Vocal learning-associated convergent evolution in mammalian proteins and regulatory elements

Vocal production learning ("vocal learning") is a convergently evolved trait in vertebrates. To identify brain genomic elements associated with mammalian vocal learning, we integrated genomic, anatomical, and neurophysiological data from the Egyptian fruit bat (Rousettus aegyptiacus) with analyses of the genomes of 215 placental mammals. First, we identified a set of proteins evolving more slowly in vocal learners. Then, we discovered a vocal motor cortical region in the Egyptian fruit bat, an emergent vocal learner, and leveraged that knowledge to identify active cis-regulatory elements in the motor cortex of vocal learners. Machine learning methods applied to motor cortex open chromatin revealed 50 enhancers robustly associated with vocal learning whose activity tended to be lower in vocal learners. Our research implicates convergent losses of motor cortex regulatory elements in mammalian vocal learning evolution.

Memory B cell subsets have divergent developmental origins that are coupled to distinct imprinted epigenetic states

Memory B cells (MBCs) are phenotypically and functionally diverse, but their developmental origins remain undefined. Murine MBCs can be divided into subsets by expression of CD80 and PD-L2. Upon re-immunization, CD80/PD-L2 double-negative (DN) MBCs spawn germinal center B cells (GCBCs), whereas CD80/PD-L2 double-positive (DP) MBCs generate plasmablasts but not GCBCs. Using multiple approaches, including generation of an inducible GCBC-lineage reporter mouse, we demonstrate in a T cell-dependent response that DN cells formed independently of the germinal center (GC), whereas DP cells exhibited either extrafollicular (DPEX) or GCBC (DPGC) origins. Chromatin and transcriptional profiling revealed similarity of DN cells with an early memory precursor. Reciprocally, GCBC-derived DP cells shared distinct genomic features with GCBCs, while DPEX cells had hybrid features. Upon restimulation, DPEX cells were more prone to divide, while DPGC cells differentiated toward IgG1+ plasmablasts. Thus, MBC functional diversity is generated through distinct developmental histories, which imprint characteristic epigenetic patterns onto their progeny, thereby programming them for divergent functional responses.

Evolutionary rate covariation is a reliable predictor of co-functional interactions but not necessarily physical interactions

Co-functional proteins tend to have rates of evolution that covary over time. This correlation between evolutionary rates can be measured over the branches of a phylogenetic tree through methods such as evolutionary rate covariation (ERC), and then used to construct gene networks by the identification of proteins with functional interactions. The cause of this correlation has been hypothesized to result from both compensatory coevolution at physical interfaces and nonphysical forces such as shared changes in selective pressure. This study explores whether coevolution due to compensatory mutations has a measurable effect on the ERC signal. We examined the difference in ERC signal between physically interacting protein domains within complexes compared to domains of the same proteins that do not physically interact. We found no generalizable relationship between physical interaction and high ERC, although a few complexes ranked physical interactions higher than nonphysical interactions. Therefore, we conclude that coevolution due to physical interaction is weak, but present in the signal captured by ERC, and we hypothesize that the stronger signal instead comes from selective pressures on the protein as a whole and maintenance of the general function.

Optimizer's dilemma: optimization strongly influences model selection in transcriptomic prediction

Motivation

Most models can be fit to data using various optimization approaches. While model choice is frequently reported in machine-learning-based research, optimizers are not often noted. We applied two different implementations of LASSO logistic regression implemented in Python's scikit-learn package, using two different optimization approaches (coordinate descent, implemented in the liblinear library, and stochastic gradient descent, or SGD), to predict mutation status and gene essentiality from gene expression across a variety of pan-cancer driver genes. For varying levels of regularization, we compared performance and model sparsity between optimizers.

Results

After model selection and tuning, we found that liblinear and SGD tended to perform comparably. liblinear models required more extensive tuning of regularization strength, performing best for high model sparsities (more nonzero coefficients), but did not require selection of a learning rate parameter. SGD models required tuning of the learning rate to perform well, but generally performed more robustly across different model sparsities as regularization strength decreased. Given these tradeoffs, we believe that the choice of optimizers should be clearly reported as a part of the model selection and validation process, to allow readers and reviewers to better understand the context in which results have been generated.

Availability and implementation

The code used to carry out the analyses in this study is available at https://github.com/greenelab/pancancer-evaluation/tree/master/01_stratified_classification. Performance/regularization strength curves for all genes in the Vogelstein et al. (2013) dataset are available at https://doi.org/10.6084/m9.figshare.22728644.

RERconverge Expansion: Using Relative Evolutionary Rates to Study Complex Categorical Trait Evolution

Comparative genomics approaches seek to associate evolutionary genetic changes with the evolution of phenotypes across a phylogeny. Many of these methods, including our evolutionary rates based method, RERconverge, lack the capability of analyzing non-ordinal, multicategorical traits. To address this limitation, we introduce an expansion to RERconverge that associates shifts in evolutionary rates with the convergent evolution of multi-categorical traits. The categorical RERconverge expansion includes methods for performing categorical ancestral state reconstruction, statistical tests for associating relative evolutionary rates with categorical variables, and a new method for performing phylogenetic permulations on multi-categorical traits. In addition to demonstrating our new method on a three-category diet phenotype, we compare its performance to naive pairwise binary RERconverge analyses and two existing methods for comparative genomic analyses of categorical traits: phylogenetic simulations and a phylogenetic signal based method. We also present a diagnostic analysis of the new permulations approach demonstrating how the method scales with the number of species and the number of categories included in the analysis. Our results show that our new categorical method outperforms phylogenetic simulations at identifying genes and enriched pathways significantly associated with the diet phenotype and that the new ancestral reconstruction drives an improvement in our ability to capture diet-related enriched pathways. Our categorical permulations were able to account for non-uniform null distributions and correct for non-independence in gene rank during pathway enrichment analysis. The categorical expansion to RERconverge will provide a strong foundation for applying the comparative method to categorical traits on larger data sets with more species and more complex trait evolution.

Benchmarking of deep neural networks for predicting personal gene expression from DNA sequence highlights shortcomings

Deep learning methods have recently become the state of the art in a variety of regulatory genomic tasks1-6, including the prediction of gene expression from genomic DNA. As such, these methods promise to serve as important tools in interpreting the full spectrum of genetic variation observed in personal genomes. Previous evaluation strategies have assessed their predictions of gene expression across genomic regions; however, systematic benchmarking is lacking to assess their predictions across individuals, which would directly evaluate their utility as personal DNA interpreters. We used paired whole genome sequencing and gene expression from 839 individuals in the ROSMAP study7 to evaluate the ability of current methods to predict gene expression variation across individuals at varied loci. Our approach identifies a limitation of current methods to correctly predict the direction of variant effects. We show that this limitation stems from insufficiently learned sequence motif grammar and suggest new model training strategies to improve performance.

Benchmarking of deep neural networks for predicting personal gene expression from DNA sequence highlights shortcomings

Deep learning methods have recently become the state-of-the-art in a variety of regulatory genomic tasks1-6 including the prediction of gene expression from genomic DNA. As such, these methods promise to serve as important tools in interpreting the full spectrum of genetic variation observed in personal genomes. Previous evaluation strategies have assessed their predictions of gene expression across genomic regions, however, systematic benchmarking is lacking to assess their predictions across individuals, which would directly evaluates their utility as personal DNA interpreters. We used paired Whole Genome Sequencing and gene expression from 839 individuals in the ROSMAP study7 to evaluate the ability of current methods to predict gene expression variation across individuals at varied loci. Our approach identifies a limitation of current methods to correctly predict the direction of variant effects. We show that this limitation stems from insufficiently learnt sequence motif grammar, and suggest new model training strategies to improve performance.

MousiPLIER: A Mouse Pathway-Level Information Extractor Model

High throughput gene expression profiling is a powerful approach to generate hypotheses on the underlying causes of biological function and disease. Yet this approach is limited by its ability to infer underlying biological pathways and burden of testing tens of thousands of individual genes. Machine learning models that incorporate prior biological knowledge are necessary to extract meaningful pathways and generate rational hypothesis from the vast amount of gene expression data generated to date. We adopted an unsupervised machine learning method, Pathway-level information extractor (PLIER), to train the first mouse PLIER model on 190,111 mouse brain RNA-sequencing samples, the greatest amount of training data ever used by PLIER. mousiPLER converted gene expression data into a latent variables that align to known pathway or cell maker gene sets, substantially reducing data dimensionality and improving interpretability. To determine the utility of mousiPLIER, we applied it to a mouse brain aging study of microglia and astrocyte transcriptomic profiling. We found a specific set of latent variables that are significantly associated with aging, including one latent variable (LV41) corresponding to striatal signal. We next performed k-means clustering on the training data to identify studies that respond strongly to LV41, finding that the variable is relevant to striatum and aging across the scientific literature. Finally, we built a web server (http://mousiplier.greenelab.com/) for users to easily explore the learned latent variables. Taken together this study provides proof of concept that mousiPLIER can uncover meaningful biological processes in mouse transcriptomic studies.

An intrinsically interpretable neural network architecture for sequence-to-function learning

MOTIVATION

Sequence-based deep learning approaches have been shown to predict a multitude of functional genomic readouts, including regions of open chromatin and RNA expression of genes. However, a major limitation of current methods is that model interpretation relies on computationally demanding post hoc analyses, and even then, one can often not explain the internal mechanics of highly parameterized models. Here, we introduce a deep learning architecture called totally interpretable sequence-to-function model (tiSFM). tiSFM improves upon the performance of standard multilayer convolutional models while using fewer parameters. Additionally, while tiSFM is itself technically a multilayer neural network, internal model parameters are intrinsically interpretable in terms of relevant sequence motifs.

RESULTS

We analyze published open chromatin measurements across hematopoietic lineage cell-types and demonstrate that tiSFM outperforms a state-of-the-art convolutional neural network model custom-tailored to this dataset. We also show that it correctly identifies context-specific activities of transcription factors with known roles in hematopoietic differentiation, including Pax5 and Ebf1 for B-cells, and Rorc for innate lymphoid cells. tiSFM's model parameters have biologically meaningful interpretations, and we show the utility of our approach on a complex task of predicting the change in epigenetic state as a function of developmental transition.

