Genetic and Metabolic Characteristics of Lean Nonalcoholic Fatty Liver Disease in a Korean Health Examinee Cohort

Background/Aims

The pathophysiology of lean nonalcoholic fatty liver disease (NAFLD) is unclear but has been shown to be associated with more diverse pathogenic mechanisms than that of obese NAFLD. We investigated the characteristics of genetic or metabolic lean NAFLD in a health checkup cohort.

Methods

This retrospective cross-sectional study analyzed single nucleotide polymorphism data for 6,939 health examinees. Lean individuals were categorized according to a body mass index cutoff of 23 kg/m2. Single nucleotide polymorphisms were analyzed using genotyping arrays.

Results

The prevalence of lean NAFLD was 21.6% among all participants with NAFLD, and the proportion of lean NAFLD was 18.5% among lean participants. The prevalence of metabolic syndrome and diabetes among lean patients with NAFLD was 12.4% and 10.4%, respectively. Lean NAFLD appeared to be metabolic-associated in approximately 20.1% of patients. The homozygous minor allele (GG) of PNPLA3 (rs738409) and heterozygous minor alleles (CT, TT) of TM6SF2 (rs58542926) were associated with lean NAFLD. However, the prevalence of fatty liver was not associated with the genetic variants MBOAT7 (rs641738), HSD17B13 (rs72613567), MARC1 (rs2642438), or AGXT2 (rs2291702) in lean individuals. Lean NAFLD appeared to be associated with PNPLA3 or TM6SF2 genetic variation in approximately 32.1% of cases. Multivariate risk factor analysis showed that metabolic risk factors, genetic risk variants, and waist circumference were independent risk factors for lean NAFLD.

Conclusions

In a considerable number of patients, lean NAFLD did not appear to be associated with known genetic or metabolic risk factors. Further studies are required to investigate additional risk factors and gain a more comprehensive understanding of lean NAFLD.

Epigenetic modification of gene expression in cancer cells by terahertz demethylation

Terahertz (THz) radiation can affect the degree of DNA methylation, the spectral characteristics of which exist in the terahertz region. DNA methylation is an epigenetic modification in which a methyl (CH₃) group is attached to cytosine, a nucleobase in human DNA. Appropriately controlled DNA methylation leads to proper regulation of gene expression. However, abnormal gene expression that departs from controlled genetic transcription through aberrant DNA methylation may occur in cancer or other diseases. In this study, we demonstrate the modification of gene expression in cells by THz demethylation using resonant THz radiation. Using an enzyme-linked immunosorbent assay, we observed changes in the degree of global DNA methylation in the SK-MEL-3 melanoma cell line under irradiation with 1.6-THz radiation with limited spectral bandwidth. Resonant THz radiation demethylated living melanoma cells by 19%, with no significant occurrence of apurinic/apyrimidinic sites, and the demethylation ratio was linearly proportional to the power of THz radiation. THz demethylation downregulates FOS, JUN, and CXCL8 genes, which are involved in cancer and apoptosis pathways. Our results show that THz demethylation has the potential to be a gene expression modifier with promising applications in cancer treatment.

Physician Perspectives on Vaccination in Patients With Autoimmune Inflammatory Rheumatic Diseases: An International Survey

OBJECTIVE

To evaluate the perspective of physicians who care for patients with autoimmune inflammatory rheumatic disease (AIIRD) toward vaccination.

METHODS

Physicians who care for patients with AIIRD were invited to participate in an online survey regarding their vaccination perspectives in adult patients with AIIRD.

RESULTS

Survey responses of 370 physicians from Asia (41.1%), North America (41.6%), Europe (13.8%), and other countries (3.5%) were analyzed. Participants stated that rheumatologists (58.2%) should be primarily responsible for vaccination coverage, followed by general internists (19.3%) and family medicine practitioners (12.8%). Additionally, 96.7% of participants considered vaccination very important (≥ 4/5 rating) for patients with AIIRD. Despite these sentiments, only one-third (37%) reported vaccinating the majority (≥ 60%) of their patients.

CONCLUSION

Physicians who care for patients with AIIRD agree that vaccines are effective and safe in patients with AIIRD. Unfortunately, they often do not ensure that their patients are adequately vaccinated. Further studies are needed to investigate how to improve vaccination coverage for this high-risk patient population.

Extru-seq: a method for predicting genome-wide Cas9 off-target sites with advantages of both cell-based and in vitro approaches

We present a novel genome-wide off-target prediction method named Extru-seq and compare it with cell-based (GUIDE-seq), in vitro (Digenome-seq), and in silico methods using promiscuous guide RNAs with large numbers of valid off-target sites. Extru-seq demonstrates a high validation rate and retention of information about the intracellular environment, both beneficial characteristics of cell-based methods. Extru-seq also shows a low miss rate and could easily be performed in clinically relevant cell types with little optimization, which are major positive features of the in vitro methods. In summary, Extru-seq shows beneficial features of cell-based and in vitro methods.

Physicians' Agreement on and Implementation of the 2019 European Alliance of Associations for Rheumatology Vaccination Guideline: An International Survey

Objective

To evaluate the perspective of healthcare professionals towards the 2019 European Alliance of Associations for Rheumatology (EULAR) vaccination guideline in patients with autoimmune inflammatory rheumatic diseases (AIIRD).

Methods

Healthcare professionals who care for patients with AIIRD were invited to participate in an online survey regarding their perspective on the 2019 update of the EULAR recommendations for vaccination in adult patients with AIIRD. Level of agreement and implementation of the 6 overarching principles and 9 recommendations were rated on a 5-point Likert scale (1~5).

