Peripheral blood cellular dynamics of rheumatoid arthritis treatment informs about efficacy of response to disease modifying drugs

Rheumatoid arthritis (RA) is an autoimmune disease characterized by systemic inflammation and is mediated by multiple immune cell types. In this work, we aimed to determine the relevance of changes in cell proportions in peripheral blood mononuclear cells (PBMCs) during the development of disease and following treatment. Samples from healthy blood donors, newly diagnosed RA patients, and established RA patients that had an inadequate response to MTX and were about to start tumor necrosis factor inhibitors (TNFi) treatment were collected before and after 3 months of treatment. We used in parallel a computational deconvolution approach based on RNA expression and flow cytometry to determine the relative cell-type frequencies. Cell-type frequencies from deconvolution of gene expression indicate that monocytes (both classical and non-classical) and CD4⁺ cells (T_h1 and T_h2) were increased in RA patients compared to controls, while NK cells and B cells (naïve and mature) were significantly decreased in RA patients. Treatment with MTX caused a decrease in B cells (memory and plasma cell), and a decrease in CD4 T_h cells (T_h1 and T_h17), while treatment with TNFi resulted in a significant increase in the population of B cells. Characterization of the RNA expression patterns found that most of the differentially expressed genes in RA subjects after treatment can be explained by changes in cell frequencies (98% and 74% respectively for MTX and TNFi).

Molecular signature of methotrexate response among rheumatoid arthritis patients

Background

Methotrexate (MTX) is the first line treatment for rheumatoid arthritis (RA), but failure of satisfying treatment response occurs in a significant proportion of patients. Here we present a longitudinal multi-omics study aimed at detecting molecular and cellular processes in peripheral blood associated with a successful methotrexate treatment of rheumatoid arthritis.

Methods

Eighty newly diagnosed patients with RA underwent clinical assessment and donated blood before initiation of MTX, and 3 months into treatment. Flow cytometry was used to describe cell types and presence of activation markers in peripheral blood, the expression of 51 proteins was measured in serum or plasma, and RNA sequencing was performed in peripheral blood mononuclear cells (PBMC). Response to treatment after 3 months was determined using the EULAR response criteria. We assessed the changes in biological phenotypes during treatment, and whether these changes differed between responders and non-responders with regression analysis. By using measurements from baseline, we also tried to find biomarkers of future MTX response or, alternatively, to predict MTX response.

Results

Among the MTX responders, (Good or Moderate according to EULAR treatment response classification, n = 60, 75%), we observed changes in 29 partly overlapping cell types proportions, levels of 13 proteins and expression of 38 genes during treatment. These changes were in most cases suppressions that were stronger among responders compared to non-responders. Within responders to treatment, we observed a suppression of FOXP3 gene expression, reduction of immunoglobulin gene expression and suppression of genes involved in cell proliferation. The proportion of many HLA-DR expressing T-cell populations were suppressed in all patients irrespective of clinical response, and the proportion of many IL21R+ T-cells were reduced exclusively in non-responders. Using only the baseline measurements we could not detect any biomarkers or prediction models that could predict response to MTX.

Conclusion

We conclude that a deep molecular and cellular phenotyping of peripheral blood cells in RA patients treated with methotrexate can reveal previously not recognized differences between responders and non-responders during 3 months of treatment with MTX. This may contribute to the understanding of MTX mode of action and explain non-responsiveness to MTX therapy.

Diagnostic usefulness of spiroergometry and risk factors of long -COVID in patients with normal left ventricular ejection fraction

Background

Recent evidence has shown that patients with acute SARS-CoV-2 infection might present symptoms of infection a long time after a recovery.

Purpose

To investigate the risk factors and assess the utility of spiroergometry parameters in differential diagnosing patients presenting the symptoms (dyspnea, fatique, pain in chest, muscle pain, cognitive impairment, taste and smell disturbances) persisting for a few months after recovery from COVID 19 (symptoms of long COVID).

Methods and results

The 146 patients (pts) with normal left ventricular ejection fraction and without respiratory diseases, hospitalised in Cardiology Department recovering from COVID-19 at three to six months after confirmed diagnosis were included. The clinical examination, laboratory results, echocardiography using Vivid E95–GE Healthcare, non-invasive body mass analysis using Body Composition Analyzer (Tanita Pro), spiroergometry using The MetaSoft® Studio application were analyzed. The subjects were divided into the two following groups: group demonstrating long COVID symptoms (i.e. suffering from one of the following dyspnea, fatique, pain in chest, muscle pain, cognitive impairment, taste or smell disturbances) [N=44 pts] and the group without long COVID symptoms [N=102 pts]. Pts with long COVID symptoms presented significantly higher age (58 versus [vs] 44 years; p<0.0001), higher metabolic age (53 vs 45 years; p=0.01), higher left atrial diameter (37 vs 35 mm; p=0.04), higher left ventricular mass index (LVMI) (83 vs 74 g/m2, p=0.03), higher E/E' (7.3 vs 6; p<0.001) compared to control group. In CPET long COVID pts presented lower forced vital capacity (FVC) (3.6 vs 4.3 L; p=0.009), lower maximal oxygen consumption measured during incremental exercise indexed per kilogram (VO2max) (21 vs 23 ml/min/kg; p=0.04), lower respiratory exchange ratio (RER) (1.0 vs 1.1; p=0.04); lower forced expiratory volume in one second (FEV1) (2.9 vs 3.25 L; p=0,03); higher ratio of forced expiratory volume in one second to forced vital capacity (FEV1/FVC) (106 vs 100%; p=0.0002) – Figure 1, there were no significant changes in electrocardiogram between groups. The laboratory results pointed that pts with long COVID symptoms had also lower rate of red blood cells (RBC) (4,4 vs 4,6 mln; p=0.01); higher level of glucose (92 vs 90 mg%; p=0.02); lower glomerular filtration rate (GFR) estimate by Modification of Diet in Renal Disease (MDRD) (88 vs 95; p=0.02); higher level of hypersensitive cardiac Troponin T (hsTnT) (6.1 vs 3.9 ng/L; p=0.03). The parameters significant in univariate analyses were included to the multivariate model. The results of multiple logistic regression were as follows: age (OR 4.6, 95% CI: 1.7–11.5; p=0.001) and LVMI (OR 2.5, 95% CI: 1.0–6.6; p=0.04).

Conclusions

Persistent symptoms in long COVID can mimic those of cardiovascular disease. Spiroergometric parameters are useful in making a proper diagnosis.

Funding Acknowledgement

Type of funding sources: Public hospital(s). Main funding source(s): Polish Mother's Memorial Hospital Research Institute

Factors of persistent limited exercise tolerance in patients after COVID-19 with normal left ventricular ejection fraction

Background

Exercise intolerance de novo is one of the most common reported symptoms in patients (pts) recovering from COVID-19.

Purpose

The present study determines etiological and pathophysiological factors influencing the mechanism of exercise intolerance in the COVID-19 survivors. Therefore, the factors affecting percent predicted oxygen uptake at peak exercise VO2 (%VO2pred) in pts after COVID-19 with normal left ventricular ejection fraction were assessed.

Methods and results

The 120 consecutive patients from the Department of Cardiology recovering from COVID-19 at three to six months after confirmed diagnosis were included. The clinical examinations, laboratory test results, echocardiography using Vivid E95 – GE Healthcare, non-invasive body mass analysis using Body Composition Analyzer (Tanita Pro), and spiroergometry using The MetaSoft® Studio application were analysed. The subjects were divided into the two following groups: study i.e. pts with worse oxygen uptake (%VO2pred <80%; N=47) and control including these cases with %VO2pred ≥80% (N=73) – Table 1. Pts with %VO2pred <80% presented significantly lower global peak systolic strain (GLPS) [p=0.03], tricuspid annular plane systolic excursion (TAPSE) [p=0.002] and late diastolic filling velocity (A) [p=0.004] compared to controls – Figure 1. The male gender (p=0.007) and the percent of total body water content (TBW %) (p=0.02) were significantly higher in study in comparison to the control group. The results of multiple logistic regression model independently associated with %VO2pred were as follows: A (OR 0.4, 95% CI: 0.17–0.95; p=0.03) and gender (OR 2.52, 95% CI: 1.07–5.91; p=0.03).