AVAILABILITY AND IMPLEMENTATION

The source code, including scripts for the analysis of key findings, can be found at https://github.com/boooooogey/ATAConv, implemented in Python.

A methylation clock model of mild SARS-CoV-2 infection provides insight into immune dysregulation

DNA methylation comprises a cumulative record of lifetime exposures superimposed on genetically determined markers. Little is known about methylation dynamics in humans following an acute perturbation, such as infection. We characterized the temporal trajectory of blood epigenetic remodeling in 133 participants in a prospective study of young adults before, during, and after asymptomatic and mildly symptomatic SARS-CoV-2 infection. The differential methylation caused by asymptomatic or mildly symptomatic infections was indistinguishable. While differential gene expression largely returned to baseline levels after the virus became undetectable, some differentially methylated sites persisted for months of follow-up, with a pattern resembling autoimmune or inflammatory disease. We leveraged these responses to construct methylation-based machine learning models that distinguished samples from pre-, during-, and postinfection time periods, and quantitatively predicted the time since infection. The clinical trajectory in the young adults and in a diverse cohort with more severe outcomes was predicted by the similarity of methylation before or early after SARS-CoV-2 infection to the model-defined postinfection state. Unlike the phenomenon of trained immunity, the postacute SARS-CoV-2 epigenetic landscape we identify is antiprotective.

IL-21R signal reprogramming cooperates with CD40 and BCR signals to select and differentiate germinal center B cells

Both B cell receptor (BCR) and CD40 signaling are rewired in germinal center (GC) B cells (GCBCs) to synergistically induce c-MYC and phosphorylated S6 ribosomal protein (p-S6), markers of positive selection. How interleukin-21 (IL-21), a key T follicular helper (TFH)-derived cytokine, affects GCBCs is unclear. Like BCR and CD40 signals, IL-21 receptor (IL-21R) plus CD40 signals also synergize to induce c-MYC and p-S6 in GCBCs. However, IL-21R plus CD40 stimulation differentially affects GCBC fate compared with BCR plus CD40 ligation-engaging unique molecular mechanisms-as revealed by bulk RNA sequencing (RNA-seq), single-cell RNA-seq, and flow cytometry of GCBCs in vitro and in vivo. Whereas both signal pairs induced BLIMP1 in some GCBCs, only the IL-21R/CD40 combination induced IRF4hi/CD138+ cells, indicative of plasma cell differentiation, along with CCR6+/CD38+ memory B cell precursors. These findings reveal a second positive selection pathway in GCBCs, document rewired IL-21R signaling in GCBCs, and link specific TFH- and Ag-derived signals to GCBC differentiation.

An intrinsically interpretable neural network architecture for sequence to function learning

Motivation

Sequence-based deep learning approaches have been shown to predict a multitude of functional genomic readouts, including regions of open chromatin and RNA expression of genes. However, a major limitation of current methods is that model interpretation relies on computationally demanding post-hoc analyses, and even then, we often cannot explain the internal mechanics of highly parameterized models. Here, we introduce a deep learning architecture called tiSFM (totally interpretable sequence to function model). tiSFM improves upon the performance of standard multi-layer convolutional models while using fewer parameters. Additionally, while tiSFM is itself technically a multi-layer neural network, internal model parameters are intrinsically interpretable in terms of relevant sequence motifs.

Results

tiSFM's model architecture makes use of convolutions with a fixed set of kernel weights representing known transcription factor (TF) binding site motifs. We analyze published open chromatin measurements across hematopoietic lineage cell-types and demonstrate that tiSFM outperforms a state- of-the-art convolutional neural network model custom-tailored to this dataset. We also show that it correctly identifies context specific activities of transcription factors with known roles in hematopoietic differentiation, including Pax5 and Ebf1 for B-cells, and Rorc for innate lymphoid cells. tiSFM's model parameters have biologically meaningful interpretations, and we show the utility of our approach on a complex task of predicting the change in epigenetic state as a function of developmental transition.

Availability and implementation

The source code, including scripts for the analysis of key findings, can be found at https://github.com/boooooogey/ATAConv , implemented in Python.

Contact

atb44@pitt.edu.

Pre-infection antiviral innate immunity contributes to sex differences in SARS-CoV-2 infection

Male sex is a major risk factor for SARS-CoV-2 infection severity. To understand the basis for this sex difference, we studied SARS-CoV-2 infection in a young adult cohort of United States Marine recruits. Among 2,641 male and 244 female unvaccinated and seronegative recruits studied longitudinally, SARS-CoV-2 infections occurred in 1,033 males and 137 females. We identified sex differences in symptoms, viral load, blood transcriptome, RNA splicing, and proteomic signatures. Females had higher pre-infection expression of antiviral interferon-stimulated gene (ISG) programs. Causal mediation analysis implicated ISG differences in number of symptoms, levels of ISGs, and differential splicing of CD45 lymphocyte phosphatase during infection. Our results indicate that the antiviral innate immunity set point causally contributes to sex differences in response to SARS-CoV-2 infection. A record of this paper's transparent peer review process is included in the supplemental information.

Re-analysis on the statistical sampling biases of a mask promotion trial in Bangladesh: a statistical replication

A recent randomized trial evaluated the impact of mask promotion on COVID-19-related outcomes. We find that staff behavior in both unblinded and supposedly blinded steps caused large and statistically significant imbalances in population sizes. These denominator differences constitute the rate differences observed in the trial, complicating inferences of causality.

Widespread redundancy in -omics profiles of cancer mutation states

BACKGROUND

In studies of cellular function in cancer, researchers are increasingly able to choose from many -omics assays as functional readouts. Choosing the correct readout for a given study can be difficult, and which layer of cellular function is most suitable to capture the relevant signal remains unclear.

RESULTS

We consider prediction of cancer mutation status (presence or absence) from functional -omics data as a representative problem that presents an opportunity to quantify and compare the ability of different -omics readouts to capture signals of dysregulation in cancer. From the TCGA Pan-Cancer Atlas that contains genetic alteration data, we focus on RNA sequencing, DNA methylation arrays, reverse phase protein arrays (RPPA), microRNA, and somatic mutational signatures as -omics readouts. Across a collection of genes recurrently mutated in cancer, RNA sequencing tends to be the most effective predictor of mutation state. We find that one or more other data types for many of the genes are approximately equally effective predictors. Performance is more variable between mutations than that between data types for the same mutation, and there is little difference between the top data types. We also find that combining data types into a single multi-omics model provides little or no improvement in predictive ability over the best individual data type.

CONCLUSIONS

Based on our results, for the design of studies focused on the functional outcomes of cancer mutations, there are often multiple -omics types that can serve as effective readouts, although gene expression seems to be a reasonable default option.

A Quantitative Systems Pharmacology Platform Reveals NAFLD Pathophysiological States and Targeting Strategies

Non-alcoholic fatty liver disease (NAFLD) has a high global prevalence with a heterogeneous and complex pathophysiology that presents barriers to traditional targeted therapeutic approaches. We describe an integrated quantitative systems pharmacology (QSP) platform that comprehensively and unbiasedly defines disease states, in contrast to just individual genes or pathways, that promote NAFLD progression. The QSP platform can be used to predict drugs that normalize these disease states and experimentally test predictions in a human liver acinus microphysiology system (LAMPS) that recapitulates key aspects of NAFLD. Analysis of a 182 patient-derived hepatic RNA-sequencing dataset generated 12 gene signatures mirroring these states. Screening against the LINCS L1000 database led to the identification of drugs predicted to revert these signatures and corresponding disease states. A proof-of-concept study in LAMPS demonstrated mitigation of steatosis, inflammation, and fibrosis, especially with drug combinations. Mechanistically, several structurally diverse drugs were predicted to interact with a subnetwork of nuclear receptors, including pregnane X receptor (PXR; NR1I2), that has evolved to respond to both xenobiotic and endogenous ligands and is intrinsic to NAFLD-associated transcription dysregulation. In conjunction with iPSC-derived cells, this platform has the potential for developing personalized NAFLD therapeutic strategies, informing disease mechanisms, and defining optimal cohorts of patients for clinical trials.

IMMU-06. Landscape of adaptive immunity of childhood brain cancers

T lymphocytes have a unique ability to recognize a vast array of antigens prompted by an enormous T cell receptor (TCR) repertoire. Characterization of tumor-infiltrating T cells (TILs) is key to understand MHC-restricted anti-tumor immunity and for developing T cell-centered immunotherapies such as adoptive cell therapy and tumor vaccines. In the current work, we investigated RNA-Seq data from 997 pediatric brain tumor patients and performed a large-scale comprehensive examination of the immunogenomic and TCR landscape of TILs across the entire spectrum of pediatric brain tumors. We show that the relative ratio between T cell diversity (clonality) and T cell abundance within each sample, represented by the clonal expansion index (CEI), is a strong predictor of prognosis both within and between tumor types. Interestingly, we show that CEI was strongly associated with molecular subgroups of medulloblastoma but not with known tumor-genomic features of these subgroups. Investigation of TCR clones recognizing a common recurrent tumor-antigen across patients based on CDR3 homology and characteristics, reveals 9 TCR clusters which are tumor type restricted with defined prognoses and HLA dominance. Using computational immunogenomics and machine learning-based investigations of these clusters yielded novel putative HLA-restricted tumor antigens which could bind and activate the clusters’ specific TCRs. Importantly, our framework grounded the foundations for developing a precision medicine approach of T cell-centered immunotherapies. These findings have major implications for understanding the interplay between T cell and tumor genomic, and for developing new immunotherapies for children with brain tumors.

AB1040 ASSOCIATION OF Q141K POLYMORPHISM OF ABCG2 GENE WITH THE EFFECTIVENESS OF URATE-LOWERING THERAPY IN PATIENTS WITH GOUT (PILOT STUDY)

Background

The effectiveness of allopurinol in pts with gout depends on genetic factors (GF) [1]. How GF works on probability of the target serum uric acid (sUA) level achievement is not studied.

Objectives

To study the opportunity of the target sUA level achievement in pts with gout while taking allopurinol or febuxostat, depending on the polymorphism (rs2231142) of the ABCG2 gene.