Results

Survey responses of 371 healthcare professionals from Asia (42.2%) and North America (41.6%), Europe (13.8%), and other countries were analyzed. Only 16.3% of participants rated their familiarity with the 2019 EULAR guideline as 5/5 ("very well"). There was a high agreement (≥4/5 rating) with the overarching principles, except for the principles applying to live-attenuated vaccines. There was a high level of agreement with the recommendations regarding influenza and pneumococcal vaccinations; implementation of these recommendations was also high. Participants also reported a high level of agreement with the remaining recommendations but did not routinely implement these recommendations.

Conclusion

The 2019 update of EULAR recommendations for the vaccination of adult patients with AIIRD is generally thought to be important by healthcare professionals, although implementation of adequate vaccination is often lacking. Better education of healthcare providers may be important to optimize the vaccination coverage for patients with AIIRD.

Direct neuronal infection of SARS-CoV-2 reveals cellular and molecular pathology of chemosensory impairment of COVID-19 patients

Patients with recent pandemic coronavirus disease 19 (COVID-19) complain of neurological abnormalities in sensory functions such as smell and taste in the early stages of infection. Determining the cellular and molecular mechanism of sensory impairment is critical to understand the pathogenesis of clinical manifestations, as well as in setting therapeutic targets for sequelae and recurrence. The absence of studies utilizing proper models of human peripheral nerve hampers an understanding of COVID-19 pathogenesis. Here, we report that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) directly infects human peripheral sensory neurons, leading to molecular pathogenesis for chemosensory impairments. An in vitro system utilizing human embryonic stem cell (hESC)-derived peripheral neurons was used to model the cellular and molecular pathologies responsible for symptoms that most COVID-19 patients experience early in infection or may develop as sequelae. Peripheral neurons differentiated from hESCs expressed viral entry factor ACE2, and were directly infected with SARS-CoV-2 via ACE2. Human peripheral neurons infected with SARS-CoV-2 exhibited impaired molecular features of chemosensory function associated with abnormalities in sensory neurons of the olfactory or gustatory organs. Our results provide new insights into the pathogenesis of chemosensory dysfunction in patients with COVID-19.

dialogi: Utilising NLP With Chemical and Disease Similarities to Drive the Identification of Drug-Induced Liver Injury Literature

Drug-Induced Liver Injury (DILI), despite its low occurrence rate, can cause severe side effects or even lead to death. Thus, it is one of the leading causes for terminating the development of new, and restricting the use of already-circulating, drugs. Moreover, its multifactorial nature, combined with a clinical presentation that often mimics other liver diseases, complicate the identification of DILI-related (or “positive”) literature, which remains the main medium for sourcing results from the clinical practice and experimental studies. This work–contributing to the “Literature AI for DILI Challenge” of the Critical Assessment of Massive Data Analysis (CAMDA) 2021– presents an automated pipeline for distinguishing between DILI-positive and negative publications. We used Natural Language Processing (NLP) to filter out the uninformative parts of a text, and identify and extract mentions of chemicals and diseases. We combined that information with small-molecule and disease embeddings, which are capable of capturing chemical and disease similarities, to improve classification performance. The former were directly sourced from the Chemical Checker (CC). For the latter, we collected data that encode different aspects of disease similarity from the National Library of Medicine’s (NLM) Medical Subject Headings (MeSH) thesaurus and the Comparative Toxicogenomics Database (CTD). Following a similar procedure as the one used in the CC, vector representations for diseases were learnt and evaluated. Two Neural Network (NN) classifiers were developed: a baseline model that accepts texts as input and an augmented, extended, model that also utilises chemical and disease embeddings. We trained, validated, and tested the classifiers through a Nested Cross-Validation (NCV) scheme with 10 outer and 5 inner folds. During this, the baseline and extended models performed virtually identically, with F₁-scores of 95.04 ± 0.61% and 94.80 ± 0.41%, respectively. Upon validation on an external, withheld, dataset that is meant to assess classifier generalisability, the extended model achieved an F₁-score of 91.14 ± 1.62%, outperforming its baseline counterpart which received a lower score of 88.30 ± 2.44%. We make further comparisons between the classifiers and discuss future improvements and directions, including utilising chemical and disease embeddings for visualisation and exploratory analysis of the DILI-positive literature.

DILI C : An AI-Based Classifier to Search for Drug-Induced Liver Injury Literature

Drug-induced liver injury (DILI) is a class of adverse drug reactions (ADR) that causes problems in both clinical and research settings. It is the most frequent cause of acute liver failure in the majority of Western countries and is a major cause of attrition of novel drug candidates. Manual trawling of the literature is the main route of deriving information on DILI from research studies. This makes it an inefficient process prone to human error. Therefore, an automatized AI model capable of retrieving DILI-related articles from the huge ocean of literature could be invaluable for the drug discovery community. In this study, we built an artificial intelligence (AI) model combining the power of natural language processing (NLP) and machine learning (ML) to address this problem. This model uses NLP to filter out meaningless text (e.g., stop words) and uses customized functions to extract relevant keywords such as singleton, pair, and triplet. These keywords are processed by an apriori pattern mining algorithm to extract relevant patterns which are used to estimate initial weightings for a ML classifier. Along with pattern importance and frequency, an FDA-approved drug list mentioning DILI adds extra confidence in classification. The combined power of these methods builds a DILI classifier (DILI _C ), with 94.91% cross-validation and 94.14% external validation accuracy. To make DILI _C as accessible as possible, including to researchers without coding experience, an R Shiny app capable of classifying single or multiple entries for DILI is developed to enhance ease of user experience and made available at https://researchmind.co.uk/diliclassifier/. Additionally, a GitHub link (https://github.com/sanjaysinghrathi/DILI-Classifier) for app source code and ISMB extended video talk (https://www.youtube.com/watch?v=j305yIVi_f8) are available as supplementary materials.