Conclusions

Males have over twice risk of persistent limited exercise tolerance after COVID-19 infection than females. The lower late diastolic filling velocity, tricuspid annular plane systolic excursion, worse global peak systolic strain, and hydration status are connected with limited exercise tolerance after COVID-19 in patients with normal left ventricular ejection fraction.

Funding Acknowledgement

Type of funding sources: None.

Post-COVID-19 cardiovascular complications and their association with clinical characteristics, symptoms and comorbidities – the LATE-COVID study

Background

Among many complications of coronavirus disease 2019 (COVID-19) there is a wide range of cardiovascular (CV) problems ranging from mild to severe ones. Even asymptomatic patients and those with mild course of COVID-19 may develop severe CV complications. Factors leading to such state have not been extensively studied so far.

Purpose

We aimed to assess which factors were linked to the severe complications of COVID-19.

Methods

We included 200 consecutive patients admitted to the Department of Cardiology and Adult Congenital Heart Diseases of the Polish Mother's Memorial Research Institute (PMMHRI) due to post-Covid cardiovascular complications. SARS-CoV2 infection was confirmed with real-life PCR testing. Laboratory tests, 24-hour ECG monitoring and echocardiography were performed in all patients from the investigated group. For the purposes of our study severe complications were defined as: myocarditis, a decrease of ejection fraction >10% from the pre-disease value, thromboembolic complications, angina pectoris requiring myocardial revascularization and the new onset of atrial fibrillation of supraventricular tachycardia. Some patients presented more than one of the above. Statistical analysis was performed using the software Statistica v.13 (TIBCO Software Inc., Palo Alto, CA, USA). Data were presented as mean ±SD or median (25th-75th percentile) for continuous variables and as proportions for categorical variables. Comparisons between groups were performed using Student's t-test for independent variables and the Mann-Whitney U test or χ2 test with Yates's correction, as appropriate. For all calculations p-values <0.05 were considered statistically significant.

Results

Finally, we included 200 consecutive patients (aged 54±16 years, 76 males – 38%), hospitalized for COVID-19 complications after a median 3 (2–6) months following the acute phase of infection. On admission patients presented with dyspnea (23%), impairment of exercise tolerance (47%), chest pain (32%), increase in blood pressure (29%), palpitations (25%), weight loss (13%), brain fog (6%), general malaise (11%), headache (5%), limb pain (13%), swelling (14%). Severe complications of COVID-19 were diagnosed in 31 patients (16%).Taking into consideration symptoms, the presence of severe COVID-19 complications was significantly associated with dyspnoea and deterioration of exercise tolerance. In comparison to patients with mild complications, severe ones were linked to age (the older patients, the higher risk), previous history of heart failure and diabetes mellitus. We did not observe statistically significant differences in severity of complications depending on smoking status (Tables 1 and 2).

Conclusions

Previous history of heart failure and diabetes mellitus as well as symptoms (dyspnoea and deterioration of exercise tolerance) along with older age are related to more severe complications following COVID-19.

Funding Acknowledgement

Type of funding sources: None.

RA-MAP, molecular immunological landscapes in early rheumatoid arthritis and healthy vaccine recipients

Rheumatoid arthritis (RA) is a chronic inflammatory disorder with poorly defined aetiology characterised by synovial inflammation with variable disease severity and drug responsiveness. To investigate the peripheral blood immune cell landscape of early, drug naive RA, we performed comprehensive clinical and molecular profiling of 267 RA patients and 52 healthy vaccine recipients for up to 18 months to establish a high quality sample biobank including plasma, serum, peripheral blood cells, urine, genomic DNA, RNA from whole blood, lymphocyte and monocyte subsets. We have performed extensive multi-omic immune phenotyping, including genomic, metabolomic, proteomic, transcriptomic and autoantibody profiling. We anticipate that these detailed clinical and molecular data will serve as a fundamental resource offering insights into immune-mediated disease pathogenesis, progression and therapeutic response, ultimately contributing to the development and application of targeted therapies for RA.

The relationship of dehydration and body mass index with the occurrence of atrial fibrillation in heart failure patients

Background/Introduction

Heart failure (HF) and atrial fibrillation (AF) are two conditions that are likely to dominate the next years of cardiovascular (CV) care. These diseases frequently coexist and they can beget one another due to similar risk factors and similar pathophysiology.

Purpose

The aim of the study was to assess the relationship of dehydration, body mass index (BMI) and other indices with the occurrence of AF in HF patients.

Methods

The study included 113 patients [median age 64 years; 57.52% male] hospitalized due to HF. Baseline demographics, body mass analysis, echocardiographic results, key cardiopulmonary exercise test (CPET) parameters, six minute walk distance (6MWD) and Kansas City Cardiomyopathy Questionnaire (KCCQ) score were assessed.

Results

Of all patients, 23 (20.35%) had AF, and 90 (79.65%) had sinus rhythm (SR). Patients with AF were older (med. 66 vs 64 years; p=0.039), with higher BMI (32.02 vs. 28.51 kg/m2; p=0.017) and percentage of fat content (37.0 vs. 27.9%, p=0.014). They were more dehydrated, with a lower percentage of total body water (TBW%) (45.7 vs 50.0%; p=0.022). Clinically, patients with AF had more often higher New York Heart Association (NYHA) class (III vs II; p<0.001), shorter 6MWD (median 292.35 vs 378.4 m; p=0.001) and a lower KCCQ overall summary score (52.60 vs 73.96 points; p=0.002). Patients with AF had significantly lower exercise capacity as measured by peak oxygen consumption (peak VO2) (0.92 vs 1.26 mL/min, p=0.016), peak VO2/kg (11 vs. 15 mL/kg/min; p<0.001), and percentage of predicted VO2max (pp-peak VO2) (62.5 vs 70.0; p=0.010). We also found VE/VCO2 (med.33.85 vs 32.20; p=0.049) to be higher and peak oxygen pulse (8.5 vs 11 mL/beat; p=0.038) to be lower in patients with AF than in patients without AF. In a multiple logistic regression model higher BMI (OR 1.23 per unit increase, p<0.001) and higher left atrial volume index (LAVI) (OR 1.07 per unit increase, p=0.03), lower tricuspid annular plane systolic excursion (TAPSE) (OR 0.74 per unit increase, p=0.03) and lower TBW% in body mass analysis (OR 0.90 per unit increase, p=0.03) were independently related to AF in patients with HF.

Conclusions

Increased volume of left atrium and right ventricular systolic dysfunction are well-known predictors of AF occurrence in patients with HF, but hydration status and increased body mass also seem to be important factors of AF in HF patients.

Funding Acknowledgement

Type of funding sources: None. Figure 1

Hydration status, BMI and troponin as factors of an impaired exercise tolerance in women over 40 with arterial hypertension

Purpose

The aim was to identify factors influencing maximal oxygen uptake (VO2max) and early identification of hypertensive women at risk of heart failure (HF).

Methods

The 185 consecutive females with controlled hypertension were divided according VO2max quartiles. The patients underwent echocardiography, non-invasive body mass analysis, spiroergometry and hemodynamic parameters. Regression analyses determined predictors of the lowest VO2max (quartile 1: VO2max <17 ml/kg/min).