Methods

The study included 82 pts with gout aged ≥18 yrs who did not take urate-lowering drugs (ULD) and had sUA level >360 µmol/l. Initially all patients were prescribed allopurinol 100 mg/day, than the dose was up-titrared to achieve the target sUA level (<360 µmol/l or <300 µmol/l in pts with chronic tophaceous gout). Maximum dosage was 900 mg/day; in pts with glomerular filtration rate (GFR) <60 ml/min/1.73 m2 - 300 mg/day. Pts who did not achieve the target sUA level while using allopurinol were prescribed febuxostat 80 mg/day, which, if necessary, was increased to 120 mg/day. Each patient was followed up until the target sUA level was achieved.

All pts underwent genotyping of the С>А (rs2231142) polymorphism of the ABCG2 gene. During the study we compared: the probability of achieving the target sUA level, the average values of the sUA level decline, the average doses of ULD in pts with different genotypes (CC, CA, AA) of the ABCG2 gene. Statistical analysis was carried out using the Statistica 12.0 software package, and descriptive statistics methods.

Results

The target sUA level was defined as <300 µmol/l in 45 (55%) of 82 pts, as <360 µmol/l in 37 (45%) pts. In 26 pts, the dose of allopurinol did not exceed 300 mg/day. In 28 (34%) pts on allopurinol therapy, the target level of sUA was achived. In 54 (66%) pts allopurinol was replaced with febuxostat, while in 22 (41%) of them, the level of sUA decreased and was below the target.

The CC genotype of the ABCG2 gene was found in 51 (62%) pts, the CA genotype in 30 (37%) pts, and the minor AA genotype in 1 (1%) pt. The opportunity of the target sUA level achievement during the allopurinol therapy in carriers of the homozygous CC genotype and CA or AA genotypes did not differ: 17 (33%) and 11 (35%) cases, respectively. It turned out that CA and AA pts required a significantly higher dose of allopurinol (365±102 mg/day) than CC pts (290±85 mg/day), p=0.002. Of 54 pts treated with febuxostat who did not achieve the target sUA level, 30 (56%) pts had the CC genotype and 24 (44%) pts had the CA genotype. The opportunity of the target sUA level achievement was comparable (p=0.22).

Conclusion

The opportunity of achieving the target sUA level in pts with gout taking allopurinol is not associated with the C>A polymorphism of the ABCG2 gene, but the presence of the CA and AA genotypes is associated with the need to prescribe large doses of allopurinol.

References

[1]Wen CC, Yee SW, Liang X et al. Genome-wide association study identifies ABCG2 (BCRP) as an allopurinol transporter and a determinant of drug response. Clin Pharmacol Ther. 2015 May;97(5):518-25. doi: 10.1002/cpt.89

Disclosure of Interests

Maxim Eliseev Speakers bureau: Berlin Chemie Menarini Group, Sobi, EGIS, CSC, MosFarma, Alium Group, Maria Chikina: None declared, Olga Sheliabina Speakers bureau: Berlin Chemie Menarini Group, Elena Cheremushkina: None declared

AB1045 QUALITY OF LIFE IN PATIENTS WITH GOUT TAKING URATE-LOWERING DRUGS, DEPENDING ON THE ACHIEVEMENT OF THE TARGET LEVEL OF SERUM URIC ACID

Background

Intake of urate-lowering drugs (ULD) leads to an improvement in the quality of life (QoL) in pts with gout. However, it is not clear to what extend the QoL is changed in pts who did not achieve the target level of serum uric acid (sUA).

Objectives

to evaluate the dynamics of the QoL in pts, taking ULD, who have achieved and have not achieved the target sUA level.

Methods

98 pts with gout were included in the prospective study. The follow-up period was 24 months, allopurinol or febuxostat at doses sufficient to achieve the target sUA level (<360 µmol/l) were used. The maximum daily dose of allopurinol was 900 mg/day, febuxostat - 120 mg/day. Pts who did not achieve the target sUA level continued taking ULD at the maximum dosages. The values of the Qol in dynamics were calculated using the SF-36v2 questionnaire. The assessment of the QoL was carried out separately in pts who achieved and did not achieve the target level of sUA. The frequency of exacerbations of arthritis was also assessed. Statistica 12.0 package was used for statistical data processing.

Results

69 of 98 (70%) pts achieved the target sUA level, wherein allopurinol was taken by 46 pts, febuxostat – 34 pts. Pts who achieved the target level of sUA after 6 mo. of ULD usage, demonstrated a significant improvement in the physical health (PH), including physical functioning (PF), role limitations due to physical functioning (RP), general health (GH), as well as vitality (VT) (p<0.05 for all). After 12 and 24 mo. improvement was achieved in RH, GH and PF (p<0.01), RP, bodily pain intensity (BP) and VT (p<0.05). General mental health (MH), role-emotional functioning (RE) and social functioning (SF) were unchanged throughout the study. Pts who did not achieve the target sUA level after 6 and 12 mo. significantly improved: PF, RP (p<0.05 for all). After 24 months, for all QoL parameters, the values did not differ from the initial ones. The frequency of arthritis exacerbation in pts who achieved the target sUA level decreased from 3.1±1.6 cases per year to 0.9±1.1 cases per year (p=0.0013); in those who did not achieve - from 3.1±1.9 cases per year to 2.4±1.6 cases per year (p=0.047).

Conclusion

: The QoL in gout pts who achieved target sUA level continues to improve during the first year of ULD intake. Even if the target sUA level is not achieved, the QoL of patients with gout treated with ULD remains stable for at least 2 years of therapy. This predetermines the need to use maximum daily doses of ULD, even if the target serum UA level is not achieved.

Disclosure of Interests

Maria Chikina: None declared, Olga Sheliabina Speakers bureau: Berlin Chemie Menarini Group, Maxim Eliseev Speakers bureau: Berlin Chemie Menarini Group, Sobi, EGIS, CSC, MosFarma, Alium Group

AB1046 EFFICACY OF FEBUXOSTAT IN PATIENTS WITH GOUT STRATIFIED BY BASELINE RENAL FUNCTION

Background

The opportunity of achievement of the target serum UA (sUA) level in pts with gout, stratified by renal function, is not studied.

Objectives

To compare the probability of the sUA level achievement during therapy with febuxostat in patients with gout, stratified according to renal function.

Methods

The prospective study included 136 pts aged ≥18 years with a crystal-verified diagnosis of gout and sUA level >360 µmol/L who had never taken febuxostat or other urate-lowering drugs (at least 2 weeks before the start of the study). All pts were prescribed febuxostat 80 mg/day; if the target sUA level (<360 µmol/l) was not achieved, the dose was increased to 120 mg/day. Prophylactic anti-inflammatory drugs (AIDs) were taken: colchicine in 59 (43.4%) pts, NSAIDs - 51 (37.58%) pts, GC - 12 (98.8%) pts. 14 (10.3%) pts did not take AIDs. Laboratory tests (serum levels of glucose, creatinine, UA) before and after 26 weeks of therapy were collected. GFR was calculated using CKD-EPI formula before and after therapy. The pts were initially divided into groups depending on the CKD stages according to the level of GFR (CKD-EPI): C1 – normal or high renal function (>90 ml/min/1.73 m2), C2 – mildly decreased (60-89 ml/min/1.73 m2), C3 - moderately decreased (30-59 ml/min/1.73 m2), C4 – severely decreased (15-29 ml/min/1.73 m2). The observation period covered at least 26 weeks, the primary end point was the achievement of the target sUA level. The dynamics of GFR was also assessed. Statistica 12.0 package was used for statistical data processing.

Results

It was found that 30 (22.12%) pts had CKD stage 0-1, 28 (66-20.6%) pts - C2, 62 (45.6%) pts – C3, 16 (11.8%) – C4. 98 (72.1%) pts received febuxostat 80 mg/day, 38 (27.9%) pts - 120 mg/day. Pts with CKD C4 were older than ones with CKD C2 (p=0.00001) and CKD C0-1 (p=0.002); had a longer duration of gout (p=0.003); they were more likely to have subcutaneous tophi than pts with CKD C2 (p=0.007). The frequency of diagnosing DM, hypertension, as well as the sUA level in the groups did not differ. The levels of sUA, GFR in patients with gout, stratified by the level of GFR at baseline and after 26 weeks of febuxostat therapy, are given below (Table 1).

Table 1.

Levels of UA, eGFR in patients with gout, stratified by the level of eGFR at baseline and after 26 weeks of febuxostat therapy.

ParametersAll patients, n=136CKD С0-1, n=30CKD С2, n=28CKD С3, n=62CKD С4, n=16UA baseline, µmol/l472,4±99,3451,9±102,8486,9±103,8476,9±86,7468,3±109,8UA after 26 weeks, µmol/l306,27±104,4298,6±104,8*282,2±95,8*318,9±97,6*313,5±106,9*Δ UA, µmol/l166±10,2153,3±10,7204,7±12,4157,9±17,8154,8±14,9UA<360 µmol/l, n (%)117 (84)25 (83)25 (89)51 (82)13 (81)GFR baseline, ml/min/1.73 m263,98±15,3101,3±18,175,9±9,750,2±5,526,5±2,6GFR after 26 weeks, ml/min/1.73 m264,74±26,9102,8±28,6*76,7±9,350,9±6,927,3±4,9

* - p<0.05 between baseline and 26 weeks

The target sUA level was achieved in 33 (87%) patients with DM (the probability did not depend on the initial GFR value). Achievement of target sUA level was registered in 84% of general sample: in 83% of pts with CKD C0-1, 89% - CKD C2, 82% - CKD C3, 81% of pts with CKD C4. Mean GFR values increased in all groups, but significant differences registered in patients with CKD C0-1 (p=0.002) only.

Conclusion

The ability to achieve the target sUA level while taking febuxostat in patients with gout does not depend on renal function, exceeding 80% in patients with CKD C4. The drug is well tolerated regardless of renal function.

