve HCT care. Data-driven grading provides an expandable platform for classification and risk assessment supporting precision medicine in transplantation.n = 1345) and the Department for Stem Cell Transplantation of the University Medical Center Hamburg-Eppendorf (n = 974). The independent test cohort included 700 patients from 3 large academic HCT centers, the Department of Hematology, Hemostasis, Oncology and Stem Cell Transplantation of Hannover Medical School (n = 434), the Department of Medicine and Hematology, Charité Universitätsmedizin Berlin (n = 156) and the Department of Internal Medicine V, University Hospital Heidelberg (n = 110). For comparative Cox analysis of different aGVHD grading systems, an additional cohort (n = 735) of HCT patients without aGVHD (aGVHD grade 0) served as the reference group. Patient baseline data, donors, HCT characteristics, aGVHD organ stages and HCT outcomes were extracted from patients’ electronic health records and retrospectively analyzed. To ensure data quality, correct classification and standardized aGVHD reporting between different HCT centers, full documentation of clinical aGVHD organ involvement  was required and served to calculate the grades of both conventional and data-driven classifications. Appropriate coverage of aGVHD phenotypes in cohorts was verified during the exploratory data analysis. Assignment to HCT treatment, GVHD prophylaxis, supportive care and follow-up care were based on standardized clinical treatment protocols and HCT center policies, considering hematologic diagnosis, age, comorbidities and donor constellation. Details are provided in the supplementary data. After HCT, inpatients were screened daily for clinical signs of aGVHD. Outpatients were assessed at each visit . Further outpatient follow-up intervals were sequentially extended, depending on clinical status and HCT-related complications. Once diagnosed, aGVHD severity was evaluated daily for inpatients and at each visit for outpatients and documented in patients’ health records. The maximum extent of aGVHD organ involvement and severity was used as an input variable for analysis.This analysis included 3754 adult patients with allogeneic HCT between January 2008 and December 2018, of which 3019 had aGVHD. The training cohort of data-driven aGVHD grading included 2319 consecutive patients diagnosed with aGVHD after HCT from two major German academic HCT centers, the Department of Hematology and Stem Cell Transplantation of the West German Cancer Center at University Hospital Essen (n = 2319) and test cohorts (n = 700) to ensure adequate data distribution in the independent test cohort. A correlation matrix was generated with Spearman’s rank correlation coefficients for the target organ stages . Pair plot analysis was used to illustrate and compare the distribution of single variables of the skin, liver, and GI and their mutual relationship.Exploratory data analysis was performed on the training  was applied to transform the multidimensional dataset into a set of successive orthogonal components so that the variance in the data could be explained at best in a lower dimensional space. Biplot and scree plots were used to display the results of this dimensionality reduction. The loading scores of the first principal component  were used to formulate an aGVHD severity index K-means clustering were applied to the training cohort data. For HClust, a bottom-up approach was adopted, and the distance threshold was set to 30 to split the cohort into 4 clusters. Distances between data points for the clusters were determined by ward linkage using the minimum increase of the sum of squares (MISSQ) as previously described27. The results are presented in a dendrogram. Partitional K-means clustering was the second alternative data-driven method that we applied. The determination of the optimal cluster combination was evaluated via both the sum of squares of distances  and the silhouette coefficient performance index. Again, the default cluster number was set to 4. Cluster numbers >4 were used for supplemental analysis . Given that clustering-defined grades were not automatically categorized into higher or lower severity, we ranked clustering grades using OS. Despite its large size, the training cohort did not represent all possible aGVHD phenotypes . aGVHD phenotypes of the test cohort that were not defined by the training cohort (n = 6) were omitted for validation.As alternative data-driven methods, agglomerative hierarchical clustering (HClust) and partitional All studied aGVHD grading systems in this study were externally tested on an independent multicenter test cohort from three large German HCT centers. To compare the grading performance of different data-driven and conventional aGVHD grading systems, we employed several established comparative metrics.28 using the following formula:L) is the conditional log-likelihood for Cox proportional hazards models and p’ is the number of categories in a given grading system. Due to the potential presence of tied events, the Efron method29 was additionally used. The range of the AIC varies with the size of the studied population but is comparable in the same dataset. Smaller AIC values are preferable.We applied the Akaike information criterion (AIC) as previously described31 was employed to compare the prognostic ability of the survival models. The risk groups in the survival models were created with respect to the aGVHD grades, which were obtained by using data-driven and conventional grading methods. The range of the Ci is from 0 to 1, with a higher value considered superior.Harrel’s concordance index (Ci)Time-dependent receiver operating characteristic (ROC) curves were generated to visualize the specificity and sensitivity of aGVHD classifications for 12-month OS and NRM. The areas under the ROC curves (AUROCs) were compared between different grading methods.32 to compare the intergrading agreement of the different grading systems, which categorize patients into 4 severity grades . Cohen’s kappa ranges from 0 (no agreement) to 1 (full agreement). Values between 0.41 and 0.6 indicate moderate agreement, and values between 0.61 and 0.8 indicate substantial agreement. Values between 0.81 and 1 indicate very high agreement.Cohen’s kappa was calculated as previously describedn = 700) of aGVHD patients was analyzed for nonrelapse mortality (NRM) and overall survival (OS) at 12 months. Patient outcomes were comparatively visualized for each grading system with stratification according to the respective aGVHD severity grade. OS was analyzed via Kaplan‒Meier analysis33; aGVHD grade subgroups were compared using the log-rank test; and survival hazards were calculated by a Cox proportional hazards model34. NRM and relapse were considered competing events and were analyzed by competing risk analysis and compared by Gray’s test. P values < 0.05 were considered statistically significant.The external test cohort  using the following libraries: Rtsne, umap, tidyverse, readxl, writexl, ggplot2, survival, survminer, cmprsk, ggstatsplot, cmprsk, dplyr, dynpred, tidyr, aod, tableone and timeROC. Details and references to all libraries are provided in the supplementary data.The development of data science grading methods  was performed with the open-source software Python (version 3.10.2) using the following libraries: scikit-learn, numpy, scipy, pandas, matplotlib, seaborn, os, pyaml and datetimStudy protocol approval was obtained by the institutional review board of the University Duisburg-Essen (Protocols Nos. 17-7675-BO and 21-9965-BO). All patients have given written informed consent to the collection, electronic storage, and scientific analysis of anonymized HCT-specific patient data in accordance with German legislation and the revised Helsinki Declaration. We confirm that no patient can be identified through the use of anonymized patient data.Further information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1-11Reporting SummarySource Data


Multiple sclerosis (MS) is a heterogeneous disease of the central nervous system that is governed by neural tissue loss and dystrophy during its progressive phase, with complex reactive pathological cellular changes. The immune-mediated mechanisms that promulgate the demyelinating lesions during relapses of acute episodes are not characteristic of chronic lesions during progressive MS. This has limited our capacity to target the disease effectively as it evolves within the central nervous system white and gray matter, thereby leaving neurologists without effective options to manage individuals as they transition to a secondary progressive phase. The current review highlights the molecular and cellular sequelae that have been identified as cooperating with and/or contributing to neurodegeneration that characterizes individuals with progressive forms of MS. We emphasize the need for appropriate monitoring via known and novel molecular and imaging biomarkers that can accurately detect and predict progression for the purposes of newly designed clinical trials that can demonstrate the efficacy of neuroprotection and potentially neurorepair. To achieve neurorepair, we focus on the modifications required in the reactive cellular and extracellular milieu in order to enable endogenous cell growth as well as transplanted cells that can integrate and/or renew the degenerative MS plaque. Multiple sclerosis (MS) pathology presents as several multifocal lesions characterized by inflammation and demyelination within the central nervous system (CNS) . These pThe severity and frequency of relapses during the RRMS phase can be alleviated to some extent by currently available disease-modifying treatments (DMTs) such as fingolimod, which modulates immune cell trafficking. Despite the significant therapeutic impact of DMTs in improving the symptoms of RRMS, the conversion to secondary progressive MS (SPMS) remains a prognostic outcome with further neurological progression governed by the lack of treatment options. Therefore, treatment for progressive MS remains a major unmet medical need ,12,13,14The urgent need for novel and/or repurposed therapeutics has been highlighted by a recent retrospective study conducted in Iran that predicted 93% of RRMS patients would transition into SPMS within a span of 30 years despite receiving early intensive DMTs or escalation treatment . AnotherIn this review, we discuss the comprehensive cellular and molecular mechanisms involved in the progressive stages of MS, with particular focus on the role of phagocytosis in promoting remyelination and axonal regeneration within the CNS. Moreover, we highlight the benefits of using cellular delivery strategies, such as genetically modified hematopoietic stem cells (HSCs) that can express potential therapeutic proteins capable of crossing the blood–brain barrier (BBB) to repair the CNS environment during progressive MS. Furthermore, we address the lack of cellular and molecular biomarkers used in MS diagnosis and in the assessment of progression