Results

Females with the worst oxygen consumption had significantly higher level of high sensitive cardiac Troponin T (hs-cTnT) [p=0.001], higher values of the left atrial (LA) volume, late diastolic mitral annulus velocity (A'), ratio of peak velocity of early diastolic transmitral flow to peak velocity of early diastolic mitral annular motion (E/E') [p=0.0003, p=0.02, p=0.04; respectively] and lower E' [p=0.001] compared to controls. Women with the worst exercise capacity had higher body mass index (BMI) and fat content (kg and %) [p<0.0001], higher fat free mass (FFM) (kg) [p<0.0001], higher total body water content (TBW) [p=0.0002] as well as extracellular body water content (ECW) [p<0.0001] and intracellular body water content (ICW) [p=0.005], ECW/TBW x 100% [p<0.0001] and metabolic age [p<0.0001] compared to counterparts. In a multiple logistic regression model independently associated with VO2max were: ECW/TBW x 100% (OR 4.45, 95% CI: 1.77–11.21; p=0.002) Figure 1, BMI (OR 7.11, 95% CI: 2.01–25.11; p=0.002) Figure 2 and hs-cTnT level (OR 2.69, 95% CI: 1.23–5.91; p=0.013).

Conclusions

High-sensitivity cardiac troponin may serve as early biomarker of heart failure in hypertensive women. Hydration status should be considered in overall hypertensive women care. There is an importance of body mass compartments analysis in early identification of hypertensive females at risk of heart failure.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): The Project is financed by the Polish National Agency for Academic Exchange under the Foreign Promotion Programme. Figure 1Figure 2

Early Prediction of Clinical Response to Anti-TNF Treatment using Multi-omics and Machine Learning in Rheumatoid Arthritis

Objectives

Advances in immunotherapy by blocking TNF have remarkably improved treatment outcomes for Rheumatoid arthritis (RA) patients. Although treatment specifically targets TNF, the downstream mechanisms of immune suppression are not completely understood. The aim of this study was to detect biomarkers and expression signatures of treatment response to TNF inhibition.

Methods

Peripheral blood mononuclear cells (PBMCs) from 39 female patients were collected before anti-TNF treatment initiation (day 0) and after 3 months. The study cohort included patients previously treated with MTX who failed to respond adequately. Response to treatment was defined based on the EULAR criteria and classified 23 patients as responders and 16 as non-responders. We investigated differences in gene expression in PBMCs, the proportion of cell types and cell phenotypes in peripheral blood using flow cytometry and the level of proteins in plasma. Finally, we used machine learning models to predict non-response to anti-TNF treatment.

Results

The gene expression analysis in baseline samples revealed notably higher expression of the gene EPPK1 in future responders. We detected the suppression of genes and proteins following treatment, including suppressed expression of the T cell inhibitor gene CHI3L1 and its protein YKL-40. The gene expression results were replicated in an independent cohort. Finally, machine learning models mainly based on transcriptomic data showed high predictive utility in classifying non-response to anti-TNF treatment in RA.

Conclusions

Our integrative multi-omics analyses identified new biomarkers for the prediction of response, found pathways influenced by treatment and suggested new predictive models of anti-TNF treatment in RA patients.

What Is the Persistence to Methotrexate in Rheumatoid Arthritis, and Does Machine Learning Outperform Hypothesis-Based Approaches to Its Prediction?

OBJECTIVE

The objectives of this study were to assess the 1-year persistence to methotrexate (MTX) initiated as the first ever conventional synthetic disease-modifying antirheumatic drug in new-onset rheumatoid arthritis (RA) and to investigate the marginal gains and robustness of the results by increasing the number and nature of covariates and by using data-driven, instead of hypothesis-based, methods to predict this persistence.

METHODS

Through the Swedish Rheumatology Quality Register, linked to other data sources, we identified a cohort of 5475 patients with new-onset RA in 2006-2016 who were starting MTX monotherapy as their first disease-modifying antirheumatic drug. Data on phenotype at diagnosis and demographics were combined with increasingly detailed data on medical disease history and medication use in four increasingly complex data sets (48-4162 covariates). We performed manual model building using logistic regression. We also performed five different machine learning (ML) methods and combined the ML results into an ensemble model. We calculated the area under the receiver operating characteristic curve (AUROC) and made calibration plots. We trained on 90% of the data, and tested the models on a holdout data set.

RESULTS

Of the 5475 patients, 3834 (70%) remained on MTX monotherapy 1 year after treatment start. Clinical RA disease activity and baseline characteristics were most strongly associated with the outcome. The best manual model had an AUROC of 0.66 (95% confidence interval [CI] 0.60-0.71). For the ML methods, Lasso regression performed best (AUROC = 0.67; 95% CI 0.62-0.71).

CONCLUSION

Approximately two thirds of patients with early RA who start MTX remain on this therapy 1 year later. Predicting this persistence remains a challenge, whether using hypothesis-based or ML models, and may yet require additional types of data.

Distinct clinical phenotypes for Crohn's disease derived from patient surveys

Background

Defining clinical phenotypes provides opportunities for new diagnostics and may provide insights into early intervention and disease prevention. There is increasing evidence that patient-derived health data may contain information that complements traditional methods of clinical phenotyping. The utility of these data for defining meaningful phenotypic groups is of great interest because social media and online resources make it possible to query large cohorts of patients with health conditions.

Methods

We evaluated the degree to which patient-reported categorical data is useful for discovering subclinical phenotypes and evaluated its utility for discovering new measures of disease severity, treatment response and genetic architecture. Specifically, we examined the responses of 1961 patients with inflammatory bowel disease to questionnaires in search of sub-phenotypes. We applied machine learning methods to identify novel subtypes of Crohn’s disease and studied their associations with drug responses.

Results

Using the patients’ self-reported information, we identified two subpopulations of Crohn’s disease; these subpopulations differ in disease severity, associations with smoking, and genetic transmission patterns. We also identified distinct features of drug response for the two Crohn’s disease subtypes. These subtypes show a trend towards differential genotype signatures.

Conclusion

Our findings suggest that patient-defined data can have unplanned utility for defining disease subtypes and may be useful for guiding treatment approaches.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12876-021-01740-6.

Degree for weakly upper semicontinuous perturbations of quasi-m-accretive operators

In the paper, we provide the construction of a coincidence degree being a homotopy invariant detecting the existence of solutions of equations or inclusions of the form Ax ∈ F(x), x ∈ U, where [Formula: see text] is an m-accretive operator in a Banach space E, [Formula: see text] is a weakly upper semicontinuous set-valued map constrained to an open subset U of a closed set K ⊂ E. Two different approaches are presented. The theory is applied to show the existence of non-trivial positive solutions of some nonlinear second-order partial differential equations with discontinuities. This article is part of the theme issue 'Topological degree and fixed point theories in differential and difference equations'.

P17 Prediction of response of methotrexate in patients with rheumatoid arthritis using serum lipidomics

Background

For patients with rheumatoid arthritis (RA), introduction of early, effective therapy has consistently been shown to improve long-term outcomes. Low-dose methotrexate (MTX) is commonly prescribed as first-line treatment for RA. However, MTX is not effective for a large minority of patients and there is currently no way to determine ahead of therapy which patients are most likely to benefit. Metabolomics and lipidomics are emerging approaches for studying patient stratification in RA and have the potential to identify disease processes that underpin treatment outcomes. Here we apply state-of-the-art machine learning algorithms to predict MTX treatment response, by testing serum lipid levels measured at two time-points (pre-treatment and following 4 weeks on drug) to predict MTX response by 6 months.

