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Introduction: The immune response after transplantation depends on recipient/donor HLA allele mismatches. To enhance our understanding of the relations of HLA alleles in terms of amino-acid polymorphisms and shared epitopes, we assessed pairwise sequence difference between HLA-alleles., Methods: We translated amino-acid sequences of confirmed eplets into an atlas of HLA class I and II antigens, followed by visualization of the pairwise allele distances by means of antigen-specific disparity graphs in differential amino-acid space. We obtained an overview of relationships of all alleles of an antigen, corresponding similarity/dissimilarity structures, outliers, alleles with similarity to different antigen groups. Additionally, we calculated prevalence of the amino-acids for each polymorphic sequence position and visualized them in amino-acid motif plots of all alleles belonging to an antigen., Results: Our visualizations show strongly varying intra-group heterogeneity of HLA class I and II alleles, as well as shared inter-group and inter-locus eplets and epitopes, indicating a benefit of epitope-based transplant matching: Single allele recipient/donor mismatches potentially refer to identical eplets, or to a set of multiple mismatched eplets., Discussion: This data reveals inconsistencies in the HLA group nomenclature and consequently adds a new level of quality to allocation, motivating the definition of tolerable or taboo mismatches., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Doxiadis, Lehmann, Lachmann and Loeffler-Wirth.)

Disulfide-rich peptides such as defensins play diverse roles in immunity and ion channel modulation, as well as constituting the bioactive components of many animal venoms. We investigated the structure and bioactivity of U-RDTX-Pp19, a peptide previously discovered in venom of the assassin bug Pristhesancus plagipennis. Recombinant Pp19 (rPp19) was found to possess insecticidal activity when injected into Drosophila melanogaster. A bioinformatic search revealed that domains homologous to Pp19 are produced by assassin bugs and diverse other arthropods. rPp19 co-eluted with native Pp19 isolated from P. plagipennis, which we found is more abundant in hemolymph than venom. We solved the three-dimensional structure of rPp19 using 2D 1 H NMR spectroscopy, finding that it adopts a disulfide-stabilized structure highly similar to known trans-defensins, with the same cystine connectivity as human α-defensin (I-VI, II-IV, and III-V). The structure of Pp19 is unique among reported structures of arthropod peptides., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Sebaceous glands (SG) and their oily secretion (sebum) are indispensable for maintaining skin structure and function, and their deregulation causes skin disorders including but not limited to acne. Recent studies also indicate that sebum may have important immunomodulatory activities and may influence whole-body energy metabolism. However, the progressive transcriptional changes of sebocytes that lead to sebum production have never been characterized in detail. Here, we exploited the high cellular resolution provided by sebaceous hyperplasia and integrated spatial transcriptomics, pseudo time analysis, RNA velocity, and functional enrichment to map the landscape of sebaceous differentiation. Our results were validated by comparison with published SG transcriptome data and further corroborated by assessing the protein expression pattern of a subset of the transcripts in the public repository Human Protein Atlas. Departing from four sebocyte differentiation stages generated by unsupervised clustering, we demonstrate consecutive modulation of cellular functions associable with specific gene sets, from cell proliferation and oxidative phosphorylation via lipid synthesis to cell death. Both validation methods confirmed the biological significance of our results. Our report is complemented by a freely available and browsable online tool. Our data provide the first high-resolution spatial portrait of the SG transcriptional landscape and deliver starting points for experimentally assessing novel candidate molecules for regulating SG homeostasis in health and disease., Competing Interests: Conflict of interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Objective: In a cooperative study of the University Hospital Leipzig, University of Leipzig, and the Charité Berlin on kidney transplant patients, we analysed the occurrence of HLA-specific antibodies with respect to the HLA setup of the patients. We aimed at the definition of specific HLA antigens towards which the patients produced these antibodies., Methods: Patients were typed for the relevant HLA determinants using mainly the next-generation technology. Antibody screening was performed by the state-of-the-art multiplex-based technology using microspheres coupled with the respective HLA alleles of HLA class I and II determinants., Results: Patients homozygous for HLA-A * 02, HLA-A * 03, HLA-A * 24, HLA-B * 07, HLA-B * 18, HLA-B * 35, HLA-B * 44, HLA-C * 03, HLA-C * 04 , and HLA-C * 07 in the class I group and HLA-DRB1 * 01, HLA-DRB1 * 03, HLA-DRB1 * 07, HLA-DRB1 * 15, HLA-DQA1 * 01, HLA-DQA1 * 05, HLA-DQB1 * 02, HLA-DQB1 * 03(7), HLA-DQB1 * 06, HLA-DPA1 * 01 , and HLA-DPB1 * 04 in the class II group were found to have a significant higher antibody production compared to the heterozygous ones. In general, all HLA determinants are affected. Remarkably, HLA-A * 24 homozygous patients can produce antibodies towards all HLA-A determinants, while HLA-B * 18 homozygous ones make antibodies towards all HLA-B and selected HLA-A and C antigens, and are associated with an elevation of HLA-DRB1, parts of DQB1 and DPB1 alleles. Homozygosity for the HLA class II HLA-DRB1*01 , and HLA-DRB1 * 15 seems to increase the risk for antibody responses against most of the HLA class I antigens (HLA-A, HLA-B, and HLA-C) in contrast to HLA-DQB1 * 03(7) where a lower risk towards few HLA-A and HLA-B alleles is found. The widely observed differential antibody response is therefore to be accounted to the patient's HLA type., Conclusion: Homozygous patients are at risk of producing HLA-specific antibodies hampering the outcome of transplantation. Including this information on the allocation procedure might reduce antibody-mediated immune reactivity and prevent graft loss in a patient at risk, increasing the life span of the transplanted organ., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Loeffler-Wirth, Lehmann, Lachmann and Doxiadis.)

A crucial feature of life is its spatial organization and compartmentalization on the molecular, cellular, and tissue levels. Spatial transcriptomics (ST) technology has opened a new chapter of the sequencing revolution, emerging rapidly with transformative effects across biology. This technique produces extensive and complex sequencing data, raising the need for computational methods for their comprehensive analysis and interpretation. We developed the ST browser web tool for the interactive discovery of ST images, focusing on different functional aspects such as single gene expression, the expression of functional gene sets, as well as the inspection of the spatial patterns of cell-cell interactions. As a unique feature, our tool applies self-organizing map (SOM) machine learning to the ST data. Our SOM data portrayal method generates individual gene expression landscapes for each spot in the ST image, enabling its downstream analysis with high resolution. The performance of the spatial browser is demonstrated by disentangling the intra-tumoral heterogeneity of melanoma and the microarchitecture of the mouse brain. The integration of machine-learning-based SOM portrayal into an interactive ST analysis environment opens novel perspectives for the comprehensive knowledge mining of the organization and interactions of cellular ecosystems., Competing Interests: The authors declare no conflicts of interest.

The efficiency of the weak s process in low-metallicity rotating massive stars depends strongly on the rates of the competing ^{17}O(α,n)^{20}Ne and ^{17}O(α,γ)^{21}Ne reactions that determine the potency of the ^{16}O neutron poison. Their reaction rates are poorly known in the astrophysical energy range of interest for core helium burning in massive stars because of the lack of spectroscopic information (partial widths, spin parities) for the relevant states in the compound nucleus ^{21}Ne. In this Letter, we report on the first experimental determination of the α-particle spectroscopic factors and partial widths of these states using the ^{17}O(^{7}Li,t)^{21}Ne α-transfer reaction. With these the ^{17}O(α,n)^{20}Ne and ^{17}O(α,γ)^{21}Ne reaction rates were evaluated with uncertainties reduced by a factor more than 3 with respect to previous evaluations and the present ^{17}O(α,n)^{20}Ne reaction rate is more than 20 times larger. The present (α,n)/(α,γ) rate ratio favors neutron recycling and suggests an enhancement of the weak s process in the Zr-Nd region by more than 1.5 dex in metal-poor rotating massive stars.

Background: HLA epitopes are currently in the focus of transplantation immunogenetics. The main reason is the complexity of the HLA system with >38,000 alleles, the number of which increases steadily. These alleles are determined by the current state-of-the art typing methods like second- and third-generation sequencing. Screening for HLA antibodies is hampered by the lack of specific target beads with all possible alleles described., Summary: A way to circumvent the problem is to define HLA epitopes. The number of antibody-confirmed epitopes, on the other hand, was found to be 72 for HLA class I and 74 for HLA class II. Here, we elaborate on the current knowledge on these HLA epitopes. Absolute definitions of these structures are not yet available., Key Messages: Making use of eplets is a comparable way allowing statistical analyses. However, one should keep in mind that the results obtained are approximative or perhaps better associative. Continuous collaboration is needed for the full understanding of the HLA epitopes. The reactivity toward epitopes remains patient-specific., Competing Interests: The authors have no conflicts of interest to declare., (© 2024 The Author(s). Published by S. Karger AG, Basel.)