Disclosure of Interests

Maxim Eliseev Speakers bureau: Berlin Chemie Menarini Group, Sobi, EGIS, CSC, MosFarma, Alium Group, Olga Sheliabina Speakers bureau: Berlin Chemie Menarini Group, Maria Chikina: None declared

Non-negative Independent Factor Analysis disentangles discrete and continuous sources of variation in scRNA-seq data

MOTIVATION

Single-cell RNA-seq analysis has emerged as a powerful tool for understanding inter-cellular heterogeneity. Due to the inherent noise of the data, computational techniques often rely on dimensionality reduction (DR) as both a pre-processing step and an analysis tool. Ideally, DR should preserve the biological information while discarding the noise. However, if the DR is to be used directly to gain biological insight it must also be interpretable-that is the individual dimensions of the reduction should correspond to specific biological variables such as cell-type identity or pathway activity. Maximizing biological interpretability necessitates making assumption about the data structures and the choice of the model is critical.

RESULTS

We present a new probabilistic single-cell factor analysis model, Non-negative Independent Factor Analysis (NIFA), that incorporates different interpretability inducing assumptions into a single modeling framework. The key advantage of our NIFA model is that it simultaneously models uni- and multi-modal latent factors, and thus isolates discrete cell-type identity and continuous pathway activity into separate components. We apply our approach to a range of datasets where cell-type identity is known, and we show that NIFA-derived factors outperform results from ICA, PCA, NMF and scCoGAPS (an NMF method designed for single-cell data) in terms of disentangling biological sources of variation. Studying an immunotherapy dataset in detail, we show that NIFA is able to reproduce and refine previous findings in a single analysis framework and enables the discovery of new clinically relevant cell states.

AVAILABILITY AND IMPLEMENTATION

NFIA is a R package which is freely available at GitHub (https://github.com/wgmao/NIFA). The test dataset is archived at https://zenodo.org/record/6286646.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Individual variation in susceptibility or exposure to SARS-CoV-2 lowers the herd immunity threshold

Individual variation in susceptibility and exposure is subject to selection by natural infection, accelerating the acquisition of immunity, and reducing herd immunity thresholds and epidemic final sizes. This is a manifestation of a wider population phenomenon known as "frailty variation". Despite theoretical understanding, public health policies continue to be guided by mathematical models that leave out considerable variation and as a result inflate projected disease burdens and overestimate the impact of interventions. Here we focus on trajectories of the coronavirus disease (COVID-19) pandemic in England and Scotland until November 2021. We fit models to series of daily deaths and infer relevant epidemiological parameters, including coefficients of variation and effects of non-pharmaceutical interventions which we find in agreement with independent empirical estimates based on contact surveys. Our estimates are robust to whether the analysed data series encompass one or two pandemic waves and enable projections compatible with subsequent dynamics. We conclude that vaccination programmes may have contributed modestly to the acquisition of herd immunity in populations with high levels of pre-existing naturally acquired immunity, while being crucial to protect vulnerable individuals from severe outcomes as the virus becomes endemic.

Heterogeneity and clonality of kidney-infiltrating T cells in murine lupus nephritis

We previously found that kidney-infiltrating T cells (KITs) in murine lupus nephritis (LN) resembled dysfunctional T cells that infiltrate tumors. This unexpected finding raised the question of how to reconcile the "exhausted" phenotype of KITs with ongoing tissue destruction in LN. To address this, we performed single-cell RNA-Seq and TCR-Seq of KITs in murine lupus models. We found that CD8+ KITs existed first in a transitional state, before clonally expanding and evolving toward exhaustion. On the other hand, CD4+ KITs did not fit into current differentiation paradigms but included both hypoxic and cytotoxic subsets with a pervasive exhaustion signature. Thus, autoimmune nephritis is unlike acute pathogen immunity; rather, the kidney microenvironment suppresses T cells by progressively inducing exhausted states. Our findings suggest that LN, a chronic condition, results from slow evolution of damage caused by dysfunctional T cells and their precursors on the way to exhaustion. These findings have implications for both autoimmunity and tumor immunology.

Individual variation in susceptibility or exposure to SARS-CoV-2 lowers the herd immunity threshold

Individual variation in susceptibility and exposure is subject to selection by natural infection, accelerating the acquisition of immunity, and reducing herd immunity thresholds and epidemic final sizes. This is a manifestation of a wider population phenomenon known as "frailty variation". Despite theoretical understanding, public health policies continue to be guided by mathematical models that leave out considerable variation and as a result inflate projected disease burdens and overestimate the impact of interventions. Here we focus on trajectories of the coronavirus disease (COVID-19) pandemic in England and Scotland until November 2021. We fit models to series of daily deaths and infer relevant epidemiological parameters, including coefficients of variation and effects of non-pharmaceutical interventions which we find in agreement with independent empirical estimates based on contact surveys. Our estimates are robust to whether the analysed data series encompass one or two pandemic waves and enable projections compatible with subsequent dynamics. We conclude that vaccination programmes may have contributed modestly to the acquisition of herd immunity in populations with high levels of pre-existing naturally acquired immunity, while being critical to protect vulnerable individuals from severe outcomes as the virus becomes endemic.

Surface phenotypes of naive and memory B cells in mouse and human tissues

Memory B cells (MBCs) protect the body from recurring infections. MBCs differ from their naive counterparts (NBCs) in many ways, but functional and surface marker differences are poorly characterized. In addition, although mice are the prevalent model for human immunology, information is limited concerning the nature of homology in B cell compartments. To address this, we undertook an unbiased, large-scale screening of both human and mouse MBCs for their differential expression of surface markers. By correlating the expression of such markers with extensive panels of known markers in high-dimensional flow cytometry, we comprehensively identified numerous surface proteins that are differentially expressed between MBCs and NBCs. The combination of these markers allows for the identification of MBCs in humans and mice and provides insight into their functional differences. These results will greatly enhance understanding of humoral immunity and can be used to improve immune monitoring.

Complementary evolution of coding and noncoding sequence underlies mammalian hairlessness

Body hair is a defining mammalian characteristic, but several mammals, such as whales, naked mole-rats, and humans, have notably less hair. To find the genetic basis of reduced hair quantity, we used our evolutionary-rates-based method, RERconverge, to identify coding and noncoding sequences that evolve at significantly different rates in so-called hairless mammals compared to hairy mammals. Using RERconverge, we performed a genome-wide scan over 62 mammal species using 19,149 genes and 343,598 conserved noncoding regions. In addition to detecting known and potential novel hair-related genes, we also discovered hundreds of putative hair-related regulatory elements. Computational investigation revealed that genes and their associated noncoding regions show different evolutionary patterns and influence different aspects of hair growth and development. Many genes under accelerated evolution are associated with the structure of the hair shaft itself, while evolutionary rate shifts in noncoding regions also included the dermal papilla and matrix regions of the hair follicle that contribute to hair growth and cycling. Genes that were top ranked for coding sequence acceleration included known hair and skin genes KRT2, KRT35, PKP1, and PTPRM that surprisingly showed no signals of evolutionary rate shifts in nearby noncoding regions. Conversely, accelerated noncoding regions are most strongly enriched near regulatory hair-related genes and microRNAs, such as mir205, ELF3, and FOXC1, that themselves do not show rate shifts in their protein-coding sequences. Such dichotomy highlights the interplay between the evolution of protein sequence and regulatory sequence to contribute to the emergence of a convergent phenotype.

Evolutionary rate covariation identifies SLC30A9 (ZnT9) as a mitochondrial zinc transporter

Recent advances in genome sequencing have led to the identification of new ion and metabolite transporters, many of which have not been characterized. Due to the variety of subcellular localizations, cargo and transport mechanisms, such characterization is a daunting task, and predictive approaches focused on the functional context of transporters are very much needed. Here we present a case for identifying a transporter localization using evolutionary rate covariation (ERC), a computational approach based on pairwise correlations of amino acid sequence evolutionary rates across the mammalian phylogeny. As a case study, we find that poorly characterized transporter SLC30A9 (ZnT9) coevolves with several components of the mitochondrial oxidative phosphorylation chain, suggesting mitochondrial localization. We confirmed this computational finding experimentally using recombinant human SLC30A9. SLC30A9 loss caused zinc mishandling in the mitochondria, suggesting that under normal conditions it acts as a zinc exporter. We therefore propose that ERC can be used to predict the functional context of novel transporters and other poorly characterized proteins.

Antibody Responses to SARS-CoV-2 Following an Outbreak Among Marine Recruits With Asymptomatic or Mild Infection

We investigated serological responses following a SARS-CoV-2 outbreak in spring 2020 on a US Marine recruit training base. 147 participants that were isolated during an outbreak of respiratory illness were enrolled in this study, with visits approximately 6 and 10 weeks post-outbreak (PO). This cohort is comprised of young healthy adults, ages 18-26, with a high rate of asymptomatic infection or mild symptoms, and therefore differs from previously reported longitudinal studies on humoral responses to SARS-CoV-2, which often focus on more diverse age populations and worse clinical presentation. 80.9% (119/147) of the participants presented with circulating IgG antibodies against SARS-CoV-2 spike (S) receptor-binding domain (RBD) at 6 weeks PO, of whom 97.3% (111/114) remained positive, with significantly decreased levels, at 10 weeks PO. Neutralizing activity was detected in all sera from SARS-CoV-2 IgG positive participants tested (n=38) at 6 and 10 weeks PO, without significant loss between time points. IgG and IgA antibodies against SARS-CoV-2 RBD, S1, S2, and the nucleocapsid (N) protein, as well neutralization activity, were generally comparable between those participants that had asymptomatic infection or mild disease. A multiplex assay including S proteins from SARS-CoV-2 and related zoonotic and human endemic betacoronaviruses revealed a positive correlation for polyclonal cross-reactivity to S after SARS-CoV-2 infection. Overall, young adults that experienced asymptomatic or mild SARS-CoV-2 infection developed comparable humoral responses, with no decrease in neutralizing activity at least up to 10 weeks after infection.

DataRemix: a universal data transformation for optimal inference from gene expression datasets

MOTIVATION

RNA-seq technology provides unprecedented power in the assessment of the transcription abundance and can be used to perform a variety of downstream tasks such as inference of gene-correlation network and eQTL discovery. However, raw gene expression values have to be normalized for nuisance biological variation and technical covariates, and different normalization strategies can lead to dramatically different results in the downstream study.