by exploring novel potential biomarkers as a means of monitoring neuroreparative strategies designed for clinical translation during trials of recruited individuals living with SPMS.Structurally, the BBB is a tightly regulated biophysical cellular barrier consisting of cerebral endothelial cells, pericytes, and a basement membrane that interacts with astrocyte end-feet . This bOther pathogenic factors that are upregulated within the extracellular milieu include matrix metalloproteinases (MMPs), which regulate the cleavage of the extracellular matrix (ECM) proteins and penetrate and mobilize innate and adaptive leukocytes throughout the CNS tissue . The impThroughout the neuroinflammatory lesions, the cytokines generated by differentiated T cells that can drive MMP activity within the pathogenic milieu can include tumor necrosis factor-alpha (TNF-α) and interleukin (IL)-17, which can stimulate MMP-9 transcription to degrade the ECM . This woThe relationship of MMP activity during lesion formation in active MS demonstrates a dysregulation of MMP-1, -2, -3, -7, and -9 expression by demyelinating macrophages. When these lesions progress to the chronic state, macrophages display a downregulation of MMP expression ,29. AlexImmune cell infiltration across the BBB may well be the primary target for future therapeutics to limit pathogenic T-cell subsets from perpetuating the cycle of neuroinflammation. Recent evidence has implicated the dual immunoglobulin domain-containing cell adhesion molecule (DICAM) as a prominent receptor expressed on invading T-helper (Th) cell 17+ lymphocytes during RRMS and progressive MS . Importainside-out and outside-in models, which manifest similar clinical presentations . These  the CNS ,36,37. C the CNS ). Althou the CNS . Investi the CNS .The CLECimmunity ,41. The immunity ,43,44.+ T cells are able to recognize both EBV and myelin peptides PK11195 [11C]PBR28 [18F]FEPPA [11C]ER176 PK11195 , [11C]PB1C]PBR28 , [18F]FE8F]FEPPA , and [111C]ER176 . 11C]PK11195 in lesions and NAWM in SPMS patients was reported, which is associated with ongoing microglial activity [11C]PK11195 has poor BBB permeability and high non-specific binding, whereas other tracers displayed heterogeneous binding to TSPO . Conseqiew, see ). Anotheiew, see , which diew, see  but not iew, see ,297. Thi11C]PiB was higher in NAWM compared to gray matter, and there was a lack of [11C]PiB uptake in the lesion sites of RRMS patients [11C]PiB binding in MS lesions over time using PET imaging, suggesting that it may demonstrate remyelination within MS lesions [Thioflavin T derivatives, such as Pittsburgh Compound-B (PiB), have also been used in PET imaging to detect amyloid pathology in Alzheimer’s patients due to its binding affinity for myelin, making such tracers potentially useful in assessing demyelination and even remyelination in MS ,299. Stapatients . Similar lesions ,302. PieThe current unmet medical need in treating progressive MS is limited due to CNS-specific pathological lesions separated in time and space with low efficacy of targeted agents to cross the BBB, especially in the secondary progressive phase, during which the BBB reseals. Once therapeutics can reach the CNS compartment with appropriate bioavailability, they must achieve efficacy by either limiting the pathogenetic mechanisms that propagate neurodegeneration or potentiate neurorepair. As such, phagocytosis of myelin debris that may contain inhibitory factors for remyelination could be key to improving neurorepair and limiting neurodegeneration during progressive MS. With the development of cellular therapies, the transplantable cells may remodel the inhibitory and inflammatory endogenous environment that ensues during MS. These novel therapeutic strategies may be designed to target ECM deposited during the evolution of pathogenic lesions or alternatively to cellular-based therapies targeting immune cells, glial cells, and neuronal responses that may initiate neurorepair.Recent developments in neurotherapeutic outcomes during secondary and primary progressive MS have emanated out of efficacy studies using Bruton’s tyrosine kinase (BTK) inhibitors to limit B-cell development and signaling ,304. TheThe complex interplay between the innate and adaptive immune mechanisms that govern chronic neuroinflammation  can inv3)+ regulatory T lymphocytes (Tregs) [The ECM has been shown to play an important role in leukocyte activation and infiltration into the CNS. The increase in the production of hyaluronan in the ECM has been observed in both acute and chronic inflammatory sites, especially in the demyelinated lesions of MS and EAE . Winkler (Tregs) . In addi (Tregs) ,315. TheAnother component of the ECM includes chondroitin sulfate proteoglycans (CSPGs), which play a central role in the formation of glial scars, can regulate lymphocyte migratory responses and remyelination potential with profound effects on axonal regeneration ,317,318.Additionally, CPSGs have been shown to negatively influence the differentiation of OPCs in pathological conditions and limit remyelination during inflammatory demyelination. Siebert and Osterhout discovered that CSPG inhibited neurite outgrowth along with the differentiation of OPCs in vitro, but treatment with chABC reversed the inhibition . In suppIn progressive MS patients, the most common type of lesion is the slowly expanding lesion with a hypocellular demyelinated center . The gliCell-based therapies may be a promising approach to support the ongoing efforts of overcoming the lack of effectiveness of DMTs in patients with progressive MS. The concept of replacement of autoreactive and pathogenic cells and related output on signaling pathway regulation are of increasing interest in the research on progressive MS to eliminate autoreactive immune responses and enhance neurological recovery. Neural stem cells (NSCs) and autologous HSC-based transplantation has recently reached the clinical trial phase, opening the possibility of using cellular replacement as a regimen for MS patients.NSCs distribute in neurogenic stem cell niches, specifically enriched in the subventricular zone (SVZ) adjacent to the lateral ventricle in the forebrain and the subgranular zone (SGZ) of the dentate gyrus (DG) interface in the hippocampus . As men−/− NSCs, microglia failed to convert to an anti-inflammatory phenotype, and only a slight recovery of behavioral outcomes was observed [A major problem in achieving neurorepair through NSC transplantation during MS is to resolve the pro-inflammatory microenvironment and repopulate the parenchymal functional cells at the lesion site. However, excessive and disorganized ECM, apoptotic cell debris, and pro-inflammatory cytokines can affect the viability, differentiation, and migration ability of NSCs to the lesion site ,338,339.observed .Bone marrow-derived NSCs and those derived from the SVZ have been shown to exert almost the same therapeutic effects in the EAE preclinical models, and interestingly, the BM-derived NSCs have similar morphological characteristics and similar capability of differentiating into neurons and glial cells to SVZ-derived NSCs . Xie et These results indicate that genetically modifying NSCs can be more effective at inhibiting clinical severity, inflammation, and demyelination in the CNS of mice. In addition, these investigations reported that the total number of neurons and oligodendrocytes in the CNS was significantly increased in the TGF-β1-transfected NSC transplantation group compared with the control group injected with normal saline . However+CD25+FoxP3+ Tregs were observed following transplantation of human NSCs into mice at the chronic stage of the disease [A demonstration of remyelination of the CNS in EAE-induced male mice and an increased number of CD4 disease . Compare disease . Harris  disease . In the  disease .HSC transplantation has been shown to be a potential treatment for ameliorating neurological deficits by promoting neural regeneration and functional recovery ,349. TheGene modification techniques applied to cells  before cellular-based transplantation is an ideal strategy that enhances functional cell survival and promotes CNS regeneration in the model of neurodegenerative diseases ,352,353.A signaling cascade that may govern neurodegenerative change within the CNS has been well established to involve the inhibitory-signaling cascade induced by myelin-associated inhibitory factors (MAIFs). These MAIFs include Nogo-A, which has the strongest inhibiting effect on CNS neuronal and myelinated oligodendroglial lineage cells through binding to Nogo receptor 1 (NgR1) . NgR1 aHSCs can differentiate into various immune cells such as T cells, B cells, and macrophage  and HSCThe major cellular players in MS consist of T cells, B cells, macrophages, astrocytes, microglia, and oligodendrocytes that undergo reactive changes when exposed to pathological conditions in the CNS. Although diverse immunomodulatory DMTs are being investigated, they mainly target the T and B cells and aim to resolve inflammation during the acute stage of RRMS. Moreover, there are only a few approved DMTs for patients with progressive MS who have suffered from permanent neuronal and behavioral dysfunction due to extensive demyelination and neurodegeneration. Many studies focus on the clearance of myelin debris and the removal of inhibitory substrates in the glial scar to promote neuroregeneration, prompting the adaptive immunity- and glia-mediated response to facilitate the neural repair process. Histopathologically, acute demyelinating inflammatory lesions substantially develop into chronic active and chronic inactive plaques, and these chronic lesions are typically observed in the post-mortem tissue sections of SPMS patients. The distribution of immune and glial cell populations within chronic plaques in progressives MS is vastly different from acute lesions in RRMS. The presence of demyelinated axons and reactive gliosis from activated astrocytic and microglial interactions contributes to the formation of glial scars, which are observed in chronic MS plaques. Classical MS-like disease models, including EAE and cuprizone toxin models, have similar immunopathology and glial pathology with MS, and these models are being used to investigate the complexity of cellular responses during neurodegeneration. Nonetheless, several limitations, such as the insufficient manifestation of MS progression and pathophysiological hallmarks in EAE and cuprizone toxin models, still exist. Hence, a newly developed animal model needs to be investigated, particularly linking inside-out and outside-in mechanisms to outline a more comprehensive profile of MS cellular pathology and pathogenesis. A recent study using a newly developed MS-like model, defined as cuprizone autoimmune encephalitis (CAE), reported that both endogenous and peripheral immune responses can be activated during lesion formation and demyelination ,369. ThiOne issue in translational research of MS is that there are limited molecular and