Identification of potential pan-coronavirus therapies using a computational drug repurposing platform

In the past 20 years, there have been several infectious disease outbreaks in humans for which the causative agent has been a zoonotic coronavirus. Novel infectious disease outbreaks, as illustrated by the current coronavirus disease 2019 (COVID-19) pandemic, demand a rapid response in terms of identifying effective treatments for seriously ill patients. The repurposing of approved drugs from other therapeutic areas is one of the most practical routes through which to approach this. Here, we present a systematic network-based drug repurposing methodology, which interrogates virus-human, human protein-protein and drug-protein interactome data. We identified 196 approved drugs that are appropriate for repurposing against COVID-19 and 102 approved drugs against a related coronavirus, severe acute respiratory syndrome (SARS-CoV). We constructed a protein-protein interaction (PPI) network based on disease signatures from COVID-19 and SARS multi-omics datasets. Analysis of this PPI network uncovered key pathways. Of the 196 drugs predicted to target COVID-19 related pathways, 44 (hypergeometric p-value: 1.98e-04) are already in COVID-19 clinical trials, demonstrating the validity of our approach. Using an artificial neural network, we provide information on the mechanism of action and therapeutic value for each of the identified drugs, to facilitate their rapid repurposing into clinical trials.

Computational Discovery of Cancer Immunotherapy Targets by Intercellular CRISPR Screens

Cancer immunotherapy targets the interplay between immune and cancer cells. In particular, interactions between cytotoxic T lymphocytes (CTLs) and cancer cells, such as PD-1 (PDCD1) binding PD-L1 (CD274), are crucial for cancer cell clearance. However, immune checkpoint inhibitors targeting these interactions are effective only in a subset of patients, requiring the identification of novel immunotherapy targets. Genome-wide clustered regularly interspaced short palindromic repeats (CRISPR) screening in either cancer or immune cells has been employed to discover regulators of immune cell function. However, CRISPR screens in a single cell type complicate the identification of essential intercellular interactions. Further, pooled screening is associated with high noise levels. Herein, we propose intercellular CRISPR screens, a computational approach for the analysis of genome-wide CRISPR screens in every interacting cell type for the discovery of intercellular interactions as immunotherapeutic targets. We used two publicly available genome-wide CRISPR screening datasets obtained while triple-negative breast cancer (TNBC) cells and CTLs were interacting. We analyzed 4825 interactions between 1391 ligands and receptors on TNBC cells and CTLs to evaluate their effects on CTL function. Intercellular CRISPR screens discovered targets of approved drugs, a few of which were not identifiable in single datasets. To evaluate the method's performance, we used data for cytokines and costimulatory molecules as they constitute the majority of immunotherapeutic targets. Combining both CRISPR datasets improved the recall of discovering these genes relative to using single CRISPR datasets over two-fold. Our results indicate that intercellular CRISPR screens can suggest novel immunotherapy targets that are not obtained through individual CRISPR screens. The pipeline can be extended to other cancer and immune cell types to discover important intercellular interactions as potential immunotherapeutic targets.

A Unifying Framework for Understanding Biological Structures and Functions Across Levels of Biological Organization

The relationship between structure and function is a major constituent of the rules of life. Structures and functions occur across all levels of biological organization. Current efforts to integrate conceptual frameworks and approaches to address new and old questions promise to allow a more holistic and robust understanding of how different biological functions are achieved across levels of biological organization. Here, we provide unifying and generalizable definitions of both structure and function that can be applied across all levels of biological organization. However, we find differences in the nature of structures at the organismal level and below as compared to above the level of the organism. We term these intrinsic and emergent structures, respectively. Intrinsic structures are directly under selection, contributing to the overall performance (fitness) of the individual organism. Emergent structures involve interactions among aggregations of organisms and are not directly under selection. Given this distinction, we argue that while the functions of many intrinsic structures remain unknown, functions of emergent structures are the result of the aggregate of processes of individual organisms. We then provide a detailed and unified framework of the structure-function relationship for intrinsic structures to explore how their unknown functions can be defined. We provide examples of how these scalable definitions applied to intrinsic structures provide a framework to address questions on structure-function relationships that can be approached simultaneously from all subdisciplines of biology. We propose that this will produce a more holistic and robust understanding of how different biological functions are achieved across levels of biological organization.

Psychosocial adjustment mediates impacts of playmate positive support on body mass index and overweight risk in adolescents

OBJECTIVES

We examined the mediation effects of psychosocial adjustment on the impact of playmate positive support throughout childhood and early adolescence (from age 54 months to 11 years) on later body mass index (BMI) and overweight risk in middle adolescence (age 15 years).

STUDY DESIGN

This was a prospective cohort study.

METHODS

Among 844 children and their families, positive support between child-playmate dyads was repeatedly assessed from child's age 54 months to Grade 5. Long-term positive support between child-playmate dyads throughout childhood and early adolescence was prospectively linked to child's BMI and overweight/obesity status at age 15 years. The average scores of repeated assessments of internalizing and externalizing behavior problems from Grades 3 to 6 were used as mediators.

RESULTS

Significant mediations of internalizing and externalizing behavior problems were observed on pathways from positive support between child-playmate dyads to later BMI and overweight/obesity status at age 15 years. The observed mediations were mainly sustained with pronounced magnitudes in girls, but not in boys.

CONCLUSIONS

Our findings demonstrated a significant mediating role of psychosocial adjustment. Future research efforts are highly encouraged to replicate our findings and further explore this underlying mediation mechanism.