Serological assays for SARS-CoV-2 play a pivotal role in the definition of whether patients are infected, the understanding of viral epidemiology, the screening of convalescent sera for therapeutic and prophylactic purposes, and in obtaining a better understanding of the immune response towards the virus. The aim of this study was to investigate the performance of a bead-based multiplex assay. This assay allowed for the simultaneous testing of IgG antibodies against SARS-CoV-2 spike, S1, S2, RBD, and nucleocapsid moieties and S1 of seasonal coronaviruses hCoV-22E, hCoV-HKU1, hCoV-NL63, and hCoV-OC43, as well as MERS and SARS-CoV. We compared the bead-based multiplex assay with commercial ELISA tests. We tested the sera of 27 SARS-CoV-2 PCR-positive individuals who were previously tested with different ELISA assays. Additionally, we investigated the reproducibility of the results by means of multiple testing of the same sera. Finally, the results were correlated with neutralising assays. In summary, the concordance of the qualitative results ranged between 78% and 96% depending on the ELISA assay and the specific antigen. Repeated freezing-thawing cycles resulted in reduced mean fluorescence intensity, while the storage period had no influence in this respect. In our test cohort, we detected up to 36% of sera positive for the development of neutralising antibodies, which is in concordance with the bead-based multiplex and IgG ELISA.

Rationale: Psoriasis is a chronic inflammatory skin disease involving different cytokines and chemokines., Objectives: Here we use single-cell transcriptomic analyses to identify relevant immune cell and nonimmune cell populations for an in-depth characterization of cell types and inflammatory mediators in this disease., Methods: Psoriasis skin lesions of eight patients are analyzed using single-cell technology. Data are further validated by in situ hybridization (ISH) of human tissues, serum analyses of human samples and tissues of a murine model of psoriasis, and by in vitro cell culture experiments., Results: Several different immune-activated cell types with particular cytokine patterns are identified such as keratinocytes, T-helper cells, dendritic cells, macrophages, and fibroblasts. Apart from well-known factors, IL-14 (TXLNA), IL-18, and IL-32 are identified with prominent expression in individual cell types in psoriasis. The percentage of inflammatory cellular subtypes expressing IL-14, IL-18, and IL-32 was significantly higher in psoriatic skin compared with healthy control skin. These findings were confirmed by ISH of human skin samples, in a murine model of psoriasis, in human serum samples, and in in vitro experiments., Conclusions: Taken together, we provide a differentiated view of psoriasis immune-cell phenotypes that support the role of IL-14, IL-18, and IL-32 in psoriasis pathogenesis., (© 2023 The Authors. European Journal of Immunology published by Wiley-VCH GmbH.)

We addressed the question of the influence of the molecular polymorphism of cytokines from different T helper subsets on the susceptibility to SARS-CoV-2 infection. From a cohort of 527 samples (collected from 26 May 2020 to 31 March 2022), we focused on individuals living in the same household (n = 58) with the SARS-CoV-2-infected person. We divided them into households with all individuals SARS-CoV-2 PCR positive (n = 29, households, 61 individuals), households with mixed PCR pattern (n = 24, 62) and negative households (n = 5, 15), respectively. TGF-β1 and IL-6 were the only cytokines tested with a significant difference between the cohorts. We observed a shift toward Th2 and the regulatory Th17 and Treg subset regulation for households with all members infected compared to those without infection. These data indicate that the genetically determined balance between the cytokines acting on different T helper cell subsets may play a pivotal role in transmission of and susceptibility to SARS-CoV-2 infection. Contacts infected by their index persons were more likely to highly express TGF-β1, indicating a reduced inflammatory response. Those not infected after contact had a polymorphism leading to a higher IL-6 expression. IL-6 acts in innate immunity, allergy and on the T helper cell differentiation, explaining the reduced susceptibility to SARS-CoV-2.

During the coronavirus pandemic, evidence is growing that the severity, susceptibility and host immune response to SARS-CoV-2 infection can be highly variable. Several influencing factors have been discussed. Here, we investigated the humoral immune response against SARS-CoV-2 spike, S1, S2, the RBD, nucleocapsid moieties and S1 of seasonal coronaviruses: hCoV-229E, hCoV-HKU1, hCoV-NL63 and hCoV-OC43, as well as MERS-CoV and SARS-CoV, in a cohort of 512 individuals. A bead-based multiplex assay allowed simultaneous testing for all the above antigens and the identification of different antibody patterns. Then, we correlated these patterns with 11 HLA loci. Regarding the seasonal coronaviruses, we found a moderate negative correlation between antibody levels against hCoV-229E, hCoV-HKU1 and hCoV-NL63 and the SARS-CoV-2 antigens. This could be an indication of the original immunological imprinting. High and low antibody response patterns were distinguishable, demonstrating the individuality of the humoral response towards the virus. An immunogenetical factor associated with a high antibody response (formation of ≥4 different antibodies) was the presence of HLA A*26:01, C*02:02 and DPB1*04:01 alleles, whereas the HLA alleles DRB3*01:01, DPB1*03:01 and DB1*10:01 were enriched in low responders. A better understanding of this variable immune response could enable more individualized protective measures.

We used the ^{138}Ba(d,α) reaction to carry out an in-depth study of states in ^{136}Cs, up to around 2.5 MeV. In this Letter, we place emphasis on hitherto unobserved states below the first 1^{+} level, which are important in the context of solar neutrino and fermionic dark matter (FDM) detection in large-scale xenon-based experiments. We identify for the first time candidate metastable states in ^{136}Cs, which would allow a real-time detection of solar neutrino and FDM events in xenon detectors, with high background suppression. Our results are also compared with shell-model calculations performed with three Hamiltonians that were previously used to evaluate the nuclear matrix element (NME) for ^{136}Xe neutrinoless double beta decay. We find that one of these Hamiltonians, which also systematically underestimates the NME compared with the others, dramatically fails to describe the observed low-energy ^{136}Cs spectrum, while the other two show reasonably good agreement.

The molecular mechanisms of the liver metastasis of colorectal cancer (CRLM) remain poorly understood. Here, we applied machine learning and bioinformatics trajectory inference to analyze a gene expression dataset of CRLM. We studied the co-regulation patterns at the gene level, the potential paths of tumor development, their functional context, and their prognostic relevance. Our analysis confirmed the subtyping of five liver metastasis subtypes (LMS). We provide gene-marker signatures for each LMS, and a comprehensive functional characterization that considers both the hallmarks of cancer and the tumor microenvironment. The ordering of CRLMs along a pseudotime-tree revealed a continuous shift in expression programs, suggesting a developmental relationship between the subtypes. Notably, trajectory inference and personalized analysis discovered a range of epigenetic states that shape and guide metastasis progression. By constructing prognostic maps that divided the expression landscape into regions associated with favorable and unfavorable prognoses, we derived a prognostic expression score. This was associated with critical processes such as epithelial-mesenchymal transition, treatment resistance, and immune evasion. These factors were associated with responses to neoadjuvant treatment and the formation of an immuno-suppressive, mesenchymal state. Our machine learning-based molecular profiling provides an in-depth characterization of CRLM heterogeneity with possible implications for treatment and personalized diagnostics.