cellular biomarkers available for monitoring the disease severity and examining the effectiveness of the therapies over the course of MS. As a consequence of inconsistent and unpredictable disease progression in MS patients, it is difficult to find a biomarker with well-evaluated validity and clinical relevance. From the visualization perspective, advanced MRI techniques provide several imaging biomarkers through the assessment of brain volume and the thickness of the cortical cortex, which have helped to establish the microstructural changes in the CNS for MS patients. However, fluctuations in parameters obtained from MRI techniques in different MS patients highlight the potential risk of results that are rarely reproducible. The potential strategy of combining molecular biomarkers with imaging techniques to investigate either new therapeutics or disease progression monitoring provides a feasible way to obtain a more accurate analysis.Another important consideration to improve the clinical outcomes of MS patients is to investigate potential therapeutics. Stem cell transplantation combined with genetic modification techniques has become a promising option for treating autoimmune diseases and immunodeficiency disorders. This therapeutic strategy not only replaces the pathogenic immune cell populations with healthy cells but also produces therapeutic proteins by genetic-editing techniques on transplanted cells. The delivery of decoy fusion protein NgR(310)ecto-Fc via genetically modified HSCs directly into the lesions can inhibit neurodegeneration and improve neurorepair, potentially offering long-term neuroprotection after the progressive stage of the disease. The repair can also be assessed using existing molecular and imaging biomarkers. In the future, genetically modifying HSCs with CRISPR-Cas9 to deliver NgR(310)ecto-Fc may improve the safety of the treatment and possibly offer a new therapeutic option for progressive MS patients.


Existing splice prediction tools are complementary but knowing which to use for each splicing context remains difficult. Here, we describe Introme, which uses machine learning to integrate predictions from several splice detection tools, additional splicing rules, and gene architecture features to comprehensively evaluate the likelihood of a variant impacting splicing. Through extensive benchmarking across 21,000 splice-altering variants, Introme outperformed all tools (auPRC: 0.98) for the detection of clinically significant splice variants. Introme is available at The online version contains supplementary material available at 10.1186/s13059-023-02936-7. An important challenge in genomic medicine is the accurate identification of genetic variants that either cause disease or drive disease progression, and overcoming this challenge is critical to achieving a genetic diagnosis. The use of genome sequencing for rare genetic diseases can generally provide a diagnosis in 40–60% of cases . These cThe process of splicing is critical for the accurate generation of mRNA and ultimately protein. The delineation of coding regions by the precise removal of intronic DNA from pre-mRNA is orchestrated by over 200 proteins and small nuclear RNAs (snRNAs) through the recognition of defined sequence motifs . The maiSeveral in silico methods have been developed to predict the likely splicing-impact of a genetic variant –13. ChooAnother category of in silico splice-prediction tools is overall predictors, which attempt to identify all types of splice-altering variants, often constructed using artificial intelligence methods. The first deep learning method, SPANR/SPIDEX , used RNHere, we describe a novel in silico splicing analysis tool called Introme, which evaluates a variant’s likelihood of altering splicing by combining predictions from multiple splice-scoring tools, combined with additional splicing rules, and gene architecture features. Introme can accurately predict the impact of human coding and noncoding variants on splicing through investigating for the potential damage, creation, or strengthening of splice elements and outperforms all leading tools that we tested. This was achieved using a machine learning approach to optimise the performance of several best-in-class splice-detection tools. Introme allows the investigator to comprehensively identify splice-altering variants, avoiding the need to consult and interpret the outcomes from multiple tools.n = 1785; Additional file To guide the development of Introme, we undertook a comprehensive review of the literature to curate a list of variants functionally validated for splicing impacts using a variety of techniques, including RNA-seq, minigene splicing assays, and RT-PCR. We identified 1174 variants with and 611 variants without an effect on splicing across a range of rare genetic disease and cancer genes were used to train or test Introme , and when assessing model performance using tenfold cross validation, the C5.0 decision tree model ) ) . Whilst Taken together, these results demonstrate that Introme outperforms all tools tested when considering 21,000 true positives from four different validation datasets, one saturation mutagenesis screen, clinical data, and common polymorphisms.We present Introme, a comprehensive method to predict splice-altering variants with several clinical applications. Introme draws from multiple class-leading splicing prediction tools, adds additional functionality to identify variants missed by existing tools, and simplifies the process of running and interpreting the results from each of the incorporated predictive tools. Introme evaluates variants at any location within a gene for splice-altering potential, from exonic to deep intronic variants. When compared with established splice-prediction tools, Introme achieved the best performance on a dataset of functionally validated variants with an auPRC of 0.98 and consistently outperformed the next best tool’s (SpliceAI) sensitivity and false positive rate across multiple validation datasets and gene regions. In addition, Introme’s ability to accurately classify variants and predict likely splicing outcomes was applied to several clinical datasets and showed utility for the identification of splice-disrupting genetic variants in several clinical settings. Introme has been used to discover splice-altering variants in both germline and somatic tissues, in childhood cancer , and sevWe have demonstrated that existing splice prediction tools are complementary, with distinct strengths and weaknesses. Prior to the development of Introme, investigators needed to learn these characteristics, and determine which tools to trust for each class of splicing variant, which made it challenging and time consuming to screen variants for splice-altering potential. Introme significantly lowers the barrier to entry to predicting the splicing impact of genetic variants, because it can detect all types of splice-variants in coding and noncoding sequences and has learnt where its constituent tools perform well. Introme’s use of a consensus scoring approach allows shortcomings of the constituent tools to be learnt and supplemented by other tools. For example, Introme relies heavily on SpliceAI, but for variants that impact existing canonical splice sites, the better performance of MMSplice and Spliceogen in these regions improves the overall performance of Introme. Furthermore, as SpliceAI was trained on naturally occurring intron–exon junctions, several edge cases, such as AG-exclusion zone variants, minimal-length introns, and splice junctions from the minor spliceosome can be mis-classified. We addressed these limitations not captured by any tool by adding additional rules. When SpliceAI and MMSplice do not score a variant, which we saw primarily in the common variant analysis FI, we obsFurther research to predict the functional impact  of splice-altering variants and improved methods to identify splicing regulatory variants are required to further improve the utility of in silico splice predictors. In our training data, only 10% of variants had a reported quantitative value for the impact on splicing, namely the percent spliced in (PSI) value. The field needs to first gather more data linking genetic variants, to functional splice alterations and PSI, perhaps via massively parallel splicing assays ; this woTo develop Introme and benchmark it with other in silico prediction tools, we surveyed the literature to identify a large resource of variants with known splicing impacts. We aimed to identify variants across a whole range of classes, with a particular focus on identifying deep intronic and non-canonical splicing variants. We further supplemented this curated resource with three larger-scale datasets, primarily derived from matched exome and RNA-seq data, which thus have an ascertainment bias towards coding variants and regions directly surrounding the exon–intron boundary. This benchmarking again highlighted significant differences in the performance of splicing detection tools, with Introme consistently outperforming all other tools, and halving the false positive rate of SpliceAI. To our knowledge, this, and the subsequent analysis of clinical variants, represents the most comprehensive benchmarking of splicing tools and likely reflects the diversity of variants that will be identified in real-world setting. Despite these efforts, there are relatively few examples of some splice altering variants , so more examples will need to be curated to fully evaluate performance in these difficult regions.BRCA1 screen, certain regions are prioritised to be screened, and often this excludes the vast majority of intronic material. Nevertheless, the results for BRCA1 ClinVar variants (auPRC: 0.96) suggest that accurate in silico analysis of splice-altering variants in any gene is feasible using such a method.High-throughput validation methods such as saturation mutagenesis screens are powerful, but currently only a few genes have been investigated in such depth. Additionally, as demonstrated with the PKD1 could identify atypical splice-altering variants that were overlooked by clinical whole genome sequencing, and subsequently validated using cDNA Sanger sequencing.The assessment of Introme on 93 consecutive variants submitted by a diagnostic laboratory reflects a common scenario where clinical genome analysts have carefully selected variants of uncertain significance that require additional functional validation prior to reporting. Designing RT-PCR assays to validate the impact of a variant on splicing demands accurate prediction as to the likely functional impact of the variant on intron retention or exon skipping to know where to design primers. In situations where a high Introme score is obtained but is not supported by evidence from RT-PCR, careful review of assay design and results may be warranted, particularly where only one allele may be under investigation. We also showed that the splicing investigation of rare variants in Due to the large number of sequence