Predication of oxygen requirement in COVID-19 patients using dynamic change of inflammatory markers: CRP, hypertension, age, neutrophil and lymphocyte (CHANeL)

The objective of the study was to develop and validate a prediction model that identifies COVID-19 patients at risk of requiring oxygen support based on five parameters: C-reactive protein (CRP), hypertension, age, and neutrophil and lymphocyte counts (CHANeL). This retrospective cohort study included 221 consecutive COVID-19 patients and the patients were randomly assigned randomly to a training set and a test set in a ratio of 1:1. Logistic regression, logistic LASSO regression, Random Forest, Support Vector Machine, and XGBoost analyses were performed based on age, hypertension status, serial CRP, and neutrophil and lymphocyte counts during the first 3 days of hospitalization. The ability of the model to predict oxygen requirement during hospitalization was tested. During hospitalization, 45 (41.8%) patients in the training set (n = 110) and 41 (36.9%) in the test set (n = 111) required supplementary oxygen support. The logistic LASSO regression model exhibited the highest AUC for the test set, with a sensitivity of 0.927 and a specificity of 0.814. An online risk calculator for oxygen requirement using CHANeL predictors was developed. “CHANeL” prediction models based on serial CRP, neutrophil, and lymphocyte counts during the first 3 days of hospitalization, along with age and hypertension status, provide a reliable estimate of the risk of supplement oxygen requirement among patients hospitalized with COVID-19.

POS0417 EXOGENOUS CXCL5 RESTORES ENDOGENOUS BLOOD-TISSUE CHEMOKINE GRADIENT TO IMPROVE SURVIVAL IN MURINE LUPUS

Background:

Systemic lupus erythematosus (SLE) is a multi-organ autoimmune disease that is potentially fatal. There is an unmet need to improve current therapies. In patients with SLE, we observed that serum CXCL5 levels were significantly lower than healthy control subjects and negatively correlated with disease activity(1-9).

Objectives:

The aim of this study is to elucidate the effect of supplemental serum CXCL5 in abrogating the pathological processes of SLE.

Methods:

Ten doses of exogenous CXCL5 (3µg/kg) was administered to 16-week-old Faslpr mice weekly by intravenous injection. Mice were monitored for 10 weeks. Splenic immune profile was measured by flow cytometry. Circulating cytokine and immunoglobulin profile were detected by Luminex technology. Renal function was evaluated by urinary spot albumin creatinine ratio. In situ renal immune cell infiltration and complement 3 deposition were detected by Haematoxylin and Eosin (H&E) and immunohistochemistry staining. The molecular pathways involved were examined by RNA sequencing.

Results:

In Faslpr mice, intravenous administration of exogenous CXCL5 significantly improved mouse survival with concomitant reduction of autoantibody secretion, proteinuria, complement 3 deposition, neutrophil infiltration and lupus nephritis classes. Through evaluating the changes of immune profile, cytokine profile and molecular pathways, we found that intravenous CXCL5 reduced inflammation via an orchestral effect of regulating neutrophil trafficking and modulating helper T cell-mediated immune response. Pharmacokinetic and real-time Polymerase Chain Reaction studies further demonstrated that this orchestration was triggered by a cascade reaction - restoring vascular under-expressed CXCL5 by an exogenous stimulation, re-establishing the normal serum levels of endogenous CXCL5 and reverting the CXCL5 chemokine gradient between inflamed tissues and blood circulation.

Conclusion:

Managing the dysregulation of CXCL5 by exogenous supplement may provide a new option for SLE therapy.

References:

[1]Dufies M, Grytsai O, Ronco C, et al. New CXCR1/CXCR2 inhibitors represent an effective treatment for kidney or head and neck cancers sensitive or refractory to reference treatments. Theranostics. 2019;9(18):5332-5346. doi:10.7150/thno.34681

[2]Yildirim K, Colak E, Aktimur R, et al. Clinical Value of CXCL5 for Determining of Colorectal Cancer. Asian Pac J Cancer Prev. Sep 26 2018;19(9):2481-2484. doi:10.22034/apjcp.2018.19.9.2481

[3]Wu K, Yu S, Liu Q, Bai X, Zheng X. The clinical significance of CXCL5 in non-small cell lung cancer. Onco Targets Ther. 2017;10:5561-5573. doi:10.2147/ott.s148772

[4]Zhao J, Ou B, Han D, et al. Tumor-derived CXCL5 promotes human colorectal cancer metastasis through activation of the ERK/Elk-1/Snail and AKT/GSK3beta/beta-catenin pathways. Mol Cancer. Mar 29 2017;16(1):70. doi:10.1186/s12943-017-0629-4

[5]Han KQ, Han H, He XQ, et al. Chemokine CXCL1 may serve as a potential molecular target for hepatocellular carcinoma. Cancer Med. Oct 2016;5(10):2861-2871. doi:10.1002/cam4.843

[6]Pappa CA, Tsirakis G, Kanellou P, et al. Monitoring serum levels ELR+ CXC chemokines and the relationship between microvessel density and angiogenic growth factors in multiple myeloma. Cytokine. Dec 2011;56(3):616-20. doi:10.1016/j.cyto.2011.08.034

[7]Zhang L, Li H, Ge C, et al. CXCL3 contributes to CD133(+) CSCs maintenance and forms a positive feedback regulation loop with CD133 in HCC via Erk1/2 phosphorylation. Sci Rep. Jun 3 2016;6:27426. doi:10.1038/srep27426

[8]Matsubara J, Honda K, Ono M, et al. Reduced plasma level of CXC chemokine ligand 7 in patients with pancreatic cancer. Cancer Epidemiol Biomarkers Prev. Jan 2011;20(1):160-71. doi:10.1158/1055- 9965.epi-10-0397