RESULTS

We describe a generalization of singular value decomposition-based reconstruction for which the common techniques of whitening, rank-k approximation and removing the top k principal components are special cases. Our simple three-parameter transformation, DataRemix, can be tuned to reweigh the contribution of hidden factors and reveal otherwise hidden biological signals. In particular, we demonstrate that the method can effectively prioritize biological signals over noise without leveraging external dataset-specific knowledge, and can outperform normalization methods that make explicit use of known technical factors. We also show that DataRemix can be efficiently optimized via Thompson sampling approach, which makes it feasible for computationally expensive objectives such as eQTL analysis. Finally, we apply our method to the Religious Orders Study and Memory and Aging Project dataset, and we report what to our knowledge is the first replicable trans-eQTL effect in human brain.

AVAILABILITYAND IMPLEMENTATION

DataRemix is an R package which is freely available at GitHub (https://github.com/wgmao/DataRemix).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

POS1140 RISK FACTORS FOR THE DEVELOPMENT OF DIABETES MELLITUS IN PATIENTS WITH GOUT ACCORDING TO A 6-YEAR PROSPECTIVE FOLLOW-UP STUDY

Background:

Gout is often associated with diabetes mellitus (DM), but the role of serum uric acid (sUA) and urate-lowering drugs in its development in patients with gout remains controversial [1].

Objectives:

To study risk factors for DM in patients with gout based on the results of long-term prospective follow-up study.

Methods:

The prospective study included 444 patients with a crystal-verified diagnosis of gout, aged ≥18 years, 49 (11%) women, 395 (89%) men. Patients were followed up at the V.A. Nasonova Research Institute of Rheumatology from 2010 to January 2021, the median follow-up was 6.1 [2.8; 7.8] years. The exclusion criteria were the presence of other rheumatic diseases with symptoms of arthritis, DM. DM was diagnosed on the 1998 WHO criteria. The following parameters were considered as risk factors: gender, family history for diabetes mellitus, body mass index (BMI)>25 kg/m2 and > 30 kg/m2, waist volume ≥88 cm for women and ≥102 cm for men, alcohol consumption > 20 units per week, chronic kidney disease (CKD), intake of diuretics and glucocorticoids, and serum total cholesterol >5 mmol/l, triglycerides>2.25 mmol/l, serum C-reactive protein (CRP) level> 5 mg/l, as well as clinical manifestations of gout: subcutaneous tophi, polyarthritis (simultaneous involvement of ≥5 joints), intake of urate-lowering drugs, sUA (> 480 μmol/L,> 420 μmol/L,> 360 μmol/L,> 300 μmol/L). Statistica 12.0 package was used for statistical data processing.

Results:

A total of 444 patients were included, the mean age was 51.0±12.9 years, the median follow-up was 6.1 [2.8; 7.8] years. In dynamics: 35 (8%) patients died, 6 (1%) patients were not available, 403 patients were examined (44 (11%) - women and 359 (89%) - men). 290 (72%) patients received urate-lowering therapy (263 (65%) patients used allopurinol, 27 (7%) - febuxostat). The target sUA <360 μmol/L was reached by 165 (41%) patients and <300 μmol/L - by 92 (23%) patients. All patients with sUA<300 μmol/L received urate-lowering therapy, 62 (67%) patients used allopurinol, 17 (18%) - febuxostat, 13 (14%) - uricosuric drugs. Diabetes mellitus was developed in 106 (26%) patients. The factors influencing the risk of developing diabetes were - the presence of diabetes in family history (odds ratio (OR) 2.27, 95% confidence interval (CI) 1.37; 3.76); BMI> 30 kg / m2 (OR 1.79, 95% CI 1.14; 2.80), diuretics (OR 2.32, 95% CI 1.36; 3.96) and sUA> 300 μmol / l (OR 2.89, 95% CI 1.50, 5.56).

Conclusion:

The risk of developing DM in patients with gout is associated with sUA> 300 μmol/l, which may be one of the probable reasons for choosing this as a target level. Large prospective studies are needed to confirm the antidiabetic effect of urate-lowering drugs.

References:

[1]Chang HW, Lin YW, Lin MH, Lan YC, Wang RY. Associations between urate-lowering therapy and the risk of type 2 diabetes mellitus. PLoS One. 2019 Jan 7;14(1):e0210085. doi: 10.1371/journal.pone.0210085.

Disclosure of Interests:

Olga Sheliabina: None declared, Maxim Elisеev Speakers bureau: Berlin Chemie Menarini Group, Novartis International AG, EGIS, Aleksandra Novikova: None declared, Maria Chikina: None declared.

POS1363 CHONDROCALCINOSIS AS PREDICTOR OF DEVELOPMENT OF PRIMARY HYPERPARATHYROIDISM: RESULTS OF THE FOLLOW-UP OBSERVATION

Background:

The association between chondrocalcinosis and primary hyperparathyroidism (PHPT) is known, but chondrocalcinosis is considered as a late complication of PHPT.

Objectives:

To investigate whether calcium pyrophosphate crystal deposition is an early clinical sign of PHPT.

Methods:

The prospective study included 113 patients aged ≥18 years, 42 (37.2%) men and 71 (62.8%) women, with a crystal-verified diagnosis of calcium pyrophosphate crystal deposition disease (CPPD) (McCarty criteria). Exclusion criteria were the presence of other rheumatic diseases with symptoms of arthritis, the presence of hyperparathyroidism (HPT). Patients were examined at their enrollment and over time, the median follow-up was 3.86 [2.07; 8.36] years. The examination of the patients included assessment of anthropometric parameters, information about the affected joints and the time of onset of symptoms.

Laboratory tests included determination of the following in blood serum: creatinine (with estimating glomerular filtration rate (eGFR) according to the MDRD formula), total and ionized calcium (Ca and Ca++), phosphorus (P), parathyroid hormone (PTH), vitamin D (25-OH); ultrasound and X-ray investigations of the target joints (hands, knee joints) were made for all patients. Scintigraphy and ultrasound of the parathyroid glands were performed if medically required. Statistica 12.0 package was used for statistical data processing.

Results:

113 patients were examined, the average age was 58.4±12.4 years. 10 patients were excluded due to diagnosed HPT at screening. 41 patients dropped out of observation: 5 - died, 36 were not available for dynamic examination. 62 patients were examined in dynamics, 4 (6.5%) of those had HPT. In 1 (1.6%) case, HPT was associated with chronic renal failure, 3 (4.8) patients were diagnosed PHPT. The results of the examination of patients who developed PHPT during screening and in dynamics are presented in Table 1 above.

Table 1.

Results of patients with PHPT at screening and in dynamics.

Сrystals of calcium pyrophosphate in synovial fluidChondrocalcinosis by ultrasoundChondrocalcinosis by X-rayConvulsionsECG changes (shortening of the QT interval)Arthralgias / arthritisPTH, pg/ml (15,0-65,0)Ca, µmol/l (2.10-2.62)Са++, µmol/l (1.10-1.33)vitamin D (25-ОН), ng/ml (30-100)screening / dynamicsРatient А.yes/yesyes/yesnot/yesnot/notnot/notyes/yes61.6/96.22.73/2.671.37/1.24-/31Рatient В.yes/yesyes/yesyes/yesnot/yesnot/yesyes/yes40.7/2522.63/2.561.34/1.7719.1/14.2Рatient С.yes/yesyes/yesnot/yesnot/notnot/notyes/yes26.6/102.42.60/2.651.25/1.26-/40

In all three patients, chondrocalcinosis was revealed by ultrasound and Сrystals of calcium pyrophosphate in synovial fluid during the screening examination, in one patient chondrocalcinosis was revealed by X-ray. In two out of three cases, the level of serum Ca and Ca++ was minimally increased at a normal level of PTH, no other disorders of calcium metabolism were observed during the screening.

Interestingly, the first clinical manifestation of HPT in all patients was damage of the musculoskeletal system - mainly arthralgia, as well as arthritis of large and small joints. Moreover, all patients had a different CPPD phenotype: patient A - asymptomatic chondrocalcinosis, patient B - chronic arthritis (pseudo-rheumatoid form) and patient C - chronic arthritis (pseudosteoarthritis).

Conclusion:

The deposition of calcium pyrophosphate crystals may be an early predictor of the development of PHPT and precedes other manifestations.

Disclosure of Interests:

Aleksandra Novikova: None declared, Maxim Elisеev Speakers bureau: Berlin Chemie Menarini Group, Novartis International AG, EGIS, Olga Sheliabina: None declared, Maria Chikina: None declared

POS1139 COMPARISON OF THE FREQUENCY OF DETECTION OF EARLY SIGNS OF ATHEROSCLEROSIS IN PATIENTS WITH CALCIUM PYROPHOSPHATE CRYSTAL DEPOSITION DISEASE AND OSTEOARTHRITIS

Background:

Crystal-induced inflammation can significantly increase cardiovascular risk (CVR) and cause early development of atherosclerosis [1]. However, no studies have been performed in patients with calcium pyrophosphate crystal deposition disease (CPPD).

Objectives:

To compare the presence of atherosclerosis early signs (increased thickness of the intima-media complex (CIMT)) in patients with CPPD and osteoarthritis (OA).

Methods:

A cross-sectional study included 48 patients, aged 18 to 65 years, 26 patients with crystal-verified diagnosis of CPPD (McCarty criteria) (6 (23%) men and 20 (77%) women) and 22 patients with OA (7 (32%) men and 15 (68%) women). Exclusion criteria are the presence of other rheumatic diseases with symptoms of arthritis, diabetes mellitus, coronary heart disease (CHD), prior myocardial infarction, stroke or myocardial revascularization surgery, estimated glomerular filtration rate (eGFR) <60 ml/min/1.73 m2, high and very high CVR on the SCORE scale. The examination of the patients included the history taking, assessment of anthropometric parameters and the following laboratory tests: determination of serum creatinine level (eGFR according to the MDRD formula), total cholesterol (TC), high density lipoprotein cholesterol (HDL cholesterol) and low density lipoprotein cholesterol (LDL cholesterol), C-reactive protein (CRP). Doppler ultrasound of the carotid arteries with an assessment of the thickness of the intima media complex (CIMT) was made for all patients - CIMT up to 0.9 mm was taken as the norm, CIMT> 0.9 mm and <1.3 mm as increased, and CIMT>1.3 mm was regarded as an atherosclerotic plaque. Statistica 12.0 package was used for statistical data processing.