Methods

This study included patients from the Rheumatoid Arthritis Medication Study (RAMS), a UK multi-centre one-year prospective observational study investigating predictors of response to MTX in patients with RA. Since 2008, patients who are about to start MTX for the first time are asked to provide demographic and clinical data, as well as blood samples to permit DNA, RNA and serum-based biomarker studies. Patients about to commence MTX treatment were followed longitudinally and those categorised as good or non-responders following 6 months on-drug using EULAR response criteria were analysed. Serum lipid levels were measured at pre-treatment and following 4 weeks on drug using ultra-performance liquid chromatography tailored for complex lipid analysis, coupled to mass spectrometry. State-of-the-art supervised machine learning methods were then applied to predict EULAR response at 6 months. Models including lipid levels were compared to models including clinical covariates (including: MTX start dose, steroid use at inclusion, BMI, number of swollen joints, number of tender joints, CRP levels, patients’ assessment of their overall wellbeing, gender, age-at-inclusion, age-at-onset, disease duration, HAQ score and pre-treatment smoking habits).

Results

Following quality control, 3,366 features (1,060 in negatively-charged mode and 2,306 in positive mode) were available for analysis at pre-treatment and 4 weeks from 100 RA patients categorised as good (GR, n = 50) or poor (NR, n = 50) responders to MTX following 6 months on drug. The best model performance for the classifier including clinical covariates was observed using L1/L2-regularised logistic regression (ROC AUC 0.68 ± 0.02). However, the clinical covariate model outperformed the classifier including lipid levels when either pre- or on-treatment time-points were investigated (ROC AUC 0.61 ± 0.02).

Conclusion

These data do not support the utility of early treatment lipidomic monitoring in routine clinical practice in patients started on MTX for their RA.

Disclosures

M. Maciejewski: Shareholder/stock ownership; owns stock or stock options in Pfizer. C. Sands None. N. Nair None. S. Ling None. S. Verstappen None. K. Hyrich None. A. Barton None. D. Ziemek Shareholder/stock ownership; owns stock or stock options in Pfizer. M. Lewis None. D. Plant None.

Standard machine learning approaches outperform deep representation learning on phenotype prediction from transcriptomics data

BACKGROUND

The ability to confidently predict health outcomes from gene expression would catalyze a revolution in molecular diagnostics. Yet, the goal of developing actionable, robust, and reproducible predictive signatures of phenotypes such as clinical outcome has not been attained in almost any disease area. Here, we report a comprehensive analysis spanning prediction tasks from ulcerative colitis, atopic dermatitis, diabetes, to many cancer subtypes for a total of 24 binary and multiclass prediction problems and 26 survival analysis tasks. We systematically investigate the influence of gene subsets, normalization methods and prediction algorithms. Crucially, we also explore the novel use of deep representation learning methods on large transcriptomics compendia, such as GTEx and TCGA, to boost the performance of state-of-the-art methods. The resources and findings in this work should serve as both an up-to-date reference on attainable performance, and as a benchmarking resource for further research.

RESULTS

Approaches that combine large numbers of genes outperformed single gene methods consistently and with a significant margin, but neither unsupervised nor semi-supervised representation learning techniques yielded consistent improvements in out-of-sample performance across datasets. Our findings suggest that using l2-regularized regression methods applied to centered log-ratio transformed transcript abundances provide the best predictive analyses overall.

CONCLUSIONS

Transcriptomics-based phenotype prediction benefits from proper normalization techniques and state-of-the-art regularized regression approaches. In our view, breakthrough performance is likely contingent on factors which are independent of normalization and general modeling techniques; these factors might include reduction of systematic errors in sequencing data, incorporation of other data types such as single-cell sequencing and proteomics, and improved use of prior knowledge.

Peptide-TLR-7/8a conjugate vaccines chemically programmed for nanoparticle self-assembly enhance CD8 T-cell immunity to tumor antigens

Personalized cancer vaccines targeting patient-specific neoantigens are a promising cancer treatment modality; however, neoantigen physicochemical variability can present challenges to manufacturing personalized cancer vaccines in an optimal format for inducing anticancer T cells. Here, we developed a vaccine platform (SNP-7/8a) based on charge-modified peptide-TLR-7/8a conjugates that are chemically programmed to self-assemble into nanoparticles of uniform size (~20 nm) irrespective of the peptide antigen composition. This approach provided precise loading of diverse peptide neoantigens linked to TLR-7/8a (adjuvant) in nanoparticles, which increased uptake by and activation of antigen-presenting cells that promote T-cell immunity. Vaccination of mice with SNP-7/8a using predicted neoantigens (n = 179) from three tumor models induced CD8 T cells against ~50% of neoantigens with high predicted MHC-I binding affinity and led to enhanced tumor clearance. SNP-7/8a delivering in silico-designed mock neoantigens also induced CD8 T cells in nonhuman primates. Altogether, SNP-7/8a is a generalizable approach for codelivering peptide antigens and adjuvants in nanoparticles for inducing anticancer T-cell immunity.

Causal modeling of TCGA, NSCLC, and HNSCC data to identify network drivers of tumor immune subtypes

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Background: Immune checkpoint inhibitors have achieved unprecedented success in several cancer types, yet only a subset of patients derives clinical benefit. Better understanding of tumor-immune interactions is imperative to improve clinical outcomes. Bayesian causal machine learning was applied on real world data to elucidate the molecular drivers of immune subtypes of tumors. Methods: Using a Reverse Engineering Forward Simulation (REFS) platform, ensembles of causal models were built on genomics, transcriptomics, and clinical data from 681 non-small cell lung carcinoma (NSCLC), 328 lung adeno (LUAD) and 353 lung squamous cell (LUSC), and 413 head and neck squamous cell carcinoma (HNSCC) patients from TCGA. The outcomes modeled were six tumor immune subtypes (Thorsson et al., 2018): wound-healing, IFNγ dominant, inflammatory, lymphocyte-depleted, immunologically quiet, and TGFβ dominant. Causal drivers of immune subtypes were identified from average causal effect (ACE) of the variables, as computed from the counterfactual simulations. ACE was defined as median of posterior distribution of odds ratio (1 vs 0 for discrete; 95th vs. 5th %ile for continuous variables). Results: The models showed impressive k-fold cross validation predictive performance (AUC ~ 0.8-0.9) for the most prevalent immune subtypes in TCGA: wound-healing and IFNg dominant in both LUAD and HNSCC, as well as inflammatory in LUAD. The potential causal drivers of the tumor immune subtypes and their ACE are listed in Table. The findings suggest that macrophage activation and polarization, which is driven in part by metabolic reprogramming, is a primary driver of tumor immune subtypes. Conclusions: Bayesian causal modeling revealed literature-supported hypotheses regarding predictors of response (CXCL13) and resistance (STK11 mutation, mTOR pathway) to PD-(L)1 blockade therapy. The additional target pathways such as AKT1/mTOR may be actionable for altering immunogenicity of tumors. [Table: see text]

P1311 A rare case of asymptomatic cyst in interatrial septum longterm observation

Background

Incidental findings in echocardiography performed from other indications are not always able to explain the patient condition as well as the observed pathology. However, review of literature, helps to find the most possible explanation. We present a case study of a patient with our proposal of possible diagnosis.