[9]Ma Y, Ren Y, Dai ZJ, Wu CJ, Ji YH, Xu J. IL-6, IL-8 and TNF-alpha levels correlate with disease stage in breast cancer patients. Adv Clin Exp Med. May-Jun 2017;26(3):421-426. doi:10.17219/acem/62120

Disclosure of Interests:

None declared

Identification of SARS-CoV-2-induced pathways reveals drug repurposing strategies

The global outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) necessitates the rapid development of new therapies against coronavirus disease 2019 (COVID-19) infection. Here, we present the identification of 200 approved drugs, appropriate for repurposing against COVID-19. We constructed a SARS-CoV-2-induced protein network, based on disease signatures defined by COVID-19 multiomics datasets, and cross-examined these pathways against approved drugs. This analysis identified 200 drugs predicted to target SARS-CoV-2-induced pathways, 40 of which are already in COVID-19 clinical trials, testifying to the validity of the approach. Using artificial neural network analysis, we classified these 200 drugs into nine distinct pathways, within two overarching mechanisms of action (MoAs): viral replication (126) and immune response (74). Two drugs (proguanil and sulfasalazine) implicated in viral replication were shown to inhibit replication in cell assays. This unbiased and validated analysis opens new avenues for the rapid repurposing of approved drugs into clinical trials.

Current and prospective computational approaches and challenges for developing COVID-19 vaccines

SARS-CoV-2, which causes COVID-19, was first identified in humans in late 2019 and is a coronavirus which is zoonotic in origin. As it spread around the world there has been an unprecedented effort in developing effective vaccines. Computational methods can be used to speed up the long and costly process of vaccine development. Antigen selection, epitope prediction, and toxicity and allergenicity prediction are areas in which computational tools have already been applied as part of reverse vaccinology for SARS-CoV-2 vaccine development. However, there is potential for computational methods to assist further. We review approaches which have been used and highlight additional bioinformatic approaches and PK modelling as in silico methods which may be useful for SARS-CoV-2 vaccine design but remain currently unexplored. As more novel viruses with pandemic potential are expected to arise in future, these techniques are not limited to application to SARS-CoV-2 but also useful to rapidly respond to novel emerging viruses.

Pattern of inflammatory immune response determines the clinical course and outcome of COVID-19: unbiased clustering analysis

The objective of the study was to identify distinct patterns in inflammatory immune responses of COVID-19 patients and to investigate their association with clinical course and outcome. Data from hospitalized COVID-19 patients were retrieved from electronic medical record. Supervised k-means clustering of serial C-reactive protein levels (CRP), absolute neutrophil counts (ANC), and absolute lymphocyte counts (ALC) was used to assign immune responses to one of three groups. Then, relationships between patterns of inflammatory responses and clinical course and outcome of COVID-19 were assessed in a discovery and validation cohort. Unbiased clustering analysis grouped 105 patients of a discovery cohort into three distinct clusters. Cluster 1 (hyper-inflammatory immune response) was characterized by high CRP levels, high ANC, and low ALC, whereas Cluster 3 (hypo-inflammatory immune response) was associated with low CRP levels and normal ANC and ALC. Cluster 2 showed an intermediate pattern. All patients in Cluster 1 required oxygen support whilst 61% patients in Cluster 2 and no patient in Cluster 3 required supplementary oxygen. Two (13.3%) patients in Cluster 1 died, whereas no patient in Clusters 2 and 3 died. The results were confirmed in an independent validation cohort of 116 patients. We identified three different patterns of inflammatory immune response to COVID-19. Hyper-inflammatory immune responses with elevated CRP, neutrophilia, and lymphopenia are associated with a severe disease and a worse outcome. Therefore, targeting the hyper-inflammatory response might improve the clinical outcome of COVID-19.

An interactive retrieval system for clinical trial studies with context-dependent protocol elements

A well-defined protocol for a clinical trial guarantees a successful outcome report. When designing the protocol, most researchers refer to electronic databases and extract protocol elements using a keyword search. However, state-of-the-art database systems only offer text-based searches for user-entered keywords. In this study, we present a database system with a context-dependent and protocol-element-selection function for successfully designing a clinical trial protocol. To do this, we first introduce a database for a protocol retrieval system constructed from individual protocol data extracted from 184,634 clinical trials and 13,210 frame structures of clinical trial protocols. The database contains a variety of semantic information that allows the filtering of protocols during the search operation. Based on the database, we developed a web application called the clinical trial protocol database system (CLIPS; available at https://corus.kaist.edu/clips). This system enables an interactive search by utilizing protocol elements. To enable an interactive search for combinations of protocol elements, CLIPS provides optional next element selection according to the previous element in the form of a connected tree. The validation results show that our method achieves better performance than that of existing databases in predicting phenotypic features.

AB0128 CXCL5 DAMPENS INFLAMMATION IN THE PRE-CLINICAL MODEL OF SYSTEMIC LUPUS ERYTHEMATOSUS VIA THE ORCHESTRAL EFFECT OF REGULATING NEUTROPHIL TRAFFICKING AND SUPPRESSING HELPER T CELL-MEDIATED IMMUNE RESPONSE

Background:

Patients with systemic lupus erythematosus (SLE) suffer from severe morbidity and mortality1-4, either from the disease itself or from side effects of immunosuppression5. Discovery of novel effective therapies with less toxicity is an urgent need.

Objectives:

The aim of this study is to elucidate the therapeutic potential and working mechanism of cytokine CXCL5 in lupus mice.