Results:

The groups were completely comparable by gender, age and all laboratory parameters (see Table 1), an increase in CRP>5 mg/l was more often detected in patients with CPPD - 31% vs 14% patients with OA (p=0.16).

Table 1.

Clinical characteristics of patients included in the study.

ParametersCPPD (n=26)OA(n=22)p value (reliable at р<0,05)Age, years M±SD55.9±5.952.4±8.30.14Gender, men/women,n (%)6 (23)/20 (77)7 (32)/15 (68)0.50Smoking, n (%)5(19)6(27)0.50Systolic blood pressure, mmHg, M±SD134±20127±150.19Arterial hypertension, n (%)13(50)10(45)0.75Family history of CVD, n %6(23)7(32)0.50TC, mmol/L, M±SD5.4±1.35.3±1.30.95TC >5,0 mmol/L, n (%)17(65)10(45)0.17HDL, mmol/L M±SD1.7±0.51.4±0.50.10LDL, mmol/L, M±SD2.9±1.33.4±1.40.33Creatinine, μmol/l, M±SD73.2±13.878.9±11.50.16CRP, mg/l, Me [25-75th percentiles]1.1 [0.6; 6.4]1.2 [0.3; 2.8]0.60CRP ≥5 mg/l,n (%)8 (31)3(14)0.16

Mean CIMT values on the right (0.76±0.22 mm vs 0.70±0.18 mm) and on the left (0.75±0.18 mm vs 0.70±0.17 mm) did not significantly differ in CPPD and OA (p=0.34 and 0.32, respectively), the maximum CIMT values on the right (0.67±0.16 mm vs 0.67±0.16 mm) and on the left (0.67±0.14 mm vs 0,66±0.16 mm) with CPPD and OA were also comparable (p=0.95 and 0.77, respectively). However, an increase in CIMT> 0.9 mm was found in 13 (50%) patients with CPPD and only 5 (23%) with OA (p=0.02). No increase in CIMT>1.3 mm was found in patients of both groups.

Conclusion:

Early signs of atherosclerosis are detected in 50% of patients with CPPD without clinical signs of atherosclerosis and with low or moderate CVR according to SCORE, significantly more often than in patients with OA (23%), which can be reflection of chronic crystal-induced inflammation.

References:

[1]Hoseini Z, Sepahvand F, Rashidi B, Sahebkar A, Masoudifar A, Mirzaei H. NLRP3 inflammasome: Its regulation and involvement in atherosclerosis. J Cell Physiol. 2018 Mar;233(3):2116-2132. doi: 10.1002/jcp.25930. Epub 2017 May 23. PMID: 28345767.

Disclosure of Interests:

Maxim Elisеev Speakers bureau: Berlin Chemie Menarini Group, Novartis International AG, EGIS, Aleksandra Novikova: None declared, Olga Sheliabina: None declared, Maria Chikina: None declared, Eugenia Markelova: None declared.

AB0640 MORTALITY IN CALCIUM PYROPHOSPHATE CRYSTAL DEPOSITION DISEASE: PRELIMINARY DATA

Background:

Calcium pyrophosphate crystal deposition disease (CPPD) is associated with a high frequency of comorbidities and vascular calcification [1], but it is unknown whether these factors affect cardiovascular mortality.

Objectives:

To study the structure of mortality in patients with CPPD and compare with the structure of mortality in the Russian Federation.

Methods:

217 patients with crystal-verified diagnosis of CPPD (McCarty criteria) were included in the prospective study, aged ≥18 years, mean age 59.2 ± 12.6 years, 82 (38%) men and 134 (62%) women. The median follow-up was 3.9 [1.9; 7.2] years, patients were followed up for at least a year. The exclusion criteria are the presence of other rheumatic diseases with arthritis symptoms. The examination of patients included the history taking, assessment of anthropometric parameters, the presence of comorbidity and the following laboratory tests: determination of serum creatinine level (with calculation of glomerular filtration rate (eGFR) using the MDRD formula), total cholesterol (TC), C-reactive protein (CRP). Statistica 12.0 package was used for statistical data processing.

Results:

A total of 217 patients were included. Arterial hypertension was detected in 115 (53%) patients, coronary heart disease in 51 (24%) patients, diabetes mellitus in 26 (12%) patients, chronic renal failure in 17 (8%) patients, hyperparathyroidism in 18 (8%) patients, chronic heart failure in 22 (10%) patients. 65 (30%) patients had a family history for CVD, 31 (14%) patients were smokers. 122 (56%) patients had an increased level of total cholesterol> 5.0 mmol/L and 54 (25%) patients – the level of CRP>5 mg/L.

23 (11%) patients, 12 (52%) men and 11 (48%) women, died, the average age of the deceased being 62.7±9.2 years. In 15 (65%) cases out of 23, death occurred due to cardiovascular complications, which is higher than the cardiovascular mortality rate in the Russian Federation (53%). Among CVD, the distribution was as follows: acute myocardial infarction - 6 (40%) patients,apoplectic attack - 5 (33) patients, thrombosis - 2 (13%) patients, rhythm disturbances – 1 (7%) patient and decompensation of chronic heart failure - 1 (7%) patient.

Conclusion:

CVD is the main cause of death in patients with CPPD and the total frequency of mortality from CVD exceeds the population one. Further research is needed, including studies of the risk factors for overall and cardiovascular mortality in patients with CPPD.

References:

[1]Abhishek A, Doherty S, Maciewicz R, et al. Association between low cortical bone mineral density, soft-tissue calcification, vascular calcification and chondrocalcinosis: a case-control study. Ann Rheum Dis. 2013;73(11):1997-2002. doi: 10.1136/annrheumdis2013-203400

Disclosure of Interests:

Maxim Elisеev Speakers bureau: Berlin Chemie Menarini Group, Novartis International AG, EGIS, Aleksandra Novikova: None declared., Olga Sheliabina: None declared., Maria Chikina: None declared.

Phylogenetic Permulations: A Statistically Rigorous Approach to Measure Confidence in Associations in a Phylogenetic Context

Many evolutionary comparative methods seek to identify associations between phenotypic traits or between traits and genotypes, often with the goal of inferring potential functional relationships between them. Comparative genomics methods aimed at this goal measure the association between evolutionary changes at the genetic level with traits evolving convergently across phylogenetic lineages. However, these methods have complex statistical behaviors that are influenced by nontrivial and oftentimes unknown confounding factors. Consequently, using standard statistical analyses in interpreting the outputs of these methods leads to potentially inaccurate conclusions. Here, we introduce phylogenetic permulations, a novel statistical strategy that combines phylogenetic simulations and permutations to calculate accurate, unbiased P values from phylogenetic methods. Permulations construct the null expectation for P values from a given phylogenetic method by empirically generating null phenotypes. Subsequently, empirical P values that capture the true statistical confidence given the correlation structure in the data are directly calculated based on the empirical null expectation. We examine the performance of permulation methods by analyzing both binary and continuous phenotypes, including marine, subterranean, and long-lived large-bodied mammal phenotypes. Our results reveal that permulations improve the statistical power of phylogenetic analyses and correctly calibrate statements of confidence in rejecting complex null distributions while maintaining or improving the enrichment of known functions related to the phenotype. We also find that permulations refine pathway enrichment analyses by correcting for nonindependence in gene ranks. Our results demonstrate that permulations are a powerful tool for improving statistical confidence in the conclusions of phylogenetic analysis when the parametric null is unknown.

Causal network perturbations for instance-specific analysis of single cell and disease samples

MOTIVATION

Complex diseases involve perturbation in multiple pathways and a major challenge in clinical genomics is characterizing pathway perturbations in individual samples. This can lead to patient-specific identification of the underlying mechanism of disease thereby improving diagnosis and personalizing treatment. Existing methods rely on external databases to quantify pathway activity scores. This ignores the data dependencies and that pathways are incomplete or condition-specific.

RESULTS

ssNPA is a new approach for subtyping samples based on deregulation of their gene networks. ssNPA learns a causal graph directly from control data. Sample-specific network neighborhood deregulation is quantified via the error incurred in predicting the expression of each gene from its Markov blanket. We evaluate the performance of ssNPA on liver development single-cell RNA-seq data, where the correct cell timing is recovered; and two TCGA datasets, where ssNPA patient clusters have significant survival differences. In all analyses ssNPA consistently outperforms alternative methods, highlighting the advantage of network-based approaches.

AVAILABILITY AND IMPLEMENTATION

http://www.benoslab.pitt.edu/Software/ssnpa/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Modeling strict age-targeted mitigation strategies for COVID-19

We use a simple SIR-like epidemic model integrating known age-contact patterns for the United States to model the effect of age-targeted mitigation strategies for a COVID-19-like epidemic. We find that, among strategies which end with population immunity, strict age-targeted mitigation strategies have the potential to greatly reduce mortalities and ICU utilization for natural parameter choices.

RERconverge: an R package for associating evolutionary rates with convergent traits

MOTIVATION

When different lineages of organisms independently adapt to similar environments, selection often acts repeatedly upon the same genes, leading to signatures of convergent evolutionary rate shifts at these genes. With the increasing availability of genome sequences for organisms displaying a variety of convergent traits, the ability to identify genes with such convergent rate signatures would enable new insights into the molecular basis of these traits.

RESULTS

Here we present the R package RERconverge, which tests for association between relative evolutionary rates of genes and the evolution of traits across a phylogeny. RERconverge can perform associations with binary and continuous traits, and it contains tools for visualization and enrichment analyses of association results.

AVAILABILITY AND IMPLEMENTATION

RERconverge source code, documentation and a detailed usage walk-through are freely available at https://github.com/nclark-lab/RERconverge. Datasets for mammals, Drosophila and yeast are available at https://bit.ly/2J2QBnj.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

AB0921 COMPARISON OF EFFICACY AND SAFETY OF DIFFERENT ANTI-INFLAMMATORY DRUGS AT INITIATION OF URATE-LOWERING THERAPY IN PATIENTS WITH GOUT (PRELIMINARY DATA)

Background:

NSAIDs, colchicine and glucocorticoids are used for prevention of acute arthritis in gout patients, yet there is little data on their comparative efficacy.