Case report

28-year old female with hypothyroidism and no other concomitant diseases presented with easy fatigue. Exercise stress test was clinically and ECG negative with 12,8 METs. Transthoracic echocardiography showed normal size of heart structures with preserved systolic and diastolic function of both left and right chamber. The only abnormality was a cystic structure of 44x31x34 cm in interatrial septum which was protruding to both left and right atrium and was not affecting the blood flow with normal gradients. We did not find any signs of inflammation nor infiltration to the heart walls. There was no flow inside the cyst with the use of colour Doppler. The structure had homogenous echolucency with very thin walls and a septum inside. As we did not find any connection between the cyst and the atriums we considered it as not harmful in terms of a risk of embolization. Patient was hemodynamically stable, there was no history of neurological dysfunctions nor atrioventricular conduction disturbances. Taking into account possible diagnoses for that patient we decided to schedule the patient for follow-ups. Ten years observation period confirmed that that our approach was proper. Serial echocardiographic studies showed no change in the cyst. In this year we performed multimodality imaging with CT and MRI, which showed the same views as echocardiography.

Discussion

The most possible diagnose for our patient is a bronchogenic cyst, a very rare congenital bronchopulmonary malformation of the foregut that is usually found incidentally with mostly asymptomatic benign course. Also the localization of the cyst confirms that diagnosis. Nevertheless the final diagnosis would be possible only in histopathological study.

The differential diagnosis should include a cystic myxoma and echinococcosis. However the structure is not polycystic and seems to have homogenous echolucency. We ruled out the blood cyst because of the lack of typical localization and connection to valves.

As long as the patient remains asymptomatic surgical resection remains controversial.

P253 Patient after correction of Taussig-Bing anomaly with severe neoaortic regurgitation and after sudden cardiac arrest

The Taussig –Bing anomaly is a rare congenital heart malformation that was first described in 1949 by Helen B. Taussig and Richard J. Bing. It is characterized by the presence of a large subpulmonic ventricular septal defect (VSD) and, usually, side-by-side great vessels that arise entirely from the right ventricle. Unlike TGA with VSD, this anomaly is characterized by the presence of a bilateral conus and the absence of aortomitral continuity. Increased pulmonary blood flow leads to early onset of pulmonary vascular disease, hence repair in the early infancy period is recommended. VSD closure combined with arterial switch is currently the preferred procedure. Lecompte introduced a new surgical technique that includes extensive resection of the conal septum and direct reimplantation of the pulmonary trunk on the superior margin of the right ventricular infundibulotomy.

We present case of 18-year-old male patient with Taussig-Bing anomaly after pulmonary artery binding and closure of ductus arteriosus when one year old and after anatomical Jatene correction with modified Lacompte procedure at the age of two years. The patient was admitted to our Department in October 2018 after episode of sudden cardiac arrest in the mechanism of ventricular fibrillation. Echocardiographic examination revealed preserved systolic function of both ventricles (LVEF 62%, TAPSE 25 mm, RV S’ 13cm/s) without contractility disturbances. The enlarged and hypertrophic left ventricle consists of the primary cavity connecting by VSD (size 39 mm) with a fragment of the right ventricle separated from the rest of the right ventricle by a patch with Gore-Tex acting as a ventricular septum - without any leakage features (Figure 1A and 1B). We noticed also enlarged left atrium, increased diameter of neoaorty bulb (50 mm), severe neoaortic regurgitation (AV max: 1,85 m/s, ERO-70, VC-8mm, PHT 327 ms) (Figure 1C), moderate mitral regurgitation (type I according Carpentier) (Figure1D). On 8.01.2019 a subcutaneous ICD Boston Scientific Emblem with a subcutaneous defibrillation electrode was implanted. In performed spiroergometry decreased peak oxygen consumption (2,24 ml/min/kg), the study was stopped because of fatique, assessed expiratory exchange ratio, and episode of nsVT. After decision of Heart Team the patient is qualified for surgical treatment of valve defects.

Abstract P253 Figure 1

P1452 A rare case of embolic blindness in an adult patient with univentricular heart after fontan operation

Background

Thromboembolic complications following Fontan procedure are one of the major causes of mortality and morbidity among patients with univentricular heart. We may classify thromboembolic complications into two groups: systemic- and nonsystemic. We present a case of a patient with a manifestation of both.

Case report

24-year old female, foreign student was admitted to Ophthalmology Department due to sudden blindness of the left eye. Performed studies revealed embolus in the left central retinal artery. Because the patient had the history of congenital heart defect she was referred to our department. Analysis of medical documentation showed that the patient has combined congenital heart defect including right ventricle hypoplasia, tricuspid atresia, pulmonic stenosis, ventricular septal defect, atrial septal defect and persistent ductus arteriosus. She had a history of two surgeries: modified left-side Blalock-Tausing connection (in 4th month of life) and total cavo-pulmonary connection with the closure of Blalock-Tausing and excision of interatrial septum (in 2,5 year of life). On admission she presented with left-eye blindness. She had no dyspnoea or palpitations. However she reported very severe migraines from a few days preceding the admission to hospital. Echocardiography revealed tricuspid atresia, hypoplastic right ventricle, preserved systolic and diastolic function of left ventricle, atrial septal defect with no restriction. We observed enlarged diameter of vena cava inferior with no respirophasic variations and massive thrombus in inside with very low flow. The connection between inferior vena cava and right pulmonary artery was working properly with no visible fenestration. We also observed a winding vessel between ascending aorta and truncus pulmonalis/pulmonary artery with continuous flow of blood from left to right side. Computer tomography confirmed the diagnosis of massive thrombosis of vena cava inferior. Patient had anticoagulation started. Two days later we the flow in inferior vena cava returned – we did not observe any thrombus. Patient was referred to catheterization and had chronic anticoagulation initiated.

Three months follow-up revealed no changes in clinical condition of a patient.

Discussion

The palliative Fontan operation predispose to the increased risk of thromboembolic complication. Despite the risk factors of such complications have been identified, there are no guidelines about prophylactic anticoagulation in that group of patients. As a result, chronic anticoagulation is initiated in patients who have other indications e.g. atrial fibrillation. It seems that it would be beneficial to define the group of patients after Fontan procedure with indications to chronic anticoagulation therapy despite arrhythmias.

Expression III: patients' expectations and preferences regarding physician-patient relationship and clinical management-results of the international NOGGO/ENGOT-ov4-GCIG study in 1830 ovarian cancer patients from European countries

Backround

The primary aim of this study was to investigate information needs and treatment preferences of patients with ovarian cancer, focusing especially on physician-patient relationship and treatment.

Patients and methods

A questionnaire was developed based on the experiences of the national German survey 'Expression II', and was provided to patients with ovarian cancer either at initial diagnosis or with recurrent disease via Internet (online-version) or as print-out-version.

Results

From December 2009 to October 2012, a total of 1830 patients with ovarian cancer from eight European countries (Austria, Belgium, France, Germany, Italy, Poland, Romania, Spain) participated, 902 (49.3%) after initial diagnosis and 731 (39.9%) with recurrent ovarian cancer. The median age was 58 years (range 17-89). Nearly all patients (96.2%) had experienced upfront surgery followed by first-line chemotherapy (91.8%). The majority of patients were satisfied with the completeness and comprehensibility of the explanation about the diagnosis and treatment options. The three most important aspects, identified by patients to improve the treatment for ovarian cancer included: 'the therapy should not induce alopecia' (42%), 'there must be more done to counter fatigue' (34.5%) and 'the therapy should be more effective' (29.7%). Out of 659 (36%) patients, who were offered participation in a clinical trial, 476 (26%) were included.

Conclusion

This study underlines the high need of patients with ovarian cancer for all details concerning treatment options irrespective of their cultural background, the stage of disease and the patient's age. Increased information requirements regarding potential side effects and treatment alternatives were recorded. Besides the need for more effective therapy, alopecia and fatigue are the most important side effects of concern to patients.

Molecular Profiling of Ulcerative Colitis Subjects from the TURANDOT Trial Reveals Novel Pharmacodynamic/Efficacy Biomarkers

BACKGROUND AND AIMS

To define pharmacodynamic and efficacy biomarkers in ulcerative colitis [UC] patients treated with PF-00547659, an anti-human mucosal addressin cell adhesion molecule-1 [MAdCAM-1] monoclonal antibody, in the TURANDOT study.