Methods:

Treatment with CXCL5, bone marrow (BM)-MSCs, standard of care (SOC) with combination of methylprednisolone and cyclophosphamide was given to 16-week-old Faslprmice. Mice were monitored for 10 weeks. Splenic immune cell subsets were measured by flow cytometry. Circulating cytokine and immunoglobulin were detected by Luminex technology. Renal function was evaluated by urinary spot albumin creatinine ratio. In situ renal immune cell infiltration and complement 3 deposition were detected by Haematoxylin and Eosin (H&E) staining and immunohistochemistry.

Results:

CXCL5 demonstrated consistent and potent immunosuppressive capacity in suppressing SLE with reduced autoantibody secretion, lymphoproliferation and preserved kidney function. With further exploration, we proved that CXCL5 reduced the proliferation of helper T cells (TH1 and TH2) in thein vitrofunctional assay. When we administrated CXCL5 to lupus mice, it promoted the proliferation of regulatory T cells and reduced the proliferation of TH17 cells, macrophages and neutrophils. Multiple proinflammatory cytokines including IL-2, IL-6, IL-12, IL-17A, KC/CXCL1, MIP-1β/CCL4 and TNF-α were also reduced. When combined with SOC, CXCL5 boosted its therapeutic effect and reduced the relevant indices of disease activity. When we correlated the effect of four different treatment groups (CXCL5, BM-MSCs, SOC, and CXCL5 plus SOC) on mice survival and target cell changes, we found that TH17 cells were the key effector cells involved in the pathogenesis of SLE.

Conclusion:

These findings demonstrated that CXCL5 dampens inflammation in the pre-clinical model of systemic lupus erythematosus via the orchestral effect of regulating neutrophil trafficking and suppressing helper T cell-mediated immune response. Administrating exogenous CXCL5 might be an attractive option to treat patients with lupus.

References:

[1]Ji S, Guo Q, Han Y, Tan G, Luo Y, Zeng F. Mesenchymal stem cell transplantation inhibits abnormal activation of Akt/GSK3beta signaling pathway in T cells from systemic lupus erythematosus mice.Cell Physiol Biochem.2012;29(5-6):705-712.

[2]Peng SL. Altered T and B lymphocyte signaling pathways in lupus.Autoimmun Rev.2009;8(3):179-183.

[3]Ferucci ED, Johnston JM, Gaddy JR, et al. Prevalence and incidence of systemic lupus erythematosus in a population-based registry of American Indian and Alaska Native people, 2007-2009.Arthritis Rheumatol.2014;66(9):2494-2502.

[4]Jakes RW, Bae SC, Louthrenoo W, Mok CC, Navarra SV, Kwon N. Systematic review of the epidemiology of systemic lupus erythematosus in the Asia-Pacific region: prevalence, incidence, clinical features, and mortality.Arthritis Care Res (Hoboken).2012;64(2):159-168.

[5]Sattwika PD, Mustafa R, Paramaiswari A, Herningtyas EH. Stem cells for lupus nephritis: a concise review of current knowledge.Lupus.2018;27(12):1881-1897.

Acknowledgments:

The work was supported by SMART II Centre Grant (NMRC/CG/M011/2017_SGH) and SingHealth Foundation (SHF/FG638P/2016).

Disclosure of Interests:

None declared

Synergistic mechanisms of Sanghuang-Danshen phytochemicals on postprandial vascular dysfunction in healthy subjects: A network biology approach based on a clinical trial

With the increased risk of cardiovascular disease, the use of botanicals for vascular endothelial dysfunction has intensified. Here, we explored the synergistic mechanisms of Sanghuang–Danshen (SD) phytochemicals on the homeostatic protection against high-fat-induced vascular dysfunction in healthy subjects, using a network biology approach, based on a randomised crossover clinical trial. Seventeen differential markers identified in blood samples taken at 0, 3 and 6 h post-treatment, together with 12SD phytochemicals, were mapped onto the network platform, termed the context-oriented directed associations. The resulting vascular sub-networks illustrated associations between 10 phytochemicals with 32 targets implicated in 143 metabolic/signalling pathways. The three key events included adhesion molecule production (ellagic acid, fumaric acid and cryptotanshinone; VCAM-1, ICAM-1 and PLA2G2A; fatty acid metabolism), platelet activation (ellagic acid, protocatechuic acid and tanshinone IIA; VEGFA, APAF1 and ATF3; mTOR, p53, Rap1 and VEGF signalling pathways) and endothelial inflammation (all phytochemicals, except cryptotanshinone; 29 targets, including TP53 and CASP3; MAPK and PI3K-Akt signalling pathways, among others). Our collective findings demonstrate a potential of SD to protect unintended risks of vascular dysfunction in healthy subjects, providing a deeper understanding of the complicated synergistic mechanisms of signature phytochemicals in SD.

Impact of Balloon-Guiding Catheter Location on Recanalization in Patients with Acute Stroke Treated by Mechanical Thrombectomy

BACKGROUND AND PURPOSE

Mechanical thrombectomy with proximal flow control and forced aspiration may improve the outcome of endovascular revascularization therapy for patients with acute stroke. The purpose of this study was to compare the impact of balloon-guiding catheter locations in patients treated for anterior circulation acute ischemic stroke using mechanical thrombectomy.

MATERIALS AND METHODS

The influence of the balloon-guiding catheter location (proximal, balloon-guiding catheter tip proximal to C1 vertebral body; distal, between the skull base and the C1 vertebral body) was analyzed in patients with acute anterior circulation stroke treated with stent-retriever thrombectomy. The baseline angiographic/clinical characteristics, time intervals, recanalization rates, and clinical outcomes were compared.