Objectives:

Comparison of efficacy and safety of different anti-inflammatory drugs used for prevention of acute arthritis at initiation of urate-lowering therapy in gout patients.

Methods:

This monocentric prospective study included 79 gout patients (75 (94.9%) male and 4 (5.1%) female patients) with the mean age of 51.3±10.9 years old. The inclusion criteria were the following: established gout (ACR/EULAR 2015 criteria), aged 18-80, serum uric acid level >360µmol/L, absence of urate-lowering therapy at baseline and at least one gout flare within past three months. The exclusion criteria were: absolute contraindications to all of the study drugs, GFR <30ml/min/1.73m2.

All of the patients were prescribed urate-lowering therapy (allopurinol or febuxostat), the dose was titrated until the target serum uric-acid level (<360µmol/L) was achieved. Simultaneously, preventive anti-inflammatory therapy was initiated and the drug for each patient was chosen individually: colchicine 0.5mg/day or any NSAID in minimal anti-inflammatory dose or prednisolone 7.5mg/day. The analysis of the data included 3-month comparative evaluation of the efficacy of the preventive therapy against the following parameters: frequency of gout flare and duration thereof, VAS pain intensity of flare. The laboratory tests included serum creatinine level, uric acid level, AST, ALT, creatine phosphokinase, glucose; clinical blood test before, two weeks and three months after the initiation of the therapy.

Results:

NSAIDs were received by 14 (17.7%) patients, colchicine by 56 (70.9%) and glucocorticoids by 9 (11.4%) patients. There were no differences initially in age, GFR or lab test values.

Three months later, the gout flares frequency median lowered to 1 [0;2] flare (p<0.01). The frequency of gout flares did not depend on the chosen drug and was 1 [0;1] for NSAIDs, 1 [0;2] for colchicine and 1 [1;2] for glucocorticoids.

40 (50.6%) patients out of 79 did not have a single flare. The patients who received NSAIDs (57.1%) and colchicine (42.9%) experienced no gout flares more often than those who received glucocorticoids (37.5%), but the differences were not significant.

However, the VAS pain intensity of gout flares in the patients who received NSAIDs (30.7±12.9mm) was lower than in those who received colchicine (42.1±12.3mm) and glucocorticoids (42.2±8.4mm) (p<0.05 for both).

The duration of gout flares on different drugs was not significantly different and was on average 3 [1.5;4] days for the patients on NSAIDs, 5 [3;7] days for those on colchicine and 5 [4;6] days for the patients who received glucocorticoids.

The NSAID therapy was discontinued in two cases, in which the serum transaminase levels (AST, ALT) more than doubled; the colchicine therapy - because of development of diarrhea in two patients and of myopathy in one.

Conclusion:

Efficacy of and tolerance to a three-month course of preventive therapy with NSAIDs and glucocorticoids in gout patients are comparable to that with colchicine. In case of development of gouty arthritis, preventive use of NSAIDs is characterized by lower pain intensity than as against colchicine or glucocorticoids.

Disclosure of Interests:

Maria Chikina: None declared, Maxim Elisеev Speakers bureau: Novartis, Menarini Group, Alium

AB0920 APPLICATION OF THE EULAR 2016 GUIDELINES FOR URATE-LOWERING THERAPY IN CLINICAL PRACTICE (DATA OF A SIX-MONTH PROSPECTIVE STUDY)

Background:

The EULAR 2016 guidelines on gout management provide for a consecutive regimen of urate-lowering medications; however, the possibility of reaching the target uric acid level when using the regimen has not been studied in clinical practice.

Objectives:

To assess the possibility of reaching the target uric acid level when following the EULAR 2016 guidelines on gout management with use of different xanthine oxidase inhibitors available in Russia.

Methods:

This monocentric prospective study included 83 gout patients (79 (95%) male and 4 (5%) female patients) with the mean age of 51.3±10.9 years old. The inclusion criterion was indications for urate-lowering therapy in accordance with the EULAR 2016 guidelines. The exclusion criteria were the following: absolute contraindications to all of the study drugs, GFR <30ml/min/1.73m2, and NYHA class III-IV heart failure.

At urate-lowering therapy initiation, the patients were prescribed allopurinol with the starting dose of 100mg/day; the dose was titrated until the target uric acid level was reached (maximum up to 900mg/day), and in the patients with GFR between 30 and 60ml/min/1.73m2 – up to 300mg/day. In case of insufficient efficacy of allopurinol (unachieved target uric acid level of <360µmol/L, for the patients with severe gout of <300µmol/L) or development of adverse reactions, allopurinol was replaced with febuxostat with the starting dose of 80mg/day and dose titration up to 120mg/day if necessary. The laboratory tests included serum creatinine level, uric acid level, AST, ALT, creatine phosphokinase, glucose; clinical blood test. The following parameters were assessed: possibility of reaching the target uric acid level when following the suggested regimen, and frequency of development of adverse reactions when using allopurinol and febuxostat.

Results:

37 (45%) patients had the target uric acid level of <360µmol/L and 46 (55%) pts – of <300µmol/L. The recommended therapy regimen allowed 77 (93%) patients under study to reach their target uric acid level.

The target uric acid level was achieved by 44 (53%) out of 79 patients on allopurinol, of whom 36 (82%) received 100-600mg/day, and 8 (18%) – 700-900mg/day. Of the patients with GFR of >60ml/min/1.73m2, 32 (73%) patients achieved their target uric acid level and of those with GFR <60ml/min/1.73m2 – so did 12 (27%).

Then the patients on allopurinol with unachieved target uric acid level were prescribed febuxostat (in 30 (77%) cases because of inefficacy of the allopurinol therapy, in 9 (33%) patients because of their development of adverse reactions where 5 pts had a more than doubled level of transaminase (ALT, AST), 2 pts had skin itch and 2 pts had hives).

In total, 39 patients received febuxostat, of whom 4 pts were with initial intolerance for allopurinol in past history, and 35 pts after therapy with maximum dose of allopurinol. A febuxostat dose of 80mg/day was associated with achievement of the target uric acid level in 14 (42%) patients and that of 120mg/day – in 19 (58%) patients, therefore, total 33 (85%) patients reached their target uric acid level. Four patients on febuxostat developed adverse reactions: 3 patients had a more than doubled serum transaminase level (ALT, AST) and 1 patient had hives. Also, an insignificant increase in the mean GFR was registered from 73±21.4ml/min/1.73m2 to 78.4±22.5ml/min/1.73m2 which did not differ between the two drugs.

Conclusion:

The recommended regimen of xanthine oxidase inhibitors in their maximal doses secures reaching the target uric acid level in 93% patients. In 47% patients, allopurinol in maximal doses (up to 900mg/day) does not significantly increase the possibility of reaching the target uric acid level, even though it demonstrates high tolerance.

Disclosure of Interests:

Maria Chikina: None declared, Maxim Elisеev Speakers bureau: Novartis, Menarini Group, Alium, Olga Sheliabina: None declared

A germinal center B cell-specific long non-coding RNA regulates the germinal center response

Long non-coding RNAs are a unique class of molecules involved in an exceptional variety of cellular processes, including transcriptional, translational, and epigenetic regulation. Here, we report the initial characterization of a lncRNA expressed specifically in the germinal center--organized sites of B cell proliferation, somatic hyper-mutation, and cellular differentiation that develop in response to antigenic challenge. The precise signals dictating how and when differentiated cells, such as memory B cells and long-lived plasma cells, exit the GC reaction remain incompletely understood. Thus, additional levels of molecular regulation are likely at work in the coordination of these diverse processes. We identify GCLnc1--a novel, nuclear-localized lncRNA--as a regulator of the GC reaction. As GCLnc1 is located adjacent to the murine Bcl6 locus, this lncRNA has the potential to modulate expression of key transcription factors controlling B cell identity and/or differentiation. Interestingly, forced over-expression of GCLnc1 in B cells led to upregulation of TFs associated with plasma cell identity, such as IRF4 and Blimp-1. When adoptively transferred in vivo, over-expression of GCLnc1 led to transduced B cells predominantly adopting a non-GC phenotype at the typical peak GC response, in addition to enhancing expression of IRF4 and Blimp-1. Genetic deletion of GCLnc1 led to reduced frequency of GC B cells, decreased Bcl6 expression, and dysregulated light zone/dark zone distribution in response to NP-KLH immunization. Collectively, we suggest GCLnc1 plays a key role in the integration of signaling events during the GC reaction, and may modulate the processes that drive GC exit.

Germinal center B cells selectively oxidize fatty acids for energy while conducting minimal glycolysis

Germinal center B cells (GCBCs) are critical for generating long-lived humoral immunity. How GCBCs meet the energetic challenge of rapid proliferation is poorly understood. Dividing lymphocytes typically rely on aerobic glycolysis over oxidative phosphorylation for energy. Here we report that GCBCs are exceptional among proliferating B and T cells as they actively oxidize fatty acids (FAs) and conduct minimal glycolysis. In vitro, GCBCs had a very low glycolytic extracellular acidification (ECAR) but consumed oxygen in response to FAs. [¹³C₆]-glucose feeding revealed that GCBCs generate significantly less phosphorylated glucose and little lactate. Further, GCBCs did not metabolize glucose into TCA cycle intermediates. Conversely, [¹³C₁₆]-palmitic acid labeling demonstrated that GCBCs generate most of their acetyl-CoA and acetylcarnitine from FAs. FA oxidation (FAO) was functionally important, as drug-mediated and genetic dampening of FAO resulted in a selective reduction GCBCs. Hence, GCBCs appear to uncouple rapid proliferation from aerobic glycolysis.