Background: The validity of the newly developed sleepiness assessment tool, the 'Top End Sleepiness Scale' (TESS), against other established obstructive sleep apnoea (OSA) screening tools has not been evaluated., Aims: To compare the utility and validity of the culturally safe and clinically relevant subjective daytime sleepiness assessment tool, the 'TESS' was used among Indigenous Australians against STOP-Bang screening tool for predicting OSA in a regional and remote Indigenous Australian cohort., Methods: The TESS questionnaire, consisting of pictorial representations of six items representing daily activities that would induce daytime sleepiness specific for Indigenous Australians, was assessed for its correlation in predicting moderate to severe OSA according to Apnoea-Hypopnoea Index (AHI, ≥15) against the STOP-Bang screening tool., Results: Eighty Indigenous Australian patients (51% male; mean age 45.1 ± 11.5 years) were included in this study with the majority (n = 70; 88%) having OSA, of which 65 (93%) had an AHI ≥ 15. Area under the curve statistics for overall scores showed no significant difference between TESS or STOP-Bang in the prediction of OSA (P = 0.16). A moderate risk score of TESS (≥3) was superior to STOP-Bang (score 3-4) in sensitivity (84% vs 33%) and specificity (39% vs 30%). The sensitivity for a high-risk score for the STOP-Bang (≥5) was superior to the TESS (≥8; 60% vs 33%), although specificity was comparable (83% vs 91% respectively)., Conclusions: The TESS screening tool could be a useful standalone or could be adopted alongside the STOP-Bang OSA screening tools in the clinical assessment of sleep disorders among Indigenous Australians., (© 2021 Royal Australasian College of Physicians.)

Herein, we included 527 individuals from two Hospitals, Chemnitz and University-Hospital Leipzig. In total, 199 were negative for PCR and 328 were positive upon first admission. We used next generation sequencing for HLA-A, B, C, DRB1, DRB345, DQA1, DQB1, DPA1, and DPB1, and in some cases, HLA-E, F, G, and H. Furthermore, we molecularly defined 22 blood group systems comprising 26 genes and 5 platelet antigen genes. We observed a significant enrichment of homozygosity for DQA/DQB in the positive group. Within the negative subjects, HLA-B*57:01, HLA-B*55:01, DRB1*13:01, and DRB1*01:01 were enriched, and in the positive group, homozygosity for DQA/DQB, DRB1*09:01, and DRB1*15:01 was observed. DQA1*01:01, DQA1*02:01, and DQA1*01:03 were enriched in the negative group. HLA-DQB1*06:02 was enriched in the positive group, and HLA-DQB1*05:01 and HLA-DQB1*06:03 were enriched in the negative group. For the blood group systems MNS, RH, LE, FY, JK, YT, DO, and KN, enrichment was seen in both groups, depending on the antigen under observation. Homozygosity for D-positive RHD alleles, as well as the phenotypes M-N+ of the MNS blood group system and Yk(a-) of the KN system, were enriched in the positive group. All of these significances disappeared upon correction. Subjects who carried homozygous HPA-1a were more frequent in the negative group, contrasting with the finding that HPA-1ab was enriched in the positive group.

Background: Clinical trials, epidemiological studies, clinical registries, and other prospective research projects, together with patient care services, are main sources of data in the medical research domain. They serve often as a basis for secondary research in evidence-based medicine, prediction models for disease, and its progression. This data are often neither sufficiently described nor accessible. Related models are often not accessible as a functional program tool for interested users from the health care and biomedical domains., Objective: The interdisciplinary project Leipzig Health Atlas (LHA) was developed to close this gap. LHA is an online platform that serves as a sustainable archive providing medical data, metadata, models, and novel phenotypes from clinical trials, epidemiological studies, and other medical research projects., Methods: Data, models, and phenotypes are described by semantically rich metadata. The platform prefers to share data and models presented in original publications but is also open for nonpublished data. LHA provides and associates unique permanent identifiers for each dataset and model. Hence, the platform can be used to share prepared, quality-assured datasets and models while they are referenced in publications. All managed data, models, and phenotypes in LHA follow the FAIR principles, with public availability or restricted access for specific user groups., Results: The LHA platform is in productive mode (https://www.health-atlas.de/). It is already used by a variety of clinical trial and research groups and is becoming increasingly popular also in the biomedical community. LHA is an integral part of the forthcoming initiative building a national research data infrastructure for health in Germany., Competing Interests: None declared., (The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).)

Anti-CD19 CAR-T cell immunotherapy is a hopeful treatment option for patients with B cell lymphomas, however it copes with partly severe adverse effects like neurotoxicity. Single-cell resolved molecular data sets in combination with clinical parametrization allow for comprehensive characterization of cellular subpopulations, their transcriptomic states, and their relation to the adverse effects. We here present a re-analysis of single-cell RNA sequencing data of 24 patients comprising more than 130,000 cells with focus on cellular states and their association to immune cell related neurotoxicity. For this, we developed a single-cell data portraying workflow to disentangle the transcriptional state space with single-cell resolution and its analysis in terms of modularly-composed cellular programs. We demonstrated capabilities of single-cell data portraying to disentangle transcriptional states using intuitive visualization, functional mining, molecular cell stratification, and variability analyses. Our analysis revealed that the T cell composition of the patient's infusion product as well as the spectrum of their transcriptional states of cells derived from patients with low ICANS grade do not markedly differ from those of cells from high ICANS patients, while the relative abundancies, particularly that of cycling cells, of LAG3-mediated exhaustion and of CAR positive cells, vary. Our study provides molecular details of the transcriptomic landscape with possible impact to overcome neurotoxicity., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Loeffler-Wirth, Rade, Arakelyan, Kreuz, Loeffler, Koehl, Reiche and Binder.)

Classification of lymphoid neoplasms is based mainly on histologic, immunologic, and (rarer) genetic features. It has been supplemented by gene expression profiling (GEP) in the last decade. Despite the considerable success, particularly in associating lymphoma subtypes with specific transcriptional programs and classifier signatures of up- or downregulated genes, competing molecular classifiers were often proposed in the literature by different groups for the same classification tasks to distinguish, e.g., BL versus DLBCL or different DLBCL subtypes. Moreover, rarer sub-entities such as MYC and BCL2 "double hit lymphomas" (DHL), IRF4-rearranged large cell lymphoma (IRF4-LCL), and Burkitt-like lymphomas with 11q aberration pattern (mnBLL-11q) attracted interest while their relatedness regarding the major classes is still unclear in many respects. We explored the transcriptional landscape of 873 lymphomas referring to a wide spectrum of subtypes by applying self-organizing maps (SOM) machine learning. The landscape reveals a continuum of transcriptional states activated in the different subtypes without clear-cut borderlines between them and preventing their unambiguous classification. These states show striking parallels with single cell gene expression of the active germinal center (GC), which is characterized by the cyclic progression of B-cells. The expression patterns along the GC trajectory are discriminative for distinguishing different lymphoma subtypes. We show that the rare subtypes take intermediate positions between BL, DLBCL, and FL as considered by the 5th edition of the WHO classification of haemato-lymphoid tumors in 2022. Classifier gene signatures extracted from these states as modules of coregulated genes are competitive with literature classifiers. They provide functional-defined classifiers with the option of consenting redundant classifiers from the literature. We discuss alternative classification schemes of different granularity and functional impact as possible avenues toward personalization and improved diagnostics of GC-derived lymphomas.

Multi-omics high-throughput technologies produce data sets which are not restricted to only one but consist of multiple omics modalities, often as patient-matched tumour specimens. The integrative analysis of these omics modalities is essential to obtain a holistic view on the otherwise fragmented information hidden in this data. We present an intuitive method enabling the combined analysis of multi-omics data based on self-organizing maps machine learning. It "portrays" the expression, methylation and copy number variations (CNV) landscapes of each tumour using the same gene-centred coordinate system. It enables the visual evaluation and direct comparison of the different omics layers on a personalized basis. We applied this combined molecular portrayal to lower grade gliomas, a heterogeneous brain tumour entity. It classifies into a series of molecular subtypes defined by genetic key lesions, which associate with large-scale effects on DNA methylation and gene expression, and in final consequence, drive with cell fate decisions towards oligodendroglioma-, astrocytoma- and glioblastoma-like cancer cell lineages with different prognoses. Consensus modes of concerted changes of expression, methylation and CNV are governed by the degree of co-regulation within and between the omics layers. The method is not restricted to the triple-omics data used here. The similarity landscapes reflect partly independent effects of genetic lesions and DNA methylation with consequences for cancer hallmark characteristics such as proliferation, inflammation and blocked differentiation in a subtype specific fashion. It can be extended to integrate other omics features such as genetic mutation, protein expression data as well as extracting prognostic markers.