RESULTS

The clinical analysis included 102 patients (mean age, 69.5 ± 12.8 years; male/female ratio = 52:50). The balloon-guiding catheter was located distally in 49 patients and proximally in 53 patients for flow control and forced aspiration during stent retrieval. The puncture-to-recanalization time was shorter in the distal group than in the proximal group (40 versus 56 minutes, P = .02). Successful and complete recanalizations were more frequently achieved in the distal group compared with the proximal group (98.0% versus 75.5%. P = .003; 67.3% versus 45.3%, P = .04, respectively). Multivariate analysis showed that the distal catheterization location was independently associated with successful recanalization (adjusted OR, 13.4; 95% CI, 2.4-254.8; P = .02).

CONCLUSIONS

Location of the balloon-guiding catheter has a significant impact on recanalization in patients with acute stroke. The balloon-guiding catheter should be positioned as distally as safely possible in the cervical ICA for maximally effective thrombectomy.

Synergistic Effects of Sanghuang⁻Danshen Bioactives on Arterial Stiffness in a Randomized Clinical Trial of Healthy Smokers: An Integrative Approach to in silico Network Analysis

The vascular endothelium is a favorite early target of cardiovascular risk factors, including cigarette smoking. Here, we investigated the synergistic effects of Sanghuang–Danshen (SD) bioactives on vascular stiffness in a controlled clinical trial of healthy chronic smokers (n = 72). Relative to placebo, 4-week SD consumption at 900 mg/day improves pulse wave velocity (p = 0.0497), reduces systolic blood pressure (peripheral, p = 0.0008; brachial, p = 0.0046; and ankle, p = 0.0066), and increases endothelial nitric oxide synthase activation (p < 0.0001). We then mapped all differential markers obtained from the clinical data, Affymetrix microarray, and ¹H NMR metabolomics, together with 12 SD bioactives, onto the network platform termed the context-oriented directed associations. The resulting vascular subnetwork demonstrates that ellagic acid, caffeic acid, protocatechuic acid, cryptotanshinone, tanshinone I, and tanshinone IIA are linked to NOS3, ARG2, and EDN1 for vascular dilation, implicated with arginine/proline metabolism. They are also linked to SUCLG1, CYP1A1, and succinate related to the mitochondrial metabolism and detoxification, implicated with various metabolic pathways. These results could explain the synergistic action mechanisms of SD bioactives in the regulation of vascular endothelial dilation and metabolism, confirming the potential of SD in improving vascular stiffness and blood pressure in healthy smokers.

A fast detection of fusion genes from paired-end RNA-seq data

Background

Fusion genes are known to be drivers of many common cancers, so they are potential markers for diagnosis, prognosis or therapy response. The advent of paired-end RNA sequencing enhances our ability to discover fusion genes. While there are available methods, routine analyses of large number of samples are still limited due to high computational demands.

Results

We develop FuSeq, a fast and accurate method to discover fusion genes based on quasi-mapping to quickly map the reads, extract initial candidates from split reads and fusion equivalence classes of mapped reads, and finally apply multiple filters and statistical tests to get the final candidates. We apply FuSeq to four validated datasets: breast cancer, melanoma and glioma datasets, and one spike-in dataset. The results reveal high sensitivity and specificity in all datasets, and compare well against other methods such as FusionMap, TRUP, TopHat-Fusion, SOAPfuse and JAFFA. In terms of computational time, FuSeq is two-fold faster than FusionMap and orders of magnitude faster than the other methods.

Conclusions

With this advantage of less computational demands, FuSeq makes it practical to investigate fusion genes in large numbers of samples. FuSeq is implemented in C++ and R, and available at https://github.com/nghiavtr/FuSeqfor non-commercial uses.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5156-1) contains supplementary material, which is available to authorized users.

Association between fever pattern and clinical manifestations of adult-onset Still's disease: unbiased analysis using hierarchical clustering

OBJECTIVES

To perform unbiased analysis of fever patterns and to investigate their association with clinical manifestations and outcome of patients with adult-onset Still's disease (AOSD).

METHODS

AOSD patients who were treated as in-patients from 2004 through 2015 were grouped according to 24-hour body temperature (BT) by hierarchical clustering using a Euclidean distance metric with complete linkage. The clinical and laboratory characteristics of the groups were then examined.

RESULTS

Hierarchical clustering partitioned 70 AOSD patients into three distinct groups. Group 1 (n=14) had the highest mean BT (38.1± 0.4°C) and the widest variation in BT (2.7±0.9°C). Group 2 (n=35) had a lower mean BT (37.4±0.3°C) and a smaller variation (2.1±0.7°C). Group 3 (n=21) had the lowest mean BT (36.7±0.3°C) and the smallest variation (1.5±0.6°C). Clinical features and extent of organ involvement did not differ significantly between groups. However, Group 1 had lower platelet counts and higher lactate dehydrogenase, ferritin levels, and prothrombin time than the other groups. In addition, Group 1 exhibited higher risk of having a macrophage activation syndrome (MAS) and tended to require more intense treatment with corticosteroids and immunosuppressant to achieve clinical remission as compared to other groups.

CONCLUSIONS

Hierarchical clustering identified three distinct fever patterns in patients with AOSD. Higher BT was associated with wider variations in diurnal temperature, higher risk of developing MAS, more intense treatment, and longer time to clinical remission, suggesting that fever pattern is a prognostic factor for AOSD.