elements and splicing factors involved, predicting the impact of a genetic variant upon splicing can be difficult. Introme combines some of the best splice-prediction tools available using a decision tree model that achieved an auPRC of 0.98. Introme proved to be of most value when high-confidence predictions were required, achieving a sensitivity of 0.89 at 0.98 specificity. Improved methods for the detection of splice-altering variants combined with the increased use of genome sequencing or targeted sequencing with inclusion of intronic sequences will lead to more splice-altering variants being identified and implicated in disease.Published variants that had been functionally tested for splicing abnormalities were collected and sorted into (1) those with a demonstrated impact on splicing (true positives) and (2) those with no impact on splicing (true negatives). Functional confirmation included minigene assay, patient-derived RNA-seq, or cDNA analysis. For a variant to be considered as splice-altering, it must be demonstrated to either produce a novel transcript or alter the ratio of existing transcripts compared to the sequence without the variant. If quantification of the transcripts was performed, the transcript(s) with altered splicing required a 10% change to be considered as splice-altering.Machine learning methods were applied using the “caret” R package (R version 4.0.4) . Models Introme reports on a variant’s likelihood of altering splicing by combining predictions from splice-scoring tools and general variant information with machine learning methods Fig. . The inpTo further improve the ability of Introme to identify splice-altering variants, we developed several novel features focussed on known splicing rules  was generated from a massively parallel splicing minigene reporter assay that focussed primarily on exonic variants and was sensitive to small changes in exon usage; therefore, the MFASS dataset is enriched for variants that affect exonic splicing enhancers or silencers (ESE/ESS). The ncVarDB dataset [n = 536) contains variants identified from publications and may include noncoding variants that do not affect splicing. Not all variants in this dataset have been functionally validated, and we used the author assertions regarding each variant’s pathogenicity. The Shiraishi dataset [n = 13,999) was derived from paired tumour exome and RNAseq data from The Cancer Genome Atlas (TCGA) [The MFASS dataset  (n = 105 dataset  (n = 536s (TCGA)  derived The splice-altering variants from MFASS (dPSI >  = 0.5) , ncVarDBBRCA1 [Variants used for the saturation mutagenesis comparison were sourced from a study that assayed 96.5% of all possible SNVs for 13 exons in BRCA1 . Each vaFour patients with suspected autosomal dominant polycystic kidney disease underwent clinical whole genome sequencing to at least 30 × depth, at Genome.One , and raw data was released for research use. Patients were consented for research use and analysed as described previously .Variants used for allele frequency assessment were obtained from Illumina’s InfiniumCore-24v1.2 BeadChip and sorted into six tranches based on gnomAD PopMax allele frequency . A randoAdditional file 1: Table S1. Experimentally validated variants from SpliceVarDB used to train and test Introme. Table S2. Variants experimentally validated using RT-PCR for splice-altering changes by SA Pathology. Table S3. Features in Introme. Table S4. Variants used for allele frequency assessment.Additional file 2: Figure S1. Comparison of in silico splice-prediction tools on validated non-splice-altering variants. Using an UpSet plot, variants identified here by one or more tools are in silico false positives. The CADD and CADD-splice tools contributed the largest number of false positives. Figure S2. Novel Functions incorporated into Introme. A: Position Weight Matricesfor the exonic splicing enhancer motifs from ESEfinder [Figure S3. Importance of features included in Introme. Feature importance is an estimate of the contribution of each variable to the model. Boxes are coloured and labelled according to the source of the feature annotated. Figure S4. Overview of the methods and data sources for each section. Figure S5. Performance of in silico splice-prediction tools on three validation data sets. Precision recall curves and the corresponding positions of the splice-altering variants in the dataset for A-B: ncVar, C-D: MFASS and E-F: Shiraishi. Figure S6. Performance of in silico splice-prediction tools on three validation data sets, broken down by regions.SEfinder  showing SEfinder . C: NormAdditional file 3. Review History.


This review aimed to explore the available literature to update our understanding of the long head of biceps (LHB) at the shoulder. Synthesise our findings to identify emergent themes and knowledge gaps to inform future research and management directions.PubMed, Embase, Cinahl, SportDiscus, CENTRAL, and Web of Science were searched from inception to 31st December 2021. Articles were included if they referenced adult participants > 18 years of age and were written in English.214 articles were included in the final analysis, and results were categorised into six emergent themes: (1) Anatomy - Normal anatomical variation of the biceps from aberrant origins, third and fourth accessory heads, and an absence of the LHB tendon (LHBT) are not necessarily benign, with shoulder pain and instability a commonly reported theme. (2) Function - Bicep’s role in glenohumeral elevation and stability in healthy shoulders is minimal. In contrast, LHB has a more significant role in shoulder stability and humeral head depression in subjects with rotator cuff failure or an absent LHBT. (3) Pathology - There is an association between LHB tendinopathy, rotator cuff disease, LHBT instability and occult rotator cuff tears. Early recruitment and hyperactivity of the LHB in subjects with symptomatic rotator cuff tears and instability suggest a potential compensatory role. (4) Assessment - The limited diagnostic utility of special orthopaedic tests in assessing LHBT pathology was a consistent theme. The utility of magnetic resonance imaging and ultrasound to identify full-thickness tendon tears and instability of the LHBT was moderate to high. However, the utility of clinical tests and imaging may be underestimated due to arthroscopy’s limitations in fully visualising the proximal LHBT. (5) Non-Surgical Management - Ultrasound-guided injections into the biceps sheath show greater accuracy and patient outcomes than blinded injections; however, the entry of injectate into the intraarticular glenohumeral joint may have unwanted complications. (6) Surgical management - For the surgical management of biceps pathology with or without rotator cuff pathology, both biceps tenodesis and tenotomy report similar improvements in pain without any significant adverse effect on strength or function. Tenodesis favoured higher overall constant scores and a lower incidence of Popeye deformity and cramping arm pain, with tenotomy trending to be more cost and time effective. For patients with a healthy LHBT, rotator cuff repair with adjunctive tenodesis or tenotomy fails to provide additional clinical improvements compared to rotator cuff repair in isolation.The scoping review highlights the variability of biceps anatomy, which is not necessarily benign and suggests a minimal role of the LHB in shoulder elevation and stability in healthy individuals. In contrast, individuals with rotator cuff tears experience proximal humeral migration and demonstrate hyperactivity of the LHB, suggesting a potential compensation role. The observed prevalence of LHBT pathology with rotator cuff tears is well established; however, the cause-and-effect relationship between LHBT pathology and rotator cuff disease is undetermined. The diagnostic utility of clinical tests and imaging to exclude LHBT pathology may be understated due to the limitations of arthroscopy to visualise the proximal LHBT fully. Rehabilitation programs for the LHB are understudied. Similar post-surgical clinical outcomes are observed for tenodesis and tenotomy for biceps and rotator cuff-related shoulder pain. Subjects undergoing biceps tenodesis are less likely to have cramping arm pain and a Popeye deformity than patients undergoing biceps tenotomy. The significance of routine surgical removal of the LHBT and sequelae on rotator cuff tear progression to failure and long-term shoulder function is unknown, and further research is required.OSF: https://osf.io/erh9mThe online version contains supplementary material available at 10.1186/s12891-023-06346-5. The purpose of the Long Head of the Biceps (LHB) at the shoulder is an enigma. Its functional role at the shoulder and its contribution to glenohumeral joint arthrokinematics and stability remain poorly understood , 2. AsseIn contrast, there is a plethora of literature on the surgical management (tenodesis vs. tenotomy) of LHB-related shoulder pain. Often surgical recommendations for routine LHB tenodesis/tenotomy with rotator cuff tears are dubious because the functional role of the LHB at the shoulder remains uncertain , 6. ConsOther fundamental questions about the LHB also remain unanswered. With the relationship between proprioception deficits at the shoulder and glenohumeral joint instability still unclear , perhapsIn summary, the function of the LHB at the shoulder remains poorly understood. Whilst previous narrative reviews , 2 proviThe objectives of this review were: 1) review the research on (a) normal anatomy and function of the LHB at the shoulder, (b) abnormal pathology and assessment findings of the LHBT, (c) non-surgical and surgical management options for LHB-related shoulder pain and (d) functional impacts and disease sequelae of routine LHBT surgery in the operative management of rotator cuff related shoulder pain 2) synthesise findings, and 3) identify emergent themes and knowledge gaps for future research.https://osf.io/erh9m on September 12, 2021.A priori protocol was developed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Extension for Scoping Reviews (PRISMA-ScR): Checklist  undertook an initial pilot search of PubMed and Google scholar to identify articles on the topic and map key concepts. To develop a complete search strategy, synonyms were identified from text words in the titles and abstracts of relevant articles and the index terms used to describe the articles. A comprehensive search strategy, including all identified keywords and subject/index terms, was developed for PubMed and adapted using Polyglot [The lead author Polyglot  for all (BD). Potential studies were retrieved in full text and assessed in detail against the eligibility criteria for inclusion in the scoping review. Full-text studies that did not meet inclusion criteria were excluded, and the reasons for exclusion were recorded and reported in the PRISMA Flow Diagram - Fig. 1  regardless of gender, a commonly used cut-off to distinguish the point between adolescence and adulthood.Any