Mutually linked expression and methylation dynamics in the brain govern genome regulation over the whole lifetime with an impact on cognition, psychological disorders, and cancer. We performed a joint study of gene expression and DNA methylation of brain tissue originating from the human prefrontal cortex of individuals across the lifespan to describe changes in cellular programs and their regulation by epigenetic mechanisms. The analysis considers previous knowledge in terms of functional gene signatures and chromatin states derived from independent studies, aging profiles of a battery of chromatin modifying enzymes, and data of gliomas and neuropsychological disorders for a holistic view on the development and aging of the brain. Expression and methylation changes from babies to elderly adults decompose into different modes associated with the serial activation of (brain) developmental, learning, metabolic and inflammatory functions, where methylation in gene promoters mostly represses transcription. Expression of genes encoding methylome modifying enzymes is very diverse reflecting complex regulations during lifetime which also associates with the marked remodeling of chromatin between permissive and restrictive states. Data of brain cancer and psychotic disorders reveal footprints of pathophysiologies related to brain development and aging. Comparison of aging brains with gliomas supports the view that glioblastoma-like and astrocytoma-like tumors exhibit higher cellular plasticity activated in the developing healthy brain while oligodendrogliomas have a more stable differentiation hierarchy more resembling the aged brain. The balance and specific shifts between volatile and stable and between more irreversible and more plastic epigenomic networks govern the development and aging of healthy and diseased brain.

Background: Phrenicus nerve palsy (PNP) is a typical complication during pulmonary vein isolation (PVI) using the cryoballoon with the ominous potential to counteract the clinical benefit of restored sinus rhythm. According to current evidence incidence of PNP is about 5-10% of patients undergoing Cryo-PVI and is more frequent during ablation of the RSPV compared to the RIPV. However, information on patient specific characteristics predicting PNP and long-term outcome of patients suffering from this adverse event is sparse. Aim of the Study: To evaluate procedural and clinical characteristics of AF patients with PNP during cryoballoon PVI compared to patients without PNP. Methods and Results: Between 2013 and 2019 we included 632 consecutive AF patients undergoing PVI with the cryoballoon in our study. 84/632 (13.3%) patients experienced a total number of 89 PNP during the ablation procedure. 75/89 (84%) cryothermal induced PNP recovered until the end of the procedure (transient PNP, tPNP), whereas 14/89 (16%) PNP hold beyond the end of the procedure (non-transient PNP, ntPNP). Using multivariate logistic regression, we found that sex and BMI are strong and independent predictors of cryothermal induced non-transient PNP during cryoballoon PVI with an odds ratio of 3.9 (CI: 95%, 1.1-14.8, p = 0.04) for female gender. Interestingly, all patients (14/14, 100%) with a non-transient PNP experienced complete PNP resolution after a mean recovery time of 68 ± 79 days. Conclusion: Our data indicate for the first time, that female sex and lower BMI are independent predictors for non-transient PNP caused by cryoballoon PVI. Fortunately, during follow up all PNP patients resolved completely with a median recovery time of 35 days., Competing Interests: TD received speaker's honoraria and consulting fees from Medtronic, Biosense Webster, Boerhringer-Ingelheim, Bayer, Daiichi-Sankyo. AP received speaker's honoraria from Medtronic, Biosense Webster, Daiichi-Sankyo and is invited fellow of the Boston Scientific EP training program. CS and YT were funded by the Deutsche Herzstiftung. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Pott, Wirth, Teumer, Weinmann, Baumhardt, Schweizer, Markovic, Buckert, Bothner, Rottbauer and Dahme.)

Background: Sinoatrial Node (SAN) is part of the cardiac conduction system, which controls the rhythmic contraction of the vertebrate heart. The SAN consists of a specialized pacemaker cell population that has the potential to generate electrical impulses. Although the SAN pacemaker has been extensively studied in mammalian and teleost models, including the zebrafish, their molecular nature remains inadequately comprehended., Results: To characterize the molecular profile of the zebrafish sinoatrial ring (SAR) and elucidate the mechanism of pacemaker function, we utilized the transgenic line sqet33mi59BEt to isolate cells of the SAR of developing zebrafish embryos and profiled their transcriptome. Our analyses identified novel candidate genes and well-known conserved signaling pathways involved in pacemaker development. We show that, compared to the rest of the heart, the zebrafish SAR overexpresses several mammalian SAN pacemaker signature genes, which include hcn4 as well as those encoding calcium- and potassium-gated channels. Moreover, genes encoding components of the BMP and Wnt signaling pathways, as well as members of the Tbx family, which have previously been implicated in pacemaker development, were also overexpressed in the SAR. Among SAR-overexpressed genes, 24 had human homologues implicated in 104 different ClinVar phenotype entries related to various forms of congenital heart diseases, which suggest the relevance of our transcriptomics resource to studying human heart conditions. Finally, functional analyses of three SAR-overexpressed genes, pard6a, prom2, and atp1a1a.2, uncovered their novel role in heart development and physiology., Conclusion: Our results established conserved aspects between zebrafish and mammalian pacemaker function and revealed novel factors implicated in maintaining cardiac rhythm. The transcriptome data generated in this study represents a unique and valuable resource for the study of pacemaker function and associated heart diseases., (© 2021. The Author(s).)

Objective: Cellular heterogeneity is regarded as a major factor affecting treatment response and resistance in malignant melanoma. Recent developments in single-cell sequencing technology have provided deeper insights into these mechanisms., Methods: Here, we analyzed a BRAF V600E -mutant melanoma cell line by single-cell RNA-seq under various conditions: cells sensitive to BRAF inhibition with BRAF inhibitor vemurafenib and cells resistant to BRAF inhibition with vemurafenib alone or vemurafenib in combination with the MEK1/2 inhibitors cobimetinib or trametinib. Dimensionality reduction by t-distributed stochastic neighbor embedding and self-organizing maps identified distinct trajectories of resistance development clearly separating the 4 treatment conditions in cell and gene state space., Results: Trajectories associated with resistance to single-agent treatment involved cell cycle, extracellular matrix, and de-differentiation programs. In contrast, shifts detected in double-resistant cells primarily affected translation and mitogen-activated protein kinase pathway reactivation, with a small subpopulation showing markers of pluripotency. These findings were validated in pseudotime analyses and RNA velocity measurements., Conclusions: The single-cell transcriptomic analyses reported here employed a spectrum of bioinformatics methods to identify mechanisms of melanoma resistance to single- and double-agent treatments. This study deepens our understanding of treatment-induced cellular reprogramming and plasticity in melanoma cells and identifies targets of potential relevance to the management of treatment resistance., Competing Interests: M. Kunz has received honoraria from the Speakers Bureau of Roche Pharma and travel support from Novartis Pharma GmbH and Bristol-Myers Squibb GmbH. All other authors declare no conflict of interest., (Copyright © 2021 Cancer Biology & Medicine.)

Surveillance of the evolving SARS-CoV-2 genome combined with epidemiological monitoring and emerging vaccination became paramount tasks to control the pandemic which is rapidly changing in time and space. Genomic surveillance must combine generation and sharing sequence data with appropriate bioinformatics monitoring and analysis methods. We applied molecular portrayal using self-organizing maps machine learning (SOM portrayal) to characterize the diversity of the virus genomes, their mutual relatedness and development since the beginning of the pandemic. The genetic landscape obtained visualizes the relevant mutations in a lineage-specific fashion and provides developmental paths in genetic state space from early lineages towards the variants of concern alpha, beta, gamma and delta. The different genes of the virus have specific footprints in the landscape reflecting their biological impact. SOM portrayal provides a novel option for 'bioinformatics surveillance' of the pandemic, with strong odds regarding visualization, intuitive perception and 'personalization' of the mutational patterns of the virus genomes.

Genetic splice variants have become of central interest in recent years, as they play an important role in different cancers. Little is known about splice variants in melanoma. Here, we analyzed a genome-wide transcriptomic dataset of benign melanocytic nevi and primary melanomas ( n = 80) for the expression of specific splice variants. Using kallisto, a map for differentially expressed splice variants in melanoma vs. benign melanocytic nevi was generated. Among the top genes with differentially expressed splice variants were Ras-related in brain 6B ( RAB6B ), a member of the RAS family of GTPases, Macrophage Scavenger Receptor 1 ( MSR1 ), Collagen Type XI Alpha 2 Chain ( COLL11A2 ), and LY6/PLAUR Domain Containing 1 ( LYPD1 ). The Gene Ontology terms of differentially expressed splice variants showed no enrichment for functional gene sets of melanoma vs. nevus lesions, but between type 1 (pigmentation type) and type 2 (immune response type) melanocytic lesions. A number of genes such as Checkpoint Kinase 1 ( CHEK1 ) showed an association of mutational patterns and occurrence of splice variants in melanoma. Moreover, mutations in genes of the splicing machinery were common in both benign nevi and melanomas, suggesting a common mechanism starting early in melanoma development. Mutations in some of these genes of the splicing machinery, such as Serine and Arginine Rich Splicing Factor A3 and B3 ( SF3A3 , SF3B3 ), were significantly enriched in melanomas as compared to benign nevi. Taken together, a map of splice variants in melanoma is presented that shows a multitude of differentially expressed splice genes between benign nevi and primary melanomas. The underlying mechanisms may involve mutations in genes of the splicing machinery.