Global Analysis of SUMO-Binding Proteins Identifies SUMOylation as a Key Regulator of the INO80 Chromatin Remodeling Complex

SUMOylation is a critical regulator of a broad range of cellular processes, and is thought to do so in part by modulation of protein interaction. To comprehensively identify human proteins whose interaction is modulated by SUMOylation, we developed an in vitro binding assay using human proteome microarrays to identify targets of SUMO1 and SUMO2. We then integrated these results with protein SUMOylation and protein-protein interaction data to perform network motif analysis. We focused on a single network motif we termed a SUMOmodPPI (SUMO-modulated Protein-Protein Interaction) that included the INO80 chromatin remodeling complex subunits TFPT and INO80E. We validated the SUMO-binding activity of INO80E, and showed that TFPT is a SUMO substrate both in vitro and in vivo We then demonstrated a key role for SUMOylation in mediating the interaction between these two proteins, both in vitro and in vivo By demonstrating a key role for SUMOylation in regulating the INO80 chromatin remodeling complex, this work illustrates the power of bioinformatics analysis of large data sets in predicting novel biological phenomena.

Isomorphic coalescence of aster cores formed in vitro from microtubules and kinesin motors

We report fluorescence microscopy studies of the formation of aster-like structures emerging from a cellular element-based active system and a novel analysis of the aster condensation. The system consists of rhodamine labeled microtubules which are dynamically coupled by functionalized kinesin motor proteins cross-linked via streptavidin-coated quantum dots (QDs). The aster-shaped objects contain core structures. The cores are aggregates of the QD-motor protein complexes, and result from the dynamic condensation of sub-clusters that are connected to each other randomly. The structural specificity of the aster core reflects a configuration of the initial connectivity between sub-clusters. Detailed image analysis allows us to extract a novel correlation between the condensation speed and the sub-cluster separation. The size of the core is scaled down during the condensation process, following a power law dependence on the distance between sub-clusters. The exponent of the power law is close to two, as expected from a geometric model. This single exponent common to all the contractile lines implies that there exists a time regime during which an isomorphic contraction of the aster core continues during the condensation process. We analyze the observed contraction by using a model system with potential applicability in a wide range of emergent phenomena in randomly coupled active networks, which are prevalent in the cellular environment.

Context-specific functional module based drug efficacy prediction

Background

It is necessary to evaluate the efficacy of individual drugs on patients to realize personalized medicine. Testing drugs on patients in clinical trial is the only way to evaluate the efficacy of drugs. The approach is labour intensive and requires overwhelming costs and a number of experiments. Therefore, preclinical model system has been intensively investigated for predicting the efficacy of drugs. Current computational drug sensitivity prediction approaches use general biological network modules as their prediction features. Therefore, they miss indirect effectors or the effects from tissue-specific interactions.

Results

We developed cell line specific functional modules. Enriched scores of functional modules are utilized as cell line specific features to predict the efficacy of drugs. Cell line specific functional modules are clusters of genes, which have similar biological functions in cell line specific networks. We used linear regression for drug efficacy prediction. We assessed the prediction performance in leave-one-out cross-validation (LOOCV). Our method was compared with elastic net model, which is a popular model for drug efficacy prediction. In addition, we analysed drug sensitivity-associated functions of five drugs - lapatinib, erlotinib, raloxifene, tamoxifen and gefitinib- by our model.

Conclusions

Our model can provide cell line specific drug efficacy prediction and also provide functions which are associated with drug sensitivity. Therefore, we could utilize drug sensitivity associated functions for drug repositioning or for suggesting secondary drugs for overcoming drug resistance.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1078-6) contains supplementary material, which is available to authorized users.

Prediction of promoters and enhancers using multiple DNA methylation-associated features

Background

Regulatory regions (e.g. promoters and enhancers) play an essential role in human development and disease. Many computational approaches have been developed to predict the regulatory regions using various genomic features such as sequence motifs and evolutionary conservation. However, these DNA sequence-based approaches do not reflect the tissue-specific nature of the regulatory regions. In this work, we propose to predict regulatory regions using multiple features derived from DNA methylation profile.

Results

We discovered several interesting features of the methylated CpG (mCpG) sites within regulatory regions. First, a hypomethylation status of CpGs within regulatory regions, compared to the genomic background methylation level, extended out >1000 bp from the center of the regulatory regions, demonstrating a high degree of correlation between the methylation statuses of neighboring mCpG sites. Second, when a regulatory region was inactive, as determined by histone mark differences between cell lines, methylation level of the mCpG site increased from a hypomethylated state to a hypermethylated state, the level of which was even higher than the genomic background. Third, a distinct set of sequence motifs was overrepresented surrounding mCpG sites within regulatory regions. Using 5 types of features derived from DNA methylation profiles, we were able to predict promoters and enhancers using machine-learning approach (support vector machine). The performances for prediction of promoters and enhancers are quite well, showing an area under the ROC curve (AUC) of 0.992 and 0.817, respectively, which is better than that simply based on methylation level, especially for prediction of enhancers.

Conclusions

Our study suggests that DNA methylation features of mCpG sites can be used to predict regulatory regions.

Towards a global system of vigilance and surveillance in unrelated donors of haematopoietic progenitor cells for transplantation

Safety of living donors is critical to the success of blood, tissue and organ transplantation. Structured and robust vigilance and surveillance systems exist as part of some national entities, but historically no global systems are in place to ensure conformity, harmonisation and the recognition of rare adverse events (AEs). The World Health Assembly has recently resolved to require AE/reaction (AE/R) reporting both nationally and globally. The World Marrow Donor Association (WMDA) is an international organisation promoting the safety of unrelated donors and progenitor cell products for use in haematopoietic progenitor cell (HPC) transplantation. To address this issue, we established a system for collecting, collating, analysing, distributing and reacting to serious adverse events and reactions (SAE/R) in unrelated HPC donors. The WMDA successfully instituted this reporting system with 203 SAE/R reported in 2011. The committee generated two rapid reports, reacting to specific SAE/R, resulting in practice changing policies. The system has a robust governance structure, formal feedback to the WMDA membership and transparent information flows to other agencies, specialist physicians and transplant programs and the general public.