published peer-reviewed literature reporting on the LHB’s role, function, or management at the shoulder and their outcomes.All full-text research articles produced in any year were eligible for inclusion. Exclusion criteria were defined as (1) non-English language, (2) no access to full text and (3) grey literature, including narrative literature reviews, thesis/dissertations, conference abstracts/proceedings, opinion pieces, magazine, and newspaper articles. Morrison, Polisena  found no(BD) using the JBI - levels of evidence guidelines and supporting documentation [(HK), with eighteen discrepancies resolved with the assistance of a co-author (WH).Whilst the use of a critical appraisal tool was not required for this scoping review  – Methodology for JBI scoping reviews , 12, 17. – Methodentation . The levData from publications meeting eligibility criteria were extracted into customised tables. The data extraction tables were modified and revised iteratively during screening for each included study. Data charted in the final extraction tables included the author’s citation details, year of study, level of evidence and key study findings.Studies were initially categorised according to three main domains (1) normal, (2) abnormal and (3) management. Key study characteristics and raw data were tabulated for each domain. Synthesis of key findings was performed to identify emergent themes and key concepts.The search results are displayed in the PRISMA Flow Diagram - Fig. 1  has traditionally been from the supraglenoid tubercle and superior labrum, with its proximal tendon tracking distally through the rotator cuff interval where the biceps pulley envelops it and houses within the biceps groove. Upon exiting the biceps pulley, it travels under the transverse humeral ligament, where it joins the short head of the biceps to form the biceps brachii muscle belly, sharing a common distal tendon attachment onto the radial tuberosity ligament . Thirty-Of the thirty-nine articles on biceps brachii anatomy found, thirty-six papers reported anatomical variations from normal. Supplementary Table Of the twenty individual case studies in Supplementary Tables In this section of LHB function at the shoulder, forty-seven articles were categorised under the subthemes of (a) biceps electromyography, (b) shoulder biomechanics (Supplementary Table Twenty-seven studies used electromyography (EMG) to investigate the activity of the biceps brachii, as detailed in Supplementary Table Thirteen articles detailed in Supplementary Table In contrast, three studies found no significant or minimal activity of the LHB during shoulder elevation , 52, 121Six in vivo studies examined the role of the biceps brachii in shoulder stability, as detailed in Supplementary Table Thirteen in vitro cadaver studies detailed in Supplementary Table No direct evidence for or against the role of the LHB in proprioception at the shoulder was found. Two systematic reviews on proprioception and shoulder pain/pathology were found. Ager, Borms  reportedThirty-five diagnostic studies in Supplementary Tables As detailed in Supplementary Tables Concomitant rotator cuff pathology associated with LHB tendinopathy includes rotator cuff tears, Supraspinatus and Subscapularis tears, Supraspinatus tendinopathy and rotator cuff tendinopathy. A high association was observed between LHBT instability and rotator cuff pathology in twelve articles, inclusive of Subscapularis tears in eight articles , 203, isEight EMG studies were found directly supporting increased muscle activation of the biceps brachii in the presence of rotator cuff pathology and shoulder instability, as detailed in Supplementary Table Assessing the LHBT in the clinical examination can be completed in several ways. Fifty articles investigating the assessment of the LHBT pathology at the shoulder were categorised into several sub-themes, including (a) screening questionnaires and (b) clinical examination  and Arthrography (MRA), compared with arthroscopic surgery in seventeen of the eighteen studies found diagnosing proximal LHBT pathology at the shoulder, exclusive of SLAP lesions and labral pathology as detailed in Supplementary Table Ten studies examined the validity of diagnostic ultrasound in detecting LHBT pathology compared with arthroscopy in four studies, arthroscopy/open surgery in two, arthroscopy/arthrotomy in one and MRI in two studies, as detailed in Supplementary Table A single study on diagnostic injections for LHBT pathology reported high specificity but low sensitivity to exclude LHBT pathology . A cadavSupplementary Table In this section of Management, forty-one articles were categorised under non-surgical  vs. tenotomy (n = 6855). Twenty-two articles examined LHB tenodesis and tenotomy outcomes in subjects with LHBT-related shoulder pathology in isolation  were similar for both tenodesis and tenotomy, across the twenty-two articles found, with a minor trend for improved constant scores in favour of tenodesis in three articles , 224. A Of the six articles reporting outcomes of adjunctive biceps surgery for repairable and irreparable rotator cuff tears, similar levels of patient satisfaction and PROMS were observed across all studies, as detailed in Supplementary Table As detailed in Supplementary Tables Our scoping review observed considerable anatomical variation of the LHB from double or triple tendon aberrant origins and supernumerary third and fourth accessory heads to a congenital absence of the LHBT. These observed variations were associated with higher shoulder pain and instability prevalence. Morris, Guettler  and KanaThe role of the biceps brachii at the elbow joint and its contribution to elbow flexion and forearm supination is well documented and understood in the literature . Our scoThere was an established association between LHB tendinopathy and rotator cuff pathology and LHBT instability and occult Subscapularis tears in our scoping review, with EMG studies demonstrating hyperactivity of LHB in the presence of rotator cuff tears and shoulder instability, suggesting a compensation role of the LHB in pathological shoulders. Similar changes in muscle activation of the deep abdominal muscles have been established in people with chronic low back pain –239. OurThe limited diagnostic utility of screening questionnaires, special orthopaedic tests, and palpation in the differential diagnosis of LHBT pathology was a consistent theme in our scoping review. Due to the variable diagnostic utility of special orthopaedic tests of the shoulder , 246–255The American College of Radiology Appropriateness Criteria for Atraumatic Shoulder Pain recommends MRI or diagnostic ultrasound be performed when LHBT pathology is suspected, and initial radiographs are normal or inconclusive. Our scoping review findings support using MRA over MRI to diagnose LHBT appearance, position, and biceps pulley lesions for LHBT pathology. Most MRI and MRA studies reported a high utility for detecting full thickness and complete tears of the LHBT; however, the utility for MR imaging to detect and exclude partial thickness tears of the LHBT was low. Overall MR imaging to detect LHBT instability was found to be variable; though, there was an observed trend for higher specificity to rule in LHBT dislocation compared with subluxation. MRI and MRA sensitivity values were lower than the reported specificity values.Similar to our MR findings, several studies reported the higher diagnostic utility of ultrasound for biceps dislocation greater than subluxation and the detection of full-thickness tears of the LHBT. However, its ability to identify partial-thickness tears of the LHBT was less accurate. Similar findings were found for diagnosing biceps tendinopathy. Study comparisons between diagnostic ultrasound and MRI reported high specificity values for MRI greater than diagnostic ultrasound for proximal LHBT pathology, but sensitivity values for both were overall poor. A recent literature review by Ostrowski, Beaumont  found siThere were limited result findings for the conservative management of LHBT pathology due to the lack of articles found, with subjects managed non-surgically trending to return to work quicker but at lesser capacity and with less elbow/forearm strength than subjects undergoing LHB tenodesis. Similar to our observations, a systematic review by Castro, Corrêa  reportedThis review found no studies that compared LHB injection with no injection, indicating that the current literature does not provide guidance on the efficacy of injection for LHBT pathology. In contrast, a prior review reported that it might give temporary pain relief for inflammatory conditions of the LHBT . If a clFor the surgical management of long head of biceps pathology with or without rotator cuff pathology, our scoping review found similar improvements in patient-reported outcomes for pain and function post-operatively for tenodesis or tenotomy, with tenodesis trending towards higher constant scores and tenotomy trending to be more cost and time effective. At the same time, patients undergoing tenodesis were less likely to have post-surgical complications of Popeye deformity and cramping arm pain. A similar trend was observed in a recent systematic review by Aldon-Villegas, Perez-Cabezas , with feThe systematic inclusion of adjunctive LHB tenotomy or tenodesis on a healthy normal LHBT with rotator cuff repair has been reported as an increasing trend in the literature . Our fin(BD) independently performed the screening, inclusion, exclusion, and data extraction. Whilst the level of evidence for each article was assessed, the methodological quality of the studies was not appraised critically as per guidelines for completing scoping reviews. Articles biased towards rotator cuff pathology and intra-articular SLAP or labral pathology were excluded from this scoping review.This scoping review was limited to English publications, excluding full-text articles published in other languages. Previous narrative reviews and grey literature were excluded, including conference abstracts and thesis dissertations. The lead author (a) Anatomy – Common anatomical variations of the biceps brachii, associated with shoulder pain and instability, a potential role for the biceps sling in LHBT stability with minimal support for the transverse humeral ligament as a separate, distinct anatomical structure. (b) Function - the minimal role of the LHB in shoulder elevation and glenohumeral stability in healthy shoulders. In pathological shoulders, proximal humeral migration, and hyperactivity of the LHB suggest a potential compensation function in individuals with symptomatic rotator cuff tears or shoulder instability. However, changes in LHB muscle activity in subjects with asymptomatic rotator cuff pathology are undetermined. Further research is required in both asymptomatic and symptomatic rotator cuff tear populations to determine whether there is a compensation role of the LHB at the shoulder. (c) Pathology - The prevalence of concomitant LHBT pathology