Molecular mechanisms of lower-grade (II-III) diffuse gliomas (LGG) are still poorly understood, mainly because of their heterogeneity. They split into astrocytoma- (IDH-A) and oligodendroglioma-like (IDH-O) tumors both carrying mutations(s) at the isocitrate dehydrogenase (IDH) gene and into IDH wild type (IDH-wt) gliomas of glioblastoma resemblance. We generated detailed maps of the transcriptomes and DNA methylomes, revealing that cell functions divided into three major archetypic hallmarks: (i) increased proliferation in IDH-wt and, to a lesser degree, IDH-O; (ii) increased inflammation in IDH-A and IDH-wt; and (iii) the loss of synaptic transmission in all subtypes. Immunogenic properties of IDH-A are diverse, partly resembling signatures observed in grade IV mesenchymal glioblastomas or in grade I pilocytic astrocytomas. We analyzed details of coregulation between gene expression and DNA methylation and of the immunogenic micro-environment presumably driving tumor development and treatment resistance. Our transcriptome and methylome maps support personalized, case-by-case views to decipher the heterogeneity of glioma states in terms of data portraits. Thereby, molecular cartography provides a graphical coordinate system that links gene-level information with glioma subtypes, their phenotypes, and clinical context.

Coeliac disease (CD) is a clinically heterogeneous autoimmune disease with variable presentation and progression triggered by gluten intake. Molecular or genetic factors contribute to disease heterogeneity, but the reasons for different outcomes are poorly understood. Transcriptome studies of tissue biopsies from CD patients are scarce. Here, we present a high-resolution analysis of the transcriptomes extracted from duodenal biopsies of 24 children and adolescents with active CD and 21 individuals without CD but with intestinal afflictions as controls. The transcriptomes of CD patients divide into three groups-a mixed group presenting the control cases, and CD-low and CD-high groups referring to lower and higher levels of CD severity. Persistence of symptoms was weakly associated with subgroup, but the highest marsh stages were present in subgroup CD-high, together with the highest cell cycle rates as an indicator of virtually complete villous atrophy. Considerable variation in inflammation-level between subgroups was further deciphered into immune cell types using cell type de-convolution. Self-organizing maps portrayal was applied to provide high-resolution landscapes of the CD-transcriptome. We find asymmetric patterns of miRNA and long non-coding RNA and discuss the effect of epigenetic regulation. Expression of genes involved in interferon gamma signaling represent suitable markers to distinguish CD from non-CD cases. Multiple pathways overlay in CD biopsies in different ways, giving rise to heterogeneous transcriptional patterns, which potentially provide information about etiology and the course of the disease.

Purpose: To illustrate the utility of a newly developed culturally safe and clinically relevant subjective daytime sleepiness assessment tool "Top End Sleepiness Scale" (TESS) for use among Indigenous Australians., Patients and Methods: The TESS questionnaire consists of pictorial representations of 6 items representing daily activities that would induce daytime sleepiness specific for Indigenous Australians living in the regional and remote Australia. Consecutive adult Indigenous patients who consented to pilot the TESS questionnaire prior to undergoing a diagnostic polysomnography (PSG) at the Top End Health Service region, Northern Territory of Australia were assessed. The TESS questionnaire was evaluated for its correlation in predicting obstructive sleep apnea (OSA) according to apnea-hypopnea index., Results: Eighty-two patients were included. The majority (70%) had moderate to severe OSA (AHI ≥15). Patients were aged in their mid-40's (45.47 95% CI (42.9, 48.05)) with a tendency to obesity (median BMI 33.67 IQR 30.86, 38.95) and a high prevalence of chronic conditions (72%) (hypertension, diabetes or heart disease). The TESS showed high internal consistency (Split half Spearman correlation=0.71, Cronbach's α =0.81), and a cut-off value ≥3 resulted in sensitivity 84%, specificity 38%. Comparison of area under the curve for TESS to Epworth Sleepiness Scale (ESS) in this sample showed the TESS to have greater sensitivity and specificity overall, which approached significance (p=0.072) when cut-off values of ≥3 and ≥8 (TESS & ESS respectively) were used. The sensitivity and specificity for TESS was also comparable to the other currently used questionnaires, such as the Berlin Questionnaire, STOP-BANG and OSA 50., Conclusion: Currently, there are no subjective daytime sleepiness assessment toll available specifically for Indigenous population. The proposed TESS sleepiness screening tool represented in this study can potentially complement or adopted alongside other existing questionnaire, which may offer greater utility in the assessment of sleep disorders among Indigenous people., Competing Interests: All authors declare no conflicts of interest for this work., (© 2021 Benn et al.)

Cellular heterogeneity is regarded as a major factor for treatment response and resistance in a variety of malignant tumors, including malignant melanoma. More recent developments of single-cell sequencing technology provided deeper insights into this phenomenon. Single-cell data were used to identify prognostic subtypes of melanoma tumors, with a special emphasis on immune cells and fibroblasts in the tumor microenvironment. Moreover, treatment resistance to checkpoint inhibitor therapy has been shown to be associated with a set of differentially expressed immune cell signatures unraveling new targetable intracellular signaling pathways. Characterization of T cell states under checkpoint inhibitor treatment showed that exhausted CD8 + T cell types in melanoma lesions still have a high proliferative index. Other studies identified treatment resistance mechanisms to targeted treatment against the mutated BRAF serine/threonine protein kinase including repression of the melanoma differentiation gene microphthalmia-associated transcription factor (MITF) and induction of AXL receptor tyrosine kinase. Interestingly, treatment resistance mechanisms not only included selection processes of pre-existing subclones but also transition between different states of gene expression. Taken together, single-cell technology has provided deeper insights into melanoma biology and has put forward our understanding of the role of tumor heterogeneity and transcriptional plasticity, which may impact on innovative clinical trial designs and experimental approaches.

By 2040, roughly two-thirds of humanity are expected to live in urban areas. As cities expand, humans irreversibly transform natural ecosystems, creating both opportunities and challenges for wildlife. Here, we investigate how the Northern Goshawk ( Accipiter gentilis ) is adjusting to urban environments. We measured a variety of behavioural and ecological parameters in three urban and four rural study sites. City life appeared related to all parameters we measured. Urban female goshawks were overall 21.7 (CI 95% 5.13-130) times more likely to defend their nestlings from humans than rural females. Urban goshawks were 3.64 (CI 95% 2.05-6.66) times more likely to feed on pigeons and had diets exhibiting lower overall species richness and diversity. Urban females laid eggs 12.5 (CI 95% 7.12-17.4) days earlier than rural individuals and were 2.22 (CI 95% 0.984-4.73) times more likely to produce a brood of more than three nestlings. Nonetheless, urban goshawks suffered more from infections with the parasite Trichomonas gallinae , which was the second most common cause of mortality (14.6%), after collisions with windows (33.1%). In conclusion, although city life is associated with significant risks, goshawks appear to thrive in some urban environments, most likely as a result of high local availability of profitable pigeon prey. We conclude that the Northern Goshawk can be classified as an urban exploiter in parts of its distribution., Competing Interests: The authors declare that they have no conflict of interest., (© 2020 The Authors.)

Background: The blood transcriptome is expected to provide a detailed picture of an organism's physiological state with potential outcomes for applications in medical diagnostics and molecular and epidemiological research. We here present the analysis of blood specimens of 3,388 adult individuals, together with phenotype characteristics such as disease history, medication status, lifestyle factors, and body mass index (BMI). The size and heterogeneity of this data challenges analytics in terms of dimension reduction, knowledge mining, feature extraction, and data integration. Methods: Self-organizing maps (SOM)-machine learning was applied to study transcriptional states on a population-wide scale. This method permits a detailed description and visualization of the molecular heterogeneity of transcriptomes and of their association with different phenotypic features. Results: The diversity of transcriptomes is described by personalized SOM-portraits, which specify the samples in terms of modules of co-expressed genes of different functional context. We identified two major blood transcriptome types where type 1 was found more in men, the elderly, and overweight people and it upregulated genes associated with inflammation and increased heme metabolism, while type 2 was predominantly found in women, younger, and normal weight participants and it was associated with activated immune responses, transcriptional, ribosomal, mitochondrial, and telomere-maintenance cell-functions. We find a striking overlap of signatures shared by multiple diseases, aging, and obesity driven by an underlying common pattern, which was associated with the immune response and the increase of inflammatory processes. Conclusions: Machine learning applications for large and heterogeneous omics data provide a holistic view on the diversity of the human blood transcriptome. It provides a tool for comparative analyses of transcriptional signatures and of associated phenotypes in population studies and medical applications., (Copyright © 2020 Schmidt, Hopp, Arakelyan, Kirsten, Engel, Wirkner, Krohn, Burkhardt, Thiery, Loeffler, Loeffler-Wirth and Binder.)