METHODS

Transcriptome, proteome and immunohistochemistry data were generated in peripheral blood and intestinal biopsies from 357 subjects in the TURANDOT study.

RESULTS

In peripheral blood, C-C motif chemokine receptor 9 [CCR9] gene expression demonstrated a dose-dependent increase relative to placebo, but in inflamed intestinal biopsies CCR9 gene expression decreased with increasing PF-00547659 dose. Statistical models incorporating the full RNA transcriptome in inflamed intestinal biopsies showed significant ability to assess response and remission status. Oncostatin M [OSM] gene expression in inflamed intestinal biopsies demonstrated significant associations with, and good accuracy for, efficacy, and this observation was confirmed in independent published studies in which UC patients were treated with infliximab or vedolizumab. Compared with the placebo group, intestinal T-regulatory cells demonstrated a significant increase in the intermediate 22.5-mg dose cohort, but not in the 225-mg cohort.

CONCLUSIONS

CCR9 and OSM are implicated as novel pharmacodynamic and efficacy biomarkers. These findings occur amid coordinated transcriptional changes that enable the definition of surrogate efficacy biomarkers based on inflamed biopsy or blood transcriptomics data.ClinicalTrials.gov identifierNCT01620255.

Profiling of Gene Expression Biomarkers as a Classifier of Methotrexate Nonresponse in Patients With Rheumatoid Arthritis

Objective

Approximately 30–40% of rheumatoid arthritis (RA) patients who are initially started on low‐dose methotrexate (MTX) will not benefit from the treatment. To date, no reliable biomarkers of MTX inefficacy in RA have been identified. The aim of this study was to analyze whole blood samples from RA patients at 2 time points (pretreatment and 4 weeks following initiation of MTX), to identify gene expression biomarkers of the MTX response.

Methods

RA patients who were about to commence treatment with MTX were selected from the Rheumatoid Arthritis Medication Study. Using European League Against Rheumatism (EULAR) response criteria, 42 patients were categorized as good responders and 43 as nonresponders at 6 months following the initation of MTX treatment. Data on whole blood transcript expression were generated, and supervised machine learning methods were used to predict a EULAR nonresponse. Models in which transcript levels were included were compared to models in which clinical covariates alone (e.g., baseline disease activity, sex) were included. Gene network and ontology analysis was also performed.

Results

Based on the ratio of transcript values (i.e., the difference in log₂‐transformed expression values between 4 weeks of treatment and pretreatment), a highly predictive classifier of MTX nonresponse was developed using L2‐regularized logistic regression (mean ± SEM area under the receiver operating characteristic [ROC] curve [AUC] 0.78 ± 0.11). This classifier was superior to models that included clinical covariates (ROC AUC 0.63 ± 0.06). Pathway analysis of gene networks revealed significant overrepresentation of type I interferon signaling pathway genes in nonresponders at pretreatment (P = 2.8 × 10⁻²⁵) and at 4 weeks after treatment initiation (P = 4.9 × 10⁻²⁸).

Conclusion

Testing for changes in gene expression between pretreatment and 4 weeks post–treatment initiation may provide an early classifier of the MTX treatment response in RA patients who are unlikely to benefit from MTX over 6 months. Such patients should, therefore, have their treatment escalated more rapidly, which would thus potentially impact treatment pathways. These findings emphasize the importance of a role for early treatment biomarker monitoring in RA patients started on MTX.

A probabilistic pathway score (PROPS) for classification with applications to inflammatory bowel disease

Summary

Gene-based supervised machine learning classification models have been widely used to differentiate disease states, predict disease progression and determine effective treatment options. However, many of these classifiers are sensitive to noise and frequently do not replicate in external validation sets. For complex, heterogeneous diseases, these classifiers are further limited by being unable to capture varying combinations of genes that lead to the same phenotype. Pathway-based classification can overcome these challenges by using robust, aggregate features to represent biological mechanisms. In this work, we developed a novel pathway-based approach, PRObabilistic Pathway Score, which uses genes to calculate individualized pathway scores for classification. Unlike previous individualized pathway-based classification methods that use gene sets, we incorporate gene interactions using probabilistic graphical models to more accurately represent the underlying biology and achieve better performance. We apply our method to differentiate two similar complex diseases, ulcerative colitis (UC) and Crohn's disease (CD), which are the two main types of inflammatory bowel disease (IBD). Using five IBD datasets, we compare our method against four gene-based and four alternative pathway-based classifiers in distinguishing CD from UC. We demonstrate superior classification performance and provide biological insight into the top pathways separating CD from UC.

Availability and Implementation

PROPS is available as a R package, which can be downloaded at http://simtk.org/home/props or on Bioconductor.

Contact

rbaltman@stanford.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Mendelian Disease Associations Reveal Novel Insights into Inflammatory Bowel Disease

Background

Monogenic diseases have been shown to contribute to complex disease risk and may hold new insights into the underlying biological mechanism of Inflammatory Bowel Disease (IBD).

Methods

We analyzed Mendelian disease associations with IBD using over 55 million patients from the Optum's deidentified electronic health records dataset database. Using the significant Mendelian diseases, we performed pathway enrichment analysis and constructed a model using gene expression datasets to differentiate Crohn's disease (CD), ulcerative colitis (UC), and healthy patient samples.

Results

We found 50 Mendelian diseases were significantly associated with IBD, with 40 being significantly associated with both CD and UC. Our results for CD replicated those from previous studies. Pathways that were enriched consisted of mainly immune and metabolic processes with a focus on tolerance and oxidative stress. Our 3-way classifier for UC, CD, and healthy samples yielded an accuracy of 72%.

Conclusions

Mendelian diseases that are significantly associated with IBD may reveal novel insights into the genetic architecture of IBD.

Reverse translation of adverse event reports paves the way for de-risking preclinical off-targets

The Food and Drug Administration Adverse Event Reporting System (FAERS) remains the primary source for post-marketing pharmacovigilance. The system is largely un-curated, unstandardized, and lacks a method for linking drugs to the chemical structures of their active ingredients, increasing noise and artefactual trends. To address these problems, we mapped drugs to their ingredients and used natural language processing to classify and correlate drug events. Our analysis exposed key idiosyncrasies in FAERS, for example reports of thalidomide causing a deadly ADR when used against myeloma, a likely result of the disease itself; multiplications of the same report, unjustifiably increasing its importance; correlation of reported ADRs with public events, regulatory announcements, and with publications. Comparing the pharmacological, pharmacokinetic, and clinical ADR profiles of methylphenidate, aripiprazole, and risperidone, and of kinase drugs targeting the VEGF receptor, demonstrates how underlying molecular mechanisms can emerge from ADR co-analysis. The precautions and methods we describe may enable investigators to avoid confounding chemistry-based associations and reporting biases in FAERS, and illustrate how comparative analysis of ADRs can reveal underlying mechanisms.

DOI:http://dx.doi.org/10.7554/eLife.25818.001

New treatments are tested in clinical trials before they are licensed for use in patients, but until the drugs are available for prescribing it’s not always possible to identify every side effect. When the drugs enter the clinic, they might be prescribed to patients with multiple medical conditions, or combined with other treatments. The drugs may also be taken for longer periods of time than tested in trials. It is therefore common for new adverse reactions to emerge after a drug is in widespread use.

The FDA Adverse Event Reporting System (FAERS) is a surveillance system used in the United States for reporting drug side effects after new treatments have been licensed. Healthcare professionals and patients can submit reports to the database, logging the adverse drug reactions that they have experienced.