Pan-mammalian analysis of molecular constraints underlying extended lifespan

Although lifespan in mammals varies over 100-fold, the precise evolutionary mechanisms underlying variation in longevity remain unknown. Species-specific genetic changes have been observed in long-lived species including the naked mole-rat, bats, and the bowhead whale, but these adaptations do not generalize to other mammals. We present a novel method to identify associations between rates of protein evolution and continuous phenotypes across the entire mammalian phylogeny. Unlike previous analyses that focused on individual species, we treat absolute and relative longevity as quantitative traits and demonstrate that these lifespan traits affect the evolutionary constraint on hundreds of genes. Specifically, we find that genes related to cell cycle, DNA repair, cell death, the IGF1 pathway, and immunity are under increased evolutionary constraint in large and long-lived mammals. For mammals exceptionally long-lived for their body size, we find increased constraint in inflammation, DNA repair, and NFKB-related pathways. Strikingly, these pathways have considerable overlap with those that have been previously reported to have potentially adaptive changes in single-species studies, and thus would be expected to show decreased constraint in our analysis. This unexpected finding of increased constraint in many longevity-associated pathways underscores the power of our quantitative approach to detect patterns that generalize across the mammalian phylogeny.

Robust Method for Detecting Convergent Shifts in Evolutionary Rates

Identifying genomic elements underlying phenotypic adaptations is an important problem in evolutionary biology. Comparative analyses learning from convergent evolution of traits are gaining momentum in accurately detecting such elements. We previously developed a method for predicting phenotypic associations of genetic elements by contrasting patterns of sequence evolution in species showing a phenotype with those that do not. Using this method, we successfully demonstrated convergent evolutionary rate shifts in genetic elements associated with two phenotypic adaptations, namely the independent subterranean and marine transitions of terrestrial mammalian lineages. Our original method calculates gene-specific rates of evolution on branches of phylogenetic trees using linear regression. These rates represent the extent of sequence divergence on a branch after removing the expected divergence on the branch due to background factors. The rates calculated using this regression analysis exhibit an important statistical limitation, namely heteroscedasticity. We observe that the rates on branches that are longer on average show higher variance, and describe how this problem adversely affects the confidence with which we can make inferences about rate shifts. Using a combination of data transformation and weighted regression, we have developed an updated method that corrects this heteroscedasticity in the rates. We additionally illustrate the improved performance offered by the updated method at robust detection of convergent rate shifts in phylogenetic trees of protein-coding genes across mammals, as well as using simulated tree data sets. Overall, we present an important extension to our evolutionary-rates-based method that performs more robustly and consistently at detecting convergent shifts in evolutionary rates.

Liver Is a Generative Site for the B Cell Response to Ehrlichia muris

The B cell response to Ehrlichia muris is dominated by plasmablasts (PBs), with few-if any-germinal centers (GCs), yet it generates protective immunoglobulin M (IgM) memory B cells (MBCs) that express the transcription factor T-bet and harbor V-region mutations. Because Ehrlichia prominently infects the liver, we investigated the nature of liver B cell response and that of the spleen. B cells within infected livers proliferated and underwent somatic hypermutation (SHM). Vh-region sequencing revealed trafficking of clones between the spleen and liver and often subsequent local clonal expansion and intraparenchymal localization of T-bet⁺ MBCs. T-bet⁺ MBCs expressed MBC subset markers CD80 and PD-L2. Many T-bet⁺ MBCs lacked CD11b or CD11c expression but had marginal zone (MZ) B cell phenotypes and colonized the splenic MZ, revealing T-bet⁺ MBC plasticity. Hence, liver and spleen are generative sites of B cell responses, and they include V-region mutation and result in liver MBC localization.

Treg Cells Promote the SREBP1-Dependent Metabolic Fitness of Tumor-Promoting Macrophages via Repression of CD8+ T Cell-Derived Interferon-γ

Regulatory T (Treg) cells are crucial for immune homeostasis, but they also contribute to tumor immune evasion by promoting a suppressive tumor microenvironment (TME). Mice with Treg cell-restricted Neuropilin-1 deficiency show tumor resistance while maintaining peripheral immune homeostasis, thereby providing a controlled system to interrogate the impact of intratumoral Treg cells on the TME. Using this and other genetic models, we showed that Treg cells shaped the transcriptional landscape across multiple tumor-infiltrating immune cell types. Treg cells suppressed CD8⁺ T cell secretion of interferon-γ (IFNγ), which would otherwise block the activation of sterol regulatory element-binding protein 1 (SREBP1)-mediated fatty acid synthesis in immunosuppressive (M2-like) tumor-associated macrophages (TAMs). Thus, Treg cells indirectly but selectively sustained M2-like TAM metabolic fitness, mitochondrial integrity, and survival. SREBP1 inhibition augmented the efficacy of immune checkpoint blockade, suggesting that targeting Treg cells or their modulation of lipid metabolism in M2-like TAMs could improve cancer immunotherapy.

Pathway-level information extractor (PLIER) for gene expression data

A major challenge in gene expression analysis is to accurately infer relevant biological insights, such as variation in cell-type proportion or pathway activity, from global gene expression studies. We present pathway-level information extractor (PLIER) ( https://github.com/wgmao/PLIER and http://gobie.csb.pitt.edu/PLIER ), a broadly applicable solution for this problem that outperforms available cell proportion inference algorithms and can automatically identify specific pathways that regulate gene expression. Our method improves interstudy replicability and reveals biological insights when applied to trans-eQTL (expression quantitative trait loci) identification.

Adaptive plasticity of IL-10+ and IL-35+ Treg cells cooperatively promotes tumor T cell exhaustion

Regulatory T cells (T_reg cells) maintain host self-tolerance but are a major barrier to effective cancer immunotherapy. T_reg cells subvert beneficial anti-tumor immunity by modulating inhibitory receptor expression on tumor-infiltrating lymphocytes (TILs); however, the underlying mediators and mechanisms have remained elusive. Here we found that the cytokines IL-10 and IL-35 (Ebi3–IL-12α heterodimer) were divergently expressed by T_reg cell subpopulations in the tumor microenvironment (TME) and cooperatively promoted intratumoral T cell exhaustion by modulating multiple inhibitory receptor expression and exhaustion-associated transcriptomic signature of CD8⁺ TILs. While expression of BLIMP1 (encoded by Prdm1) was a common target; IL-10 and IL-35 differentially affected effector T cell versus memory T cell fates, respectively, highlighting their differential, partially overlapping but non-redundant regulation of anti-tumor immunity. Our results reveal previously unappreciated cooperative roles for T_reg cell-derived IL-10 and IL-35 in promoting BLIMP1-dependent exhaustion of CD8⁺ TILs that limits effective anti-tumor immunity.

Evolutionary rate covariation analysis of E-cadherin identifies Raskol as a regulator of cell adhesion and actin dynamics in Drosophila

The adherens junction couples the actin cytoskeletons of neighboring cells to provide the foundation for multicellular organization. The core of the adherens junction is the cadherin-catenin complex that arose early in the evolution of multicellularity to link actin to intercellular adhesions. Over time, evolutionary pressures have shaped the signaling and mechanical functions of the adherens junction to meet specific developmental and physiological demands. Evolutionary rate covariation (ERC) identifies proteins with correlated fluctuations in evolutionary rate that can reflect shared selective pressures and functions. Here we use ERC to identify proteins with evolutionary histories similar to the Drosophila E-cadherin (DE-cad) ortholog. Core adherens junction components α-catenin and p120-catenin displayed positive ERC correlations with DE-cad, indicating that they evolved under similar selective pressures during evolution between Drosophila species. Further analysis of the DE-cad ERC profile revealed a collection of proteins not previously associated with DE-cad function or cadherin-mediated adhesion. We then analyzed the function of a subset of ERC-identified candidates by RNAi during border cell (BC) migration and identified novel genes that function to regulate DE-cad. Among these, we found that the gene CG42684, which encodes a putative GTPase activating protein (GAP), regulates BC migration and adhesion. We named CG42684 raskol (“to split” in Russian) and show that it regulates DE-cad levels and actin protrusions in BCs. We propose that Raskol functions with DE-cad to restrict Ras/Rho signaling and help guide BC migration. Our results demonstrate that a coordinated selective pressure has shaped the adherens junction and this can be leveraged to identify novel components of the complexes and signaling pathways that regulate cadherin-mediated adhesion.

The establishment of intercellular adhesions facilitated the genesis of multicellular organisms. The adherens junction, which links the actin cytoskeletons of neighboring cells, arose early in the evolution of multicellularity and selective pressures have shaped its function and molecular composition over time. In this study, we used evolutionary rate covariation (ERC) analysis to examine the evolutionary history of the adherens junction and to identify proteins that coevolved with the core adherens junction protein Drosophila E-cadherin (DE-cad). ERC analysis of DE-cad revealed a collection of proteins with similar evolutionary histories. We then tested the role of ERC-identified candidates in border cell migration in the fly egg chamber, a process that requires the coordinated regulation of cell-cell adhesion and cell motility. Among these, we found that a previously uncharacterized gene CG42684, which encodes a putative GTPase activating protein (GAP), regulates the collective cell migration of border cells, stabilizes cell-cell adhesions and regulates the actin dynamics. Our results demonstrate that components of the adherens junction share an evolutionary history and that ERC analysis is a powerful method to identify novel components of cell adhesion complexes in Drosophila.

Kidney-infiltrating T cells in murine lupus nephritis are metabolically and functionally exhausted

While T cells are important for the pathogenesis of systemic lupus erythematosus (SLE) and lupus nephritis, little is known about how T cells function after infiltrating the kidney. The current paradigm suggests that kidney-infiltrating T cells (KITs) are activated effector cells contributing to tissue damage and ultimately organ failure. Herein, we demonstrate that the majority of CD4+ and CD8+ KITs in 3 murine lupus models are not effector cells, as hypothesized, but rather express multiple inhibitory receptors and are highly dysfunctional, with reduced cytokine production and proliferative capacity. In other systems, this hypofunctional profile is linked directly to metabolic and specifically mitochondrial dysfunction, which we also observed in KITs. The T cell phenotype was driven by the expression of an "exhausted" transcriptional signature. Our data thus reveal that the tissue parenchyma has the capability of suppressing T cell responses and limiting damage to self. These findings suggest avenues for the treatment of autoimmunity based on selectively exploiting the exhausted phenotype of tissue-