Background: oposSOM is a comprehensive, machine learning based open-source data analysis software combining functionalities such as diversity analyses, biomarker selection, function mining, and visualization., Results: These functionalities are now available as interactive web-browser application for a broader user audience interested in extracting detailed information from high-throughput omics data sets pre-processed by oposSOM. It enables interactive browsing of single-gene and gene set profiles, of molecular 'portrait landscapes', of associated phenotype diversity, and signalling pathway activation patterns., Conclusion: The oposSOM-Browser makes available interactive data browsing for five transcriptome data sets of cancer (melanomas, B-cell lymphomas, gliomas) and of peripheral blood (sepsis and healthy individuals) at www.izbi.uni-leipzig.de/opossom-browser .

Single-cell RNA sequencing has become a standard technique to characterize tissue development. Hereby, cross-sectional snapshots of the diversity of cell transcriptomes were transformed into (pseudo-) longitudinal trajectories of cell differentiation using computational methods, which are based on similarity measures distinguishing cell phenotypes. Cell development is driven by alterations of transcriptional programs e.g., by differentiation from stem cells into various tissues or by adapting to micro-environmental requirements. We here complement developmental trajectories in cell-state space by trajectories in gene-state space to more clearly address this latter aspect. Such trajectories can be generated using self-organizing maps machine learning. The method transforms multidimensional gene expression patterns into two dimensional data landscapes, which resemble the metaphoric Waddington epigenetic landscape. Trajectories in this landscape visualize transcriptional programs passed by cells along their developmental paths from stem cells to differentiated tissues. In addition, we generated developmental "vector fields" using RNA-velocities to forecast changes of RNA abundance in the expression landscapes. We applied the method to tissue development of planarian as an illustrative example. Gene-state space trajectories complement our data portrayal approach by (pseudo-)temporal information about changing transcriptional programs of the cells. Future applications can be seen in the fields of tissue and cell differentiation, ageing and tumor progression and also, using other data types such as genome, methylome, and also clinical and epidemiological phenotype data.

New experimental data on the neutron single-particle character of the Pygmy Dipole Resonance (PDR) in ^{208}Pb are presented. They were obtained from (d,p) and resonant proton scattering experiments performed at the Q3D spectrograph of the Maier-Leibnitz Laboratory in Garching, Germany. The new data are compared to the large suite of complementary, experimental data available for ^{208}Pb and establish (d,p) as an additional, valuable, experimental probe to study the PDR and its collectivity. Besides the single-particle character of the states, different features of the strength distributions are discussed and compared to large-scale shell model (LSSM) and energy-density functional plus quasiparticle-phonon model theoretical approaches to elucidate the microscopic structure of the PDR in ^{208}Pb.

The Covid-19 pandemic is developing worldwide with common dynamics but also with marked differences between regions and countries. These are not completely understood, but presumably, provide a clue to find ways to mitigate epidemics until strategies leading to its eradication become available. We describe an iteractive monitoring tool available in the internet. It enables inspection of the dynamic state of the epidemic in 187 countries using trajectories that visualize the transmission and removal rates of the epidemic and in this way bridge epi-curve tracking with modelling approaches. Examples were provided which characterize state of epidemic in different regions of the world in terms of fast and slow growing and decaying regimes and estimate associated rate factors. The basic spread of the disease is associated with transmission between two individuals every two-three days on the average. Non-pharmaceutical interventions decrease this value to up to ten days, whereas 'complete lock down' measures are required to stop the epidemic. Comparison of trajectories revealed marked differences between the countries regarding efficiency of measures taken against the epidemic. Trajectories also reveal marked country-specific recovery and death rate dynamics. The results presented refer to the pandemic state in May to July 2020 and can serve as 'working instruction' for timely monitoring using the interactive monitoring tool as a sort of 'seismometer' for the evaluation of the state of epidemic, e.g., the possible effect of measures taken in both, lock-down and lock-up directions. Comparison of trajectories between countries and regions will support developing hypotheses and models to better understand regional differences of dynamics of Covid-19.

Background: Whole-genome studies of vine cultivars have brought novel knowledge about the diversity, geographical relatedness, historical origin and dissemination, phenotype associations and genetic markers., Method: We applied SOM (self-organizing maps) portrayal, a neural network-based machine learning method, to re-analyze the genome-wide Single Nucleotide Polymorphism (SNP) data of nearly eight hundred grapevine cultivars. The method generates genome-specific data landscapes. Their topology reflects the geographical distribution of cultivars, indicates paths of cultivar dissemination in history and genome-phenotype associations about grape utilization., Results: The landscape of vine genomes resembles the geographic map of the Mediterranean world, reflecting two major dissemination paths from South Caucasus along a northern route via Balkan towards Western Europe and along a southern route via Palestine and Maghreb towards Iberian Peninsula. The Mediterranean and Black Sea, as well as the Pyrenees, constitute barriers for genetic exchange. On the coarsest level of stratification, cultivars divide into three major groups: Western Europe and Italian grapes, Iberian grapes and vine cultivars from Near East and Maghreb regions. Genetic landmarks were associated with agronomic traits, referring to their utilization as table and wine grapes. Pseudotime analysis describes the dissemination of grapevines in an East to West direction in different waves of cultivation., Conclusion: In analogy to the tasks of the wine waiter in gastronomy, the sommelier, our 'SOMmelier'-approach supports understanding the diversity of grapevine genomes in the context of their geographic and historical background, using SOM portrayal. It offers an option to supplement vine cultivar passports by genome fingerprint portraits.

Background & Aims: Toll-like receptor 4 (TLR4) plays an essential role in mediating organ injury in acute liver failure (ALF) and acute-on-chronic liver failure (ACLF). Herein, we assess whether inhibiting TLR4 signaling can ameliorate liver failure and serve as a potential treatment., Methods: Circulating TLR4 ligands and hepatic TLR4 expression were measured in plasma samples and liver biopsies from patients with cirrhosis. TAK-242 (TLR4 inhibitor) was tested in vivo (10 mg/kg intraperitoneally) in rodent models of ACLF (bile duct ligation + lipopolysaccharide [LPS]; carbon tetrachloride + LPS) and ALF (galactosamine + LPS) and in vitro on immortalized human monocytes (THP-1) and hepatocytes (HHL5). The in vivo therapeutic effect was assessed by coma-free survival, organ injury and cytokine release and in vitro by measuring IL-6, IL-1β or cell injury (TUNEL), respectively., Results: In patients with cirrhosis, hepatic TLR4 expression was upregulated and circulating TLR4 ligands were increased (p <0.001). ACLF in rodents was associated with a switch from apoptotic cell death in ALF to non-apoptotic forms of cell death. TAK-242 reduced LPS-induced cytokine secretion and cell death (p = 0.002) in hepatocytes and monocytes in vitro. In rodent models of ACLF, TAK-242 administration improved coma-free survival, reduced the degree of hepatocyte cell death in the liver (p <0.001) and kidneys (p = 0.048) and reduced circulating cytokine levels (IL-1β, p <0.001). In a rodent model of ALF, TAK-242 prevented organ injury (p <0.001) and systemic inflammation (IL-1β, p <0.001)., Conclusion: This study shows that TLR4 signaling is a key factor in the development of both ACLF and ALF; its inhibition reduces the severity of organ injury and improves outcome. TAK-242 may be of therapeutic relevance in patients with liver failure., Lay Summary: Toll-like receptor 4 (or TLR4) mediates endotoxin-induced tissue injury in liver failure and cirrhosis. This receptor sensitizes cells to endotoxins, which are produced by gram-negative bacteria. Thus, inhibiting TLR4 signaling with an inhibitor (TAK-242) ameliorates organ injury and systemic inflammation in rodent models of acute and acute-on-chronic liver failure., Competing Interests: Conflict of interest Rajiv Jalan has research collaborations with Takeda, and Yaqrit, and consults for Yaqrit. Rajiv Jalan is the founder of Yaqrit Limited, which is developing UCL inventions for treatment of patients with cirrhosis. Rajiv Jalan is an inventor of ornithine phenylacetate, which was licensed by UCL to Mallinckrodt. He is also the inventor of Yaq-001, DIALIVE and Yaq-005, the patents for which have been licensed by his University into a UCL spinout company, Yaqrit Ltd. Cornelius Engelmann has on-going research collaboration with Sequana Medical, Merz Pharmaceutical and Novartis. He has received speaker fees from Novartis, Gilead and Merz Pharmaceuticals. Please refer to the accompanying ICMJE disclosure forms for further details., (Copyright © 2020 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.)