FAERS currently contains over 8.5 million entries, and is growing all the time. However, Maciejewski et al. show that the database has several shortcomings that are reducing its usefulness. For instance, on average any given drug will have 16 different names in the system; this makes it challenging to group all of the reported side effects so that trends and patterns can be correctly seen.

To address this first problem, Maciejewski et al. grouped together drugs according to their active ingredients, rather than their name. This made it much easier to account for subsequent, and more crucial conflating factors such as multiple reports for the same adverse event and patient, or cases where adverse reactions were confused with the diseases that the drugs are trying to treat. For example, diabetes was listed as a side effect for drugs used to treat diabetes.

Building on this cleaned-up dataset, Maciejewski et al. monitored how adverse event signals evolve over time and uncovered biases that were hard to see otherwise. For example, side-effects were reported more often when drugs were in the news. More strikingly, this bias affected not only the drug in question, but also other drugs that acted in the same way or on the same molecular target.

The computational method developed by Maciejewski et al. allows the data in FAERS to be combined and corrected, making easier to evaluate the safety of different medicines. The link between adverse side effects and the molecular targets of the drug, via the ingredient’s chemical structure, furthermore makes it possible to analyze such clinical data reliably by using chemical and genetic information. In the future, this method could also help to identify previously unknown side effects and the biological mechanisms behind them. This could help researchers to develop new drugs with improved side effect profiles.

DOI:http://dx.doi.org/10.7554/eLife.25818.002

Implications of Dynamic Occupancy, Binding Kinetics, and Channel Gating Kinetics for hERG Blocker Safety Assessment and Mitigation

Blockade of the hERG potassium channel prolongs the ventricular action potential (AP) and QT interval, and triggers early after depolarizations (EADs) and torsade de pointes (TdP) arrhythmia. Opinions differ as to the causal relationship between hERG blockade and TdP, the relative weighting of other contributing factors, definitive metrics of preclinical proarrhythmicity, and the true safety margin in humans. Here, we have used in silico techniques to characterize the effects of channel gating and binding kinetics on hERG occupancy, and of blockade on the human ventricular AP. Gating effects differ for compounds that are sterically compatible with closed channels (becoming trapped in deactivated channels) versus those that are incompatible with the closed/closing state, and expelled during deactivation. Occupancies of trappable blockers build to equilibrium levels, whereas those of non-trappable blockers build and decay during each AP cycle. Occupancies of ~83% (non-trappable) versus ~63% (trappable) of open/inactive channels caused EADs in our AP simulations. Overall, we conclude that hERG occupancy at therapeutic exposure levels may be tolerated for nontrappable, but not trappable blockers capable of building to the proarrhythmic occupancy level. Furthermore, the widely used Redfern safety index may be biased toward trappable blockers, overestimating the exposure-IC50 separation in nontrappable cases.

[Metameric macular and papular skin mastocytosis]

BACKGROUND

Mastocytosis is characterised by the presence of abnormal quantities of mastocytes in one or more organs. Although it occurs in systemic forms of mastocytosis, isolated skin involvement is the predominant presentation, particularly in children, in the form of more or less extensive though non-systematic lesions. Herein, we report a case of maculopapular cutaneous mastocytosis that is unusual in terms of its metameric topography.

PATIENTS AND METHODS

A 16-year-old youth presented with an erythematous maculopapular rash of 18 months' duration and involving pruritic inflammatory episodes strictly localised in segment T8 to the left. The skin biopsy showed a significant increase in the number of dermal mastocytes (CD117+). No KIT mutations were found in the skin lesions nor in the unimpaired skin of the opposite side. Further investigations ruled out systemic mastocytis.

DISCUSSION

Herein, we report a case of cutaneous mastocytosis that is unusual in terms of its metameric disposition. There have been only two previous reports of segmental cutaneous mastocytis. The two pathological hypotheses involved precessional dermatitis that renders the skin surface susceptible to homing, and somatic mosaicism (type 1) with local mastocyte proliferation.

Public Domain HTS Fingerprints: Design and Evaluation of Compound Bioactivity Profiles from PubChem's Bioassay Repository

Molecular profiling efforts aim at characterizing the biological actions of small molecules by screening them in hundreds of different biochemical and/or cell-based assays. Together, these assays yield a rich data landscape of target-based and phenotypic effects of the tested compounds. However, submitting an entire compound library to a molecular profiling panel can easily become cost-prohibitive. Here, we make use of historical screening assays to create comprehensive bioactivity profiles for more than 300 000 small molecules. These bioactivity profiles, termed PubChem high-throughput screening fingerprints (PubChem HTSFPs), report small molecule activities in 243 different PubChem bioassays. Although the assays originate from originally independently pursued drug or probe discovery projects, we demonstrate their value as molecular signatures when used in combination. We use these PubChem HTSFPs as molecular descriptors in hit expansion experiments for 33 different targets and phenotypes, showing that, on average, they lead to 27 times as many hits in a set of 1000 chosen molecules as a random screening subset of the same size (average ROC score: 0.82). Moreover, we demonstrate that PubChem HTSFPs retrieve hits that are structurally diverse and distinct from active compounds retrieved by chemical similarity-based hit expansion methods. PubChem HTSFPs are made freely available for the chemical biology research community.

Experimental design strategy: weak reinforcement leads to increased hit rates and enhanced chemical diversity

High Throughput Screening (HTS) is a common approach in life sciences to discover chemical matter that modulates a biological target or phenotype. However, low assay throughput, reagents cost, or a flowchart that can deal with only a limited number of hits may impair screening large numbers of compounds. In this case, a subset of compounds is assayed, and in silico models are utilized to aid in iterative screening design, usually to expand around the found hits and enrich subsequent rounds for relevant chemical matter. However, this may lead to an overly narrow focus, and the diversity of compounds sampled in subsequent iterations may suffer. Active learning has been recently successfully applied in drug discovery with the goal of sampling diverse chemical space to improve model performance. Here we introduce a robust and straightforward iterative screening protocol based on naı̈ve Bayes models. Instead of following up on the compounds with the highest scores in the in silico model, we pursue compounds with very low but positive values. This includes unique chemotypes of weakly active compounds that enhance the applicability domain of the model and increase the cumulative hit rates. We show in a retrospective application to 81 Novartis assays that this protocol leads to consistently higher compound and scaffold hit rates compared to a standard expansion around hits or an active learning approach. We recommend using the weak reinforcement strategy introduced herein for iterative screening workflows.

The role of peroxisome-proliferator-activating receptor gamma agonists: rosiglitazone and 15-deoxy-delta12,14-prostaglandin J2 in chronic experimental cyclosporine A-induced nephrotoxicity

Cyclosporine A(CsA) is an immunosuppressor frequently used in the transplant surgery and in the treatment of autoimmune diseases. The therapeutic benefits of CsA are often limited by it's main side effect-nephrotoxicity. Mechanisms of chronic CsA- induced renal damage include: activation of renin-angiotensin-aldosterone system, upregulation of transforming growth factor beta (TGF-β), oxidative stress. This study was undertaken to investigate the protective effect of the peroxisome-proliferator-activated receptors gamma (PPARs-γ) agonists: rosiglitazone and 15-deoxy-Δ12,14-prostaglandin J2 (PGDJ2), against CsA-induced kidney injury in male Wistar rats. CsA was administered subcutaneously at a dose of 15 mg/kg/day for 28 days. Both PPAR-γ agonists were given for 28 days 0.5 hour before the administration of CsA. Rosiglitazone was administered orally at a dose of 8 mg/kg/day and PGDJ2 was given intraperitoneally at a dose of 30 μg/kg/day. CsA induced renal failure was evidenced by increased serum levels of urea, uric acid and creatinine. Serum concentrations of GSH and GSSG, lipid peroxidation products as well as NAD+/NADH, NADP+/NADPH and ADP/ATP ratios showed, that CsA induced oxidative stress and evoked an imbalanced red-ox state in the kidney. Light and electron microscope studies showed degenerative changes within renal tubules with damage to their mitochondria, interstitial fibrosis and arteriolopathy. Immunohistochemical expression of profibrotic TGF-β was assessed. The biochemical and morphological changes induced by CsA were limited by administration of both rosiglitazone and PGDJ2. Ultrastructural examination of renal tubular epithelial cells showed marked improvement within mitochondria. Our results indicate that both PPAR-γ agonists used in the experiment may play an important role in protecting against CsA-induced damage in the kidney.