with rotator cuff tears is well established; however, the cause-and-effect relationship between LHBT pathology and rotator cuff disease is undetermined. Further research is required to establish if the LHBT becomes overloaded and, in turn, pathological as it tries to compensate for the loss of function of a torn rotator cuff or is a secondary effect of degenerative shoulder pathology, pain, and weakness. (d) Assessment - The diagnostic utility of both clinical orthopaedic tests and diagnostic imaging to exclude LHBT pathology may be understated due to the inherent limitations of arthroscopy as the standard gold reference to visualise the proximal LHBT at the glenohumeral joint fully. (e) Non-surgical management - Conservative rehabilitation programs of the shoulder that include biceps strengthening protocols are understudied, and the evidence to support the inclusion of LHB rehabilitation in the management of rotator cuff and biceps-related shoulder pain is lacking. Further research is required to understand how a biceps-focused rehabilitation program may improve shoulder pain and functional outcomes in patients with symptomatic rotator cuff tears and b) prevent or reduce the likelihood of an asymptomatic rotator cuff tear becoming symptomatic and progressing to failure. (f) Surgical management - Similar post-surgical clinical outcomes are observed for tenodesis and tenotomy for biceps and concomitant rotator cuff-related shoulder pain, with subjects undergoing biceps tenodesis less likely to have cramping arm pain and a Popeye deformity compared to patients undergoing biceps tenotomy. The significance of routine surgical removal of the LHBT and sequelae on rotator cuff tear progression to failure and long-term shoulder function is unknown, and further research is required.The scoping review highlights; Below is the link to the electronic supplementary material.Supplementary Material 1Supplementary Material 2Supplementary Material 3Supplementary Material 4Supplementary Material 5Supplementary Material 6Supplementary Material 7Supplementary Material 8Supplementary Material 9Supplementary Material 10Supplementary Material 11Supplementary Material 12Supplementary Material 13Supplementary Material 14Supplementary Material 15Supplementary Material 16Supplementary Material 17Supplementary Material 18Supplementary Material 19Supplementary Material 20Supplementary Material 21Supplementary Material 22


Self-disclosure builds high quality relationships, but knowledge of self-disclosure in youth mentoring relationships is limited by a lack of research and reliance on self-reports. To demonstrate the value of observational methods and dyadic modeling of mentoring communication processes, this study examined the associations between behavioral observation of self-disclosure and self-reported relationship quality in 49 mentee-mentor dyads . Video-recorded observations of disclosure were coded on three dimensions: amount (number of topics and detail of disclosure), intimacy , and openness (willingness to disclose). More intimate mentor disclosure was associated with higher mentee relationship quality, whereas higher amount of mentor disclosure combined with low intimacy was associated with lower mentee relationship quality. Greater mentee openness correlated with higher mentor relationship quality, but more intimate mentee disclosures were associated with lower mentee relationship quality. These preliminary findings illustrate the potential of methods that enable in-depth investigation of dyadic processes to advance understanding of how behavioral processes may influence mentoring relationships. The effectiveness of formal youth mentoring programs in producing positive developmental outcomes for adolescents is largely contingent on mentors and mentees building and sustaining quality relationships  or the receiver (partner), shaping the relationship quality of the other. Disclosure scholarship emphasizes the importance of The current study offers a proof-of-concept illustration of the value of observational methods and dyadic modeling of mentoring communication processes. The benefits behavioral observation methods offer—including bypassing self-report biases, differentiating between theoretically-relevant behavioral dimensions, assessing how both mentors and mentees behavior shapes the outcomes of each other—have led to calls for their increased use in youth mentoring research  valued their friendships more Fehr, . SimilarIn sum, the dyadic processes of self-disclosure described here recognize that mentor and mentee disclosure can have important effects on the discloser and their social partner see Fig. . The comBecause youth mentoring is a relationship-based intervention, a deeper understanding of communication processes that can facilitate mentor-mentee bonds is critical. While early studies have signaled a positive disclosure-relationship quality association when mentors disclose to mentees, it is also apparent the methods used in previous studies provide limited insights into how mentor and mentee evaluations of relationship quality are affected by dyadic disclosure interactions. This rationale informed two research aims for the study. The first aim was to use behavioral observation methods to illustrate the usefulness of such methods for understanding youth mentoring relationships. To do this, mentor-mentee dyads were video-recorded engaging in a discussion that was coded for the amount, intimacy, and openness of self-disclosure exhibited by both mentors and mentees during the dyadic interaction. The second aim was to investigate the partner and actor effects of mentors’ and mentees’ amount, intimacy, and openness of self-disclosure on relationship quality see Fig. . For parThe sample comprised of 49 youth mentoring dyads. Most dyads were female same-gender matches (69.4%), 26.5% were male same-gender matches, and 4.1% were different-gender matches. Mentors’ primary ethnic identification were NZ European (49%), Pasifika (14.3%), Māori (10.2%), Other European (10.2%), Asian (8.2%), and Other (8.1%). Mentees’ primary ethnic identification were Pasifika (51%), Māori (18.4%), Asian (14.3%), NZ European (10.2%) and Other/Unknown (6.1%). One-fifth of mentors (20.4%) and almost half of mentees (42.9%) identified with multiple ethnic backgrounds. Most dyads were cross-cultural (79.6%). Mentor age ranged from 19 to 59 years  and from 12 to 19 for mentees . Relationship length ranged from three to 25 months .Participants came from nine local youth programs in Auckland, New Zealand, a diverse urban area. Eight programs were community-based, while one was a school-based mentoring program. Programs varied in the purpose and approach to mentoring: three were focused on educational achievement and the transition from high school to university, two focused on leadership skills, one each focused on creative arts and life skills, and the remaining two delivered mentoring as part of general youth development support. Mentoring programs were initially approached via email with a brief on the study and a request to attend a program event  to advertise the study and collect contact information from interested pairs. Through this strategy, 46 dyads from six programs joined the study. Further recruitment occurred through social media (two pairs) and a youth mentoring conference (one pair). In addition to being part of a formal mentoring program, all pairs met two other study eligibility criteria: 1) a minimum relationship length criterion of three months to ensure all participating dyads had an established relationship to increase the likelihood the observed interactions were representative of how they interact under normal conditions; and 2) a mentee age criteria of 12–18 years, although one participant turned 19 between signing up for the study and then attending the research session.The study used an approach to data collection and coding based on observational methods used to assess processes in romantic relationships  and 7 (high) based on a holistic assessment of each dimension across the full seven minute recorded interaction. Ratings of amount captured how much the mentor/mentee revealed information about themselves to their partner. Coders considered both the number of incidences of self-disclosure as well as the amount of information revealed in each instance of disclosure. Ratings of intimacy assessed how much the discloser revealed personal or intimate facts about themselves. Intimacy was rated bearing in mind the context of the interactions occurring within a mentoring relationship between an adult and young person, rather than the type and level of intimacy in other types of relationships . Finally, ratings of openness assessed how much the discloser appeared to be genuinely trying to open up and share themselves with their partner (see Online Resource 1 for full coding schedule).Mentors and mentees completed the same relationship quality measure, which involved rating their relationship on a 7-point scale  for six dimensions associated with their relational bond: closeness, commitment, enjoyment, liking, satisfaction, and trust  compared to mentors . Mentee disclosure was also more intimate  than mentors , and mentees expressed greater openness  compared to mentors . Self-reported relationship quality was high for both mentees  and mentors . Bivariate correlations , but not when mentors’ disclosure was high in intimacy . Equivalent models testing the amount X openness and intimacy X openness interactions were also run. No significant interactions emerged in predicting mentee or mentor relationship quality.The secondary analyses examined whether the disclosure variables combined to predict relationship quality. For example, considering the two significant partner effects of mentor disclosure on mentee relationship quality, an expected interaction between amount and intimacy of disclosure could reveal that mentees’ evaluate their relationship more negatively when they are paired with mentors who display high amounts of disclosure with lower intimacy. To test this possible combination, primary analyses were rerun with actors’ amount X intimacy interaction and partners’ amount X intimacy interaction added into the model. One significant interaction emerged , mentees’ own intimate disclosure was associated with lower mentee relationship quality (actor effect). These contrasting associations are somewhat at odds with theoretical models of disclosure as a reciprocal process where both partners progressively increase the intimacy of their disclosures, which deepens and solidifies the relationship. Yet, there are some plausible reasons for this pattern to occur in youth mentoring dyads in particular. First, the youth-adult dynamic is embedded in distinct power relations and developmental processes . Additional behavioral observation research on communication behaviors across a range of youth-adult partnerships would contribute importantly to training for adults working in professional and paraprofessional helping