Body shape and composition are heterogeneous among humans with possible impact for health. Anthropometric methods and data are needed to better describe the diversity of the human body in human populations, its age dependence, and associations with health risk. We applied whole-body laser scanning to a cohort of 8499 women and men of age 40-80 years within the frame of the LIFE (Leipzig Research Center for Civilization Diseases) study aimed at discovering health risk in a middle European urban population. Body scanning delivers multidimensional anthropometric data, which were further processed by machine learning to stratify the participants into body types. We here applied this body typing concept to describe the diversity of body shapes in an aging population and its association with physical activity and selected health and lifestyle factors. We find that aging results in similar reshaping of female and male bodies despite the large diversity of body types observed in the study. Slim body shapes remain slim and partly tend to become even more lean and fragile, while obese body shapes remain obese. Female body shapes change more strongly than male ones. The incidence of the different body types changes with characteristic Life Course trajectories. Physical activity is inversely related to the body mass index and decreases with age, while self-reported incidence for myocardial infarction shows overall the inverse trend. We discuss health risks factors in the context of body shape and its relation to obesity. Body typing opens options for personalized anthropometry to better estimate health risk in epidemiological research and future clinical applications., Competing Interests: Competing interestsThe authors declare no competing interests., (© The Author(s) 2020.)

Drug repositioning can save considerable time and resources and significantly speed up the drug development process. The increasing availability of drug action and disease-associated transcriptome data makes it an attractive source for repositioning studies. Here, we have developed a transcriptome-guided approach for drug/biologics repositioning based on multi-layer self-organizing maps (ml-SOM). It allows for analyzing multiple transcriptome datasets by segmenting them into layers of drug action- and disease-associated transcriptome data. A comparison of expression changes in clusters of functionally related genes across the layers identifies "drug target" spots in disease layers and evaluates the repositioning possibility of a drug. The repositioning potential for two approved biologics drugs (infliximab and brodalumab) confirmed the drugs' action for approved diseases (ulcerative colitis and Crohn's disease for infliximab and psoriasis for brodalumab). We showed the potential efficacy of infliximab for the treatment of sarcoidosis, but not chronic obstructive pulmonary disease (COPD). Brodalumab failed to affect dysregulated functional gene clusters in Crohn's disease (CD) and systemic juvenile idiopathic arthritis (SJIA), clearly indicating that it may not be effective in the treatment of these diseases. In conclusion, ml-SOM offers a novel approach for transcriptome-guided drug repositioning that could be particularly useful for biologics drugs.

Background: Activation of telomere maintenance mechanisms (TMMs) is a hallmark of most cancers, and is required to prevent genome instability and to establish cellular immortality through reconstitution of capping of chromosome ends. TMM depends on the cancer type. Comparative studies linking tumor biology and TMM have potential impact for evaluating cancer onset and development. Methods: We have studied alterations of telomere length, their sequence composition and transcriptional regulation in mismatch repair deficient colorectal cancers arising in Lynch syndrome (LS-CRC) and microsatellite instable (MSI) sporadic CRC (MSI s-CRC), and for comparison, in microsatellite stable (MSS) s-CRC and in benign colon mucosa. Our study applied bioinformatics analysis of whole genome DNA and RNA sequencing data and a pathway model to study telomere length alterations and the potential effect of the "classical" telomerase (TEL-) and alternative (ALT-) TMM using transcriptomic signatures. Results: We have found progressive decrease of mean telomere length in all cancer subtypes compared with reference systems. Our results support the view that telomere attrition is an early event in tumorigenesis. TMM gets activated in all tumors studied due to concerted overexpression of a large fraction of genes with direct relation to telomere function, where only a very small fraction of them showed recurrent mutations. TEL-related transcriptional state was dominating in all CRC subtypes, showing, however, subtype-specific activation patterns; while contribution of the ALT-TMM was slightly more prominent in the hypermutated MSI s-CRC and LS-CRC. TEL-TMM is mainly activated by over-expression of DKC1 and/or TERT genes and their interaction partners, where DKC1 is more prominent in MSS than in MSI s-CRC and can serve as a transcriptomic marker of TMM activity. Conclusions: Our results suggest that transcriptional patterns are indicative for TMM pathway activation with subtle differences between TEL and ALT mechanisms in a CRC subtype-specific fashion. Sequencing data potentially provide a suited measure to study alterations of telomere length and of underlying transcriptional regulation. Further studies are needed to improve this method., (Copyright © 2019 Nersisyan, Hopp, Loeffler-Wirth, Galle, Loeffler, Arakelyan and Binder.)

Background: Germinal center-derived B cell lymphomas are tumors of the lymphoid tissues representing one of the most heterogeneous malignancies. Here we characterize the variety of transcriptomic phenotypes of this disease based on 873 biopsy specimens collected in the German Cancer Aid MMML (Molecular Mechanisms in Malignant Lymphoma) consortium. They include diffuse large B cell lymphoma (DLBCL), follicular lymphoma (FL), Burkitt's lymphoma, mixed FL/DLBCL lymphomas, primary mediastinal large B cell lymphoma, multiple myeloma, IRF4-rearranged large cell lymphoma, MYC-negative Burkitt-like lymphoma with chr. 11q aberration and mantle cell lymphoma., Methods: We apply self-organizing map (SOM) machine learning to microarray-derived expression data to generate a holistic view on the transcriptome landscape of lymphomas, to describe the multidimensional nature of gene regulation and to pursue a modular view on co-expression. Expression data were complemented by pathological, genetic and clinical characteristics., Results: We present a transcriptome map of B cell lymphomas that allows visual comparison between the SOM portraits of different lymphoma strata and individual cases. It decomposes into one dozen modules of co-expressed genes related to different functional categories, to genetic defects and to the pathogenesis of lymphomas. On a molecular level, this disease rather forms a continuum of expression states than clearly separated phenotypes. We introduced the concept of combinatorial pattern types (PATs) that stratifies the lymphomas into nine PAT groups and, on a coarser level, into five prominent cancer hallmark types with proliferation, inflammation and stroma signatures. Inflammation signatures in combination with healthy B cell and tonsil characteristics associate with better overall survival rates, while proliferation in combination with inflammation and plasma cell characteristics worsens it. A phenotypic similarity tree is presented that reveals possible progression paths along the transcriptional dimensions. Our analysis provided a novel look on the transition range between FL and DLBCL, on DLBCL with poor prognosis showing expression patterns resembling that of Burkitt's lymphoma and particularly on 'double-hit' MYC and BCL2 transformed lymphomas., Conclusions: The transcriptome map provides a tool that aggregates, refines and visualizes the data collected in the MMML study and interprets them in the light of previous knowledge to provide orientation and support in current and future studies on lymphomas and on other cancer entities.