Translation of off-target effects: prediction of ADRs by integrated experimental and computational approach

Adverse drug reactions (ADRs) are associated with most drugs, often discovered late in drug development and sometimes only during extended course of clinical use.

Decoding the components of dynamics in three-domain proteins

In this study, we examine the feasibility and limitations of describing the motional behavior of three-domain proteins in which the domains are linearly connected. In addition to attempting the determination of the internal and overall reorientational correlation times, we investigate the existence of correlations in the motions between the three domains. Since in linearly arranged three-domain proteins, there are typically no experimental data that can directly report on motional correlation between the first and the third domain, we address this question by dynamics simulations. Two limiting cases occur: (1) for weak repulsive potentials and (2) when strong repulsive potentials are applied between sequential domains. The motions of the terminal domains become correlated in the case of strong interdomain repulsive potentials when these potentials do not allow the angle between the sequential domains to be smaller than about 60°. Using the model-free (MF) and extended MF formalisms of Lipari and Szabo, we find that the motional behavior can be separated into two components; the first component represents the concerted overall motion of the three domains, and the second describes the independent component of the motion of each individual domain. We find that this division of the motional behavior of the protein is maintained only when their timescales are distinct and can be made when the angles between sequential domains remain between 60° and 160°. In this work, we identify and quantify interdomain motional correlations.

Using mutagenesis and structural biology to map the binding site for the Plasmodium falciparum merozoite protein PfRh4 on the human immune adherence receptor

To survive and replicate within the human host, malaria parasites must invade erythrocytes. Invasion can be mediated by the P. falciparum reticulocyte-binding homologue protein 4 (PfRh4) on the merozoite surface interacting with complement receptor type 1 (CR1, CD35) on the erythrocyte membrane. The PfRh4 attachment site lies within the three N-terminal complement control protein modules (CCPs 1-3) of CR1, which intriguingly also accommodate binding and regulatory sites for the key complement activation-specific proteolytic products, C3b and C4b. One of these regulatory activities is decay-accelerating activity. Although PfRh4 does not impact C3b/C4b binding, it does inhibit this convertase disassociating capability. Here, we have employed ELISA, co-immunoprecipitation, and surface plasmon resonance to demonstrate that CCP 1 contains all the critical residues for PfRh4 interaction. We fine mapped by homologous substitution mutagenesis the PfRh4-binding site on CCP 1 and visualized it with a solution structure of CCPs 1-3 derived by NMR and small angle x-ray scattering. We cross-validated these results by creating an artificial PfRh4-binding site through substitution of putative PfRh4-interacting residues from CCP 1 into their homologous positions within CCP 8; strikingly, this engineered binding site had an ∼30-fold higher affinity for PfRh4 than the native one in CCP 1. These experiments define a candidate site on CR1 by which P. falciparum merozoites gain access to human erythrocytes in a non-sialic acid-dependent pathway of merozoite invasion.

Solution structure of CCP modules 10-12 illuminates functional architecture of the complement regulator, factor H

The 155-kDa plasma glycoprotein factor H (FH), which consists of 20 complement control protein (CCP) modules, protects self-tissue but not foreign organisms from damage by the complement cascade. Protection is achieved by selective engagement of FH, via CCPs 1-4, CCPs 6-8 and CCPs 19-20, with polyanion-rich host surfaces that bear covalently attached, activation-specific, fragments of complement component C3. The role of intervening CCPs 9-18 in this process is obscured by lack of structural knowledge. We have concatenated new high-resolution solution structures of overlapping recombinant CCP pairs, 10-11 and 11-12, to form a three-dimensional structure of CCPs 10-12 and validated it by small-angle X-ray scattering of the recombinant triple-module fragment. Superimposing CCP 12 of this 10-12 structure with CCP 12 from the previously solved CCP 12-13 structure yielded an S-shaped structure for CCPs 10-13 in which modules are tilted by 80-110° with respect to immediate neighbors, but the bend between CCPs 10 and 11 is counter to the arc traced by CCPs 11-13. Including this four-CCP structure in interpretation of scattering data for the longer recombinant segments, CCPs 10-15 and 8-15, implied flexible attachment of CCPs 8 and 9 to CCP 10 but compact and intimate arrangements of CCP 14 with CCPs 12, 13 and 15. Taken together with difficulties in recombinant production of module pairs 13-14 and 14-15, the aberrant structure of CCP 13 and the variability of 13-14 linker sequences among orthologues, a structural dependency of CCP 14 on its neighbors is suggested; this has implications for the FH mechanism.

New analogs of the clinical complement inhibitor compstatin with subnanomolar affinity and enhanced pharmacokinetic properties

Therapeutic modulation of the complement system has become increasingly important in line with the growing recognition of the role of complement in numerous diseases. Compstatin, a peptidic inhibitor that acts at the central level of the complement cascade, is currently in clinical evaluation but routes to improve its efficacy have not yet been fully explored. Here, we report improvements in both the inhibitory potency and pharmacokinetic parameters of compstatin that broaden its clinical applications. Selective modification of the compstatin N-terminus with non-proteinogenic amino acids resulted in the first analogue with subnanomolar binding affinity (KD=0.5nM) and other similarly potent derivatives with improved solubility in clinically relevant solvents. Detailed structure-activity relationship studies based on biophysical and computational methods revealed key structural determinants for the observed improvements. Importantly, pharmacokinetic evaluation in non-human primates revealed target-driven elimination kinetics with plasma half-life values exceeding expectations for peptidic drugs (close to 12h). This successful optimization strategy is expected to pave the way for systemic administration of compstatin in a range of clinical conditions.

Estimation of interdomain flexibility of N-terminus of factor H using residual dipolar couplings

Characterization of segmental flexibility is needed to understand the biological mechanisms of the very large category of functionally diverse proteins, exemplified by the regulators of complement activation, that consist of numerous compact modules or domains linked by short, potentially flexible, sequences of amino acid residues. The use of NMR-derived residual dipolar couplings (RDCs), in magnetically aligned media, to evaluate interdomain motion is established but only for two-domain proteins. We focused on the three N-terminal domains (called CCPs or SCRs) of the important complement regulator, human factor H (i.e., FH1-3). These domains cooperate to facilitate cleavage of the key complement activation-specific protein fragment, C3b, forming iC3b that no longer participates in the complement cascade. We refined a three-dimensional solution structure of recombinant FH1-3 based on nuclear Overhauser effects and RDCs. We then employed a rudimentary series of RDC data sets, collected in media containing magnetically aligned bicelles (disklike particles formed from phospholipids) under three different conditions, to estimate interdomain motions. This circumvents a requirement of previous approaches for technically difficult collection of five independent RDC data sets. More than 80% of conformers of this predominantly extended three-domain molecule exhibit flexions of <40°. Such segmental flexibility (together with the local dynamics of the hypervariable loop within domain 3) could facilitate recognition of C3b via initial anchoring and eventual reorganization of modules to the conformation captured in the previously solved crystal structure of a C3b:FH1-4 complex.