roles with young people, as well as the development of more targeted, evidence-informed interventions, as seen in research on other close relationships (see Heyman, Self-disclosure is a communication tool for building and deepening interpersonal relationships that is not well understood in the youth mentoring context. This study used behavioral observations of mentor-mentee interactions to examine whether self-disclosure differentially influences relationship quality depending on who is disclosing, and how. The findings showed some positive partner effects of disclosure: more intimate mentor disclosures predicted higher mentee relationship quality, and greater mentee openness predicted higher mentor relationship quality. Importantly, however, negative associations were also revealed: high amounts of low intimacy mentor disclosures and more intimate mentee disclosures predicted lower mentee relationship quality. These preliminary results are indicative of the unique impact disclosure has on mentees—whether it is their own or their mentor’s—and reinforces the fundamental orientation of mentoring practice that prioritizes mentee experiences and outcomes. The study also highlight the utility of applying well-established close relationship theories and methodologies to the mentoring context to draw out the idiosyncrasies of mentor-mentee relationships that must inform training and practice. Despite being a small study, it is illustrative of the potential knowledge contributions such methods offer and thus provide a foundation for larger-scale application of these methods. Youth mentoring interventions are popular during adolescence and continuing to build a robust evidence base of process-oriented research makes a valuable contribution towards enhancing the effectiveness of mentoring.Supplementary Information


Epidermal growth factor receptor (EGFR) is one of the most well-studied oncogenes with roles in proliferation, growth, metastasis, and therapeutic resistance. This intense study has led to the development of a range of targeted therapeutics including small-molecule tyrosine kinase inhibitors (TKIs), monoclonal antibodies, and nanobodies. These drugs are excellent at blocking the activation and kinase function of wild-type EGFR (wtEGFR) and several common EGFR mutants. These drugs have significantly improved outcomes for patients with cancers including head and neck, glioblastoma, colorectal, and non-small cell lung cancer (NSCLC). However, therapeutic resistance is often seen, resulting from acquired mutations or activation of compensatory signaling pathways. Additionally, these therapies are ineffective in tumors where EGFR is found predominantly in the nucleus, as can be found in triple negative breast cancer (TNBC). In TNBC, EGFR is subjected to alternative trafficking which drives the nuclear localization of the receptor. In the nucleus, EGFR interacts with several proteins to activate transcription, DNA repair, migration, and chemoresistance. Nuclear EGFR (nEGFR) correlates with metastatic disease and worse patient prognosis yet targeting its nuclear localization has proved difficult. This review provides an overview of current EGFR-targeted therapies and novel peptide-based therapies that block nEGFR, as well as their clinical applications and potential for use in oncology. Discovered in 1965 by Cohen  and consCetuximab was the first EGFR targeted therapeutic antibody to gain FDA approval in 2004 and acts by competitively inhibiting the ligand binding pocket to prevent activation  12]. In. In12]. Antibody-drug conjugates (ADCs) targeting EGFR have also shown promise in treating certain cancers. One of the first ADCs was an EGFR targeted antibody (mAb108), which was conjugated to the DNA intercalating agent, doxorubicin, in 1989 . This ADAnother group has generated an antibody conjugate for combination therapy by creating a multilayered sphere called, anti-EGFR-PTX-TCS-GNS. The layers from the innermost are a silica sphere, gold shell, thiol chitosan, paclitaxel, and EGFR directed antibodies . This coNanobodies are camel-derived antibodies that lack the antibody light chain. One of the first successful nanobodies targeted EGFR to block epidermal growth factor (EGF) binding and EGFR phosphorylation and showed promised in xenograft models, primarily the A431 xenograft model . Since tin vitro and ex vivo studies, this bispecific nanobody induced degranulation of NK cells.Subsequently, the creation of bispecific nanobodies (2 fused nanobodies which bind different proteins) with an αEGFR-αEGFR-αAlbumin nanobody, which binds albumin in the blood to reduce renal clearance and increase tumor delivery . This naTKIs are widely used in cancers with EGFR tyrosine kinase activating mutations as drivers, most effectively in lung adenocarcinoma, specifically NSCLC . In NSCLWhile first and second generation TKIs have shown significant clinical impact, the majority of tumors tend to acquire resistance to these drugs within a year . While sO-glycosylated N-terminal extracellular domain [In TNBC, EGFR is frequently found amplified and overexpressed, but not mutated. In these tumors, it is observed in intracellular locations in addition to the plasma membrane . Severalr domain . In healr domain . Howeverr domain . Concurrr domain . This inr domain   domain . The PX EGFR has several roles in the nucleus that can be either kinase dependent or more often kinase independent . While EnEGFR has also been linked to resistance to radiotherapy through the activation of DNA repair pathways . InfrareThe non-canonical trafficking and activities of EGFR may drive resistance to conventional therapies in several ways. The presence of EGFR within intracellular endosomes or the nucleus would prevent cell impermeable antibodies from reaching the receptor. Further, antibodies like cetuximab which act by competitively inhibiting the ligand binding pocket would not be effective as the ligand is already bound, and receptor activated and internalized . AntibodThe nuclear accumulation of EGFR represents an ideal target for therapeutic intervention as it appears to rarely occur outside the context of cancer, yet drives tumor progression, therapeutic resistance, and correlates with worse patient outcomes –71. nEGFSeveral therapeutic agents have been developed to target the retrograde trafficking of EGFR, primarily by blocking one of several protein interactions which drive this trafficking. At the plasma membrane in unpolarized epithelia during tumor progression, EGFR forms a complex with MUC1. This complex initiates a series of events that drive EGFR retrograde trafficking and has been targeted with several peptide-based inhibitors. These therapeutic peptides typically mimic some portion of the binding interface to act as a competitive inhibitor once introduced to the cell. However, therapeutic peptides are typically too large and charged or polar to be readily cell permeable. To allow cell penetration, a protein transduction domain is added to these peptides, allowing them to freely enter the cell .The Schroeder lab and others have previously produced therapeutic cell penetrating peptides that target the interaction of EGFR and MUC1. The first peptide generated, PTD4-MUC1-inhibitory-peptide (PMIP), based on the cytoplasmic domain of MUC1 which interacts with EGFR, initiating its retrograde trafficking  Table 1Table 1. Alternatively, an EJ-1 was generated to interfere directly with the nuclear localization sequence of EGFR  Table 1Table 1. Recently, the Schroeder lab targeted the endosomal trafficking protein SNX1 to generate a peptide that mimics the interaction domain between EGFR and SNX1, called cSNX1.3 , Table 1Of note, in cell culture experiments, cSNX1.3 had no effect on EGFR signal transduction, internalization, or degradation. This indicates that results observed were not due to an effect on canonical activities of EGFR. Rather, cSNX1.3 seemed to only effect the retrograde trafficking of EGFR, further highlighting the importance of this pathway for the understanding and treatment of cancer. These and other peptide-based therapeutics that block protein-protein interactions hold promise for future clinical therapeutics.EGFR is a complex protein that plays roles in many aspects of tumor growth and metastasis. Many drugs have been designed to target well characterized aspects of EGFR biology like ligand binding and kinase signaling. TKIs and antibody-based therapies have significantly improved many patient outcomes over several decades. However, tumors often develop resistance to these drugs either through activation of other signal transduction pathways or through additional mutations. In cases where there is an abundance of nEGFR these drugs don’t often work. nEGFR is a major driver of tumor progression, metastasis, and resistance to anti-EGFR therapies and has been suggested to be a better biomarker than total cell EGFR levels.The tumor specificity of nEGFR makes it a potentially valuable therapeutic target as nEGFR is rarely seen outside the context of cancer. This tumor specificity is in stark contrast to the roles of EGFR’s kinase domain which are critical in a majority of human tissues at nearly all developmental stages. The reliance on EGFR to develop and maintain human tissues, including the skin and gastrointestinal (GI) tract, explains many side effects seen with anti-EGFR therapies including rash, nausea, and diarrhea.As has been demonstrated with several peptide inhibitors of EGFR retrograde trafficking, nEGFR is a druggable target. The trafficking of EGFR to the nucleus requires several protein interactions that alter the posttranslational modification seen on EGFR, leading to a switch from lysosomal degradation to nuclear trafficking. The interactions of EGFR with MUC1 and SNX1 have both been targeted and shown efficacy in animal mouse tumor models. The interaction of EGFR and MUC1 is an upstream step in the nuclear trafficking of EGFR and might induce the degradation of EGFR in addition to the loss off nuclear localization making it an ideal anti-nEGFR therapy. In contrast targeting a nEGFR trafficking protein, like SNX1, is further downstream and is unlikely to induce EGFR degradation. However, targeting SNX1 might have additional benefits that have not been fully characterized. SNX1 binds EGFR on the kinase domain and induces the retrograde trafficking of EGFR. SNX1 also binds several other RTKs that have also been shown to drive oncogenesis with their nuclear activities. The peptide cSNX1.3 which was designed to block the interaction of EGFR and SNX1 inhibited 2 dimensional (2D) cell migration driven by EGFR. cSNX1.3 also inhibited migration driven by HER3 and c-Met, which are both RTKs shown to interact with SNX1. They undergo nuclear translocation and drive oncogenesis from within the nucleus suggesting the nuclear localization of RTKs more broadly could be a target for therapeutic intervention and targeting sorting proteins could be an avenue to a broad acting anti-RTK retrograde trafficking therapy.


The ability to accurately predict essential genes intolerant to loss-of-function (LOF) mutations can dramatically improve the identification of disease-associated genes. Recently, there have been numerous computational methods developed to predict human essential genes from population genomic data. While the existing methods are highly predictive of essential genes of long length, they have limited power in pinpointing short essential genes due to the sparsity of polymorphisms in the human genome.Motivated by the premise that population and functional genomic data may provide complementary evidence for gene essentiality, here we present an evolution-based deep learning model, DeepLOF, to predict essential genes in an unsupervised manner. Unlike previous population genetic methods, DeepLOF utilizes a novel deep learning framework to integrate both population and functional genomic data, allowing us to pinpoint short essential genes that can hardly be predicted from population genomic data alone. Compared with previous methods, DeepLOF shows unmatched performance in predicting ClinGen haploinsufficient genes, mouse essential genes, and essential genes in human cell lines. Notably, at a false positive rate of 5%, DeepLOF detects 50% more ClinGen haploinsufficient genes than previous methods. Furthermore, DeepLOF discovers 109 novel essential genes that are too short to be identified by previous methods.The predictive power of DeepLOF shows that it is a compelling computational method to aid in the discovery of essential genes.The online version contains supplementary material available at 10.1186/s12859-023-05481-z. Then, we obtained 18,797 human-mouse orthologs from the Mouse Genome Database [https://github.com/macarthur-lab/gene_lists). Finally, we obtained 364 OMIM dominant-negative genes from a previous study [We downloaded 311 ClinGen haploinsufficient genes and 404 mouse genes where heterozygous knockouts resulted in lethality from the GitHub repository for gnomAD  that would show this comparison, we first needed to match each essential gene with a nonessential gene containing a similar expected number of LOF variants. To this end, we first constructed a nonessential gene set for each of the essential gene sets that were of matching size. We matched each essential gene with a nonessential gene of similar expected number of LOF variants using MatchIt . For theWe obtained comparable numbers of LOF-intolerant genes from DeepLOF, LOEUF, VIRLOP, and CoNeS. First, we obtained 2835 LOF-intolerant genes from LOEUF using an established cutoff of 0.35 [We evaluated the enrichment of ClinGen haploinsufficient genes, human orthologs of mouse essential genes, and human genes essential for the survival of cell lines in the 109 LOF-intolerant genes uniquely predicted by DeepLOF. For each essential gene set, we defined the other genes as nonessential genes. Also, we defined LOF-tolerant genes as those genes with P-value of the permutation test was defined as the fraction of permutations where the proportion of deletions overlapping random genes was equal to or smaller than the observed proportion in empirical data.We evaluated the depletion of the 109 LOF-intolerant genes uniquely predicted by DeepLOF in benign genomic deletions. To this end, we obtained clinical structural variants from the nstd102 study in dbVar  and retrDeepLOF is an evolution-based deep learning model for inferring protein-coding genes intolerant to LOF mutations. The key variable of interest in DeepLOF is entclass1pt{minimay LOF variants in a gene given n, where n is the expected number of LOF variants in the same gene under a neutral mutation model . Thus, benign genomic deletions were depleted with the 109 novel LOF-intolerant genes predicted by DeepLOF.We hypothesized that the 109 novel LOF-intolerant genes predicted by DeepLOF might be depleted in benign genomic deletions due to the detrimental effects of deletions overlapping LOF-intolerant genes. To test this hypothesis, we obtained 5,649 benign genomic deletions overlapping protein-coding genes from dbVar . We obseFinally, we further investigated the 109 short genes uniquely predicted by DeepLOF by conducting a GO enrichment analyses on the 109 genes. We used The Database for Annotation, Visualization and Integrated Discovery (DAVID) , 54 and An example of a critical developmental gene determined by DeepLOF to be LOF-intolerant was HAND2. HAND2 is involved during cardiac development. HAND proteins are involved in the development of ventricular chambers and aortic arch arteries . As suchIn the 109 DeepLOF uniquely predicted genes, we also found significant enrichment for several genes associated with various ribosomal proteins. Ribosomal proteins are responsible for many important functions and dysfunction can lead to serious complications. Diamond-Blackfan anemia (DBA) is a rare disease in which patients’ bone marrow fails to produce enough red blood cells. The disease also is responsible for malformations in the hands, face, or heart in approximately 50% of DBA patients. Haploinsufficient mutations in various ribosomal proteins have been implicated in causing this serious disease . TSR2 waFull names, symbols and Ensembl ID of all other genes uniquely predicted by DeepLOF can be found in Additional file We present an evolution-based machine learning framework, DeepLOF, for predicting human genes intolerant to LOF mutations. Unlike previous LOF intolerance scores, such as pLI and LOEUF, the DeepLOF model leverages both population and functional genomic data to predict LOF intolerance. Therefore, DeepLOF may be particularly powerful in predicting short essential genes without sufficient polymorphisms for selection inference. Furthermore, unlike supervised methods, DeepLOF does not use known essential genes as training data. Thus, it may not suffer from the pitfalls of supervised machine learning, such as the potential leakage of information from training data to test data and the ascertainment bias in human-annotated essential genes.The linear DeepLOF model without hidden layer allows us to directly estimate the association of a genomic feature with LOF intolerance after adjusting for other genomic features Fig. a. Using We also show that genes encoding transcription factors or protein complex subunits and genes associated with developmental processes may be highly intolerant to LOF mutations Fig. a. PrevioWhile both genomic features and population genomic data are predictive of LOF intolerance, their relative importance may depend on the length of a gene. In short genes where population genomic data provide limited information on negative selection, it is critical to incorporate genomic features to improve the inference of LOF intolerance. In contrast, in long genes where polymorphisms are abundant, population genomic data may be more informative than genomic features because they directly reflect LOF intolerance at the organism level. Because DeepLOF infers the relative rate of LOF variants, ner Fig. b.By integrating genomic features and population genomic data, DeepLOF outperforms alternative methods in predicting essential genes Fig. . BecauseWe observe that the predictive power of DeepLOF and other methods in disease gene prediction depends on the genetic mechanism of a disease. Notably, DeepLOF is outperformed by a missense intolerance score, UEECON-G, in the prioritization of dominant-negative disease genes  predicted the gene to be LOF-intolerant.Additional file 5. Data File 4:  File containing the 109 LOF-intolerant genes uniquely predicted by DeepLOF. The file shows gene IDs and brief description of each gene.