Background: During the last decades a number of genome-wide association studies (GWASs) has identified numerous single nucleotide polymorphisms (SNPs) associated with different complex diseases. However, associations reported in one population are often conflicting and did not replicate when studied in other populations. One of the reasons could be that most GWAS employ a case-control design in one or a limited number of populations, but little attention was paid to the global distribution of disease-associated alleles across different populations. Moreover, the majority of GWAS have been performed on selected European, African, and Chinese populations and the considerable number of populations remains understudied. Aim: We have investigated the global distribution of so far discovered disease-associated SNPs across worldwide populations of different ancestry and geographical regions with a special focus on the understudied population of Armenians. Data and Methods: We have used genotyping data from the Human Genome Diversity Project and of Armenian population and combined them with disease-associated SNP data taken from public repositories leading to a final dataset of 44,234 markers. Their frequency distribution across 1039 individuals from 53 populations was analyzed using self-organizing maps (SOM) machine learning. Our SOM portrayal approach reduces data dimensionality, clusters SNPs with similar frequency profiles and provides two-dimensional data images which enable visual evaluation of disease-associated SNPs landscapes among human populations. Results: We find that populations from Africa, Oceania, and America show specific patterns of minor allele frequencies of disease-associated SNPs, while populations from Europe, Middle East, Central South Asia, and Armenia mostly share similar patterns. Importantly, different sets of SNPs associated with common polygenic diseases, such as cancer, diabetes, neurodegeneration in populations from different geographic regions. Armenians are characterized by a set of SNPs that are distinct from other populations from the neighboring geographical regions. Conclusion: Genetic associations of diseases considerably vary across populations which necessitates health-related genotyping efforts especially for so far understudied populations. SOM portrayal represents novel promising methods in population genetic research with special strength in visualization-based comparison of SNP data.

Background: Diffuse lower WHO grade II and III gliomas (LGG) are slowly progressing brain tumors, many of which eventually transform into a more aggressive type. LGG is characterized by widespread genetic and transcriptional heterogeneity, yet little is known about the heterogeneity of the DNA methylome, its function in tumor biology, coupling with the transcriptome and tumor microenvironment and its possible impact for tumor development., Methods: We here present novel DNA methylation data of an LGG-cohort collected in the German Glioma Network containing about 85% isocitrate dehydrogenase (IDH) mutated tumors and performed a combined bioinformatics analysis using patient-matched genome and transcriptome data., Results: Stratification of LGG based on gene expression and DNA-methylation provided four consensus subtypes. We characterized them in terms of genetic alterations, functional context, cellular composition, tumor microenvironment and their possible impact for treatment resistance and prognosis. Glioma with astrocytoma-resembling phenotypes constitute the largest fraction of nearly 60%. They revealed largest diversity and were divided into four expression and three methylation groups which only partly match each other thus reflecting largely decoupled expression and methylation patterns. We identified a novel G-protein coupled receptor and a cancer-related 'keratinization' methylation signature in in addition to the glioma-CpG island methylator phenotype (G-CIMP) signature. These different signatures overlap and combine in various ways giving rise to diverse methylation and expression patterns that shape the glioma phenotypes. The decrease of global methylation in astrocytoma-like LGG associates with higher WHO grade, age at diagnosis and inferior prognosis. We found analogies between astrocytoma-like LGG with grade IV IDH-wild type tumors regarding possible worsening of treatment resistance along a proneural-to-mesenchymal axis. Using gene signature-based inference we elucidated the impact of cellular composition of the tumors including immune cell bystanders such as macrophages., Conclusions: Genomic, epigenomic and transcriptomic factors act in concert but partly also in a decoupled fashion what underpins the need for integrative, multidimensional stratification of LGG by combining these data on gene and cellular levels to delineate mechanisms of gene (de-)regulation and to enable better patient stratification and individualization of treatment.

Recent studies revealed trajectories of mutational events in early melanomagenesis, but the accompanying changes in gene expression are far less understood. Therefore, we performed a comprehensive RNA-seq analysis of laser-microdissected melanocytic nevi (n = 23) and primary melanoma samples (n = 57) and characterized the molecular mechanisms of early melanoma development. Using self-organizing maps, unsupervised clustering, and analysis of pseudotime (PT) dynamics to identify evolutionary trajectories, we describe here two transcriptomic types of melanocytic nevi (N1 and N2) and primary melanomas (M1 and M2). N1/M1 lesions are characterized by pigmentation-type and MITF gene signatures, and a high prevalence of NRAS mutations in M1 melanomas. N2/M2 lesions are characterized by inflammatory-type and AXL gene signatures with an equal distribution of wild-type and mutated BRAF and low prevalence of NRAS mutations in M2 melanomas. Interestingly, N1 nevi and M1 melanomas and N2 nevi and M2 melanomas, respectively, cluster together, but there is no clustering in a stage-dependent manner. Transcriptional signatures of M1 melanomas harbor signatures of BRAF/MEK inhibitor resistance and M2 melanomas harbor signatures of anti-PD-1 antibody treatment resistance. Pseudotime dynamics of nevus and melanoma samples are suggestive for a switch-like immune-escape mechanism in melanoma development with downregulation of immune genes paralleled by an increasing expression of a cell cycle signature in late-stage melanomas. Taken together, the transcriptome analysis identifies gene signatures and mechanisms underlying development of melanoma in early and late stages with relevance for diagnostics and therapy.

3D-body scanning anthropometry is a suitable method for characterization of physiological development of children and adolescents, and for understanding onset and progression of disorders like overweight and obesity. Here we present a novel body typing approach to describe and to interpret longitudinal 3D-body scanning data of more than 800 children and adolescents measured in up to four follow-ups in intervals of 1 year, referring to an age range between 6 and 18 years. We analyzed transitions between body types assigned to lower-, normal- and overweight participants upon development of children and adolescents. We found a virtually parallel development of the body types with only a few transitions between them. Body types of children and adolescents tend to conserve their weight category. 3D body scanning anthropometry in combination with body typing constitutes a novel option to investigate onset and progression of obesity in children., Competing Interests: The authors have declared that no competing interests exist.

We analyzed the blood transcriptome of sepsis framed within community-acquired pneumonia (CAP) and characterized its molecular and cellular heterogeneity in terms of functional modules of co-regulated genes with impact for the underlying pathophysiological mechanisms. Our results showed that CAP severity is associated with immune suppression owing to T-cell exhaustion and HLA and chemokine receptor deactivation, endotoxin tolerance, macrophage polarization, and metabolic conversion from oxidative phosphorylation to glycolysis. We also found footprints of host's response to viruses and bacteria, altered levels of mRNA from erythrocytes and platelets indicating coagulopathy that parallel severity of sepsis and survival. Finally, our data demonstrated chromatin re-modeling associated with extensive transcriptional deregulation of chromatin modifying enzymes, which suggests the extensive changes of DNA methylation with potential impact for marker selection and functional characterization. Based on the molecular footprints identified, we propose a novel stratification of CAP cases into six groups differing in the transcriptomic scores of CAP severity, interferon response, and erythrocyte mRNA expression with impact for prognosis. Our analysis increases the resolution of transcriptomic footprints of CAP and reveals opportunities for selecting sets of transcriptomic markers with impact for translation of omics research in terms of patient stratification schemes and sets of signature genes.

Aim: We present here a novel method that enables unraveling the interplay between gene expression and DNA methylation in complex diseases such as cancer., Materials & Methods: The method is based on self-organizing maps and allows for analysis of data landscapes from 'governed by methylation' to 'governed by expression'., Results: We identified regulatory modules of coexpressed and comethylated genes in high-grade gliomas: two modes are governed by genes hypermethylated and underexpressed in IDH-mutated cases, while two other modes reflect immune and stromal signatures in the classical and mesenchymal subtypes. A fifth mode with proneural characteristics comprises genes of repressed and poised chromatin states active in healthy brain. Two additional modes enrich genes either in active or repressed chromatin states., Conclusion: The method disentangles the interplay between gene expression and methylation. It has the potential to integrate also mutation and copy number data and to apply to large sample cohorts.

Single-cell transcriptomics has been used for analysis of heterogeneous populations of cells during developmental processes and for analysis of tumor cell heterogeneity. More recently, analysis of pseudotime (PT) dynamics of heterogeneous cell populations has been established as a powerful concept to study developmental processes. Here we perform PT analysis of 3 melanoma short-term cultures with different genetic backgrounds to study specific and concordant properties of PT dynamics of selected cellular programs with impact on melanoma progression. Overall, in our setting of melanoma cells PT dynamics towards higher tumor malignancy appears to be largely driven by cell cycle genes. Single cells of all three short-term cultures show a bipolar expression of microphthalmia-associated transcription factor (MITF) and AXL receptor tyrosine kinase (AXL) signatures. Furthermore, opposing gene expression changes are observed for genes regulated by epigenetic mechanisms suggesting epigenetic reprogramming during melanoma progression. The three melanoma short-term cultures show common themes of PT dynamics such as a stromal signature at initiation, bipolar expression of the MITF/AXL signature and opposing regulation of poised and activated promoters. Differences are observed at the late stage of PT dynamics with high, low or intermediate MITF and anticorrelated AXL signatures. These findings may help to identify targets for interference at different stages of tumor progression., Competing Interests: The authors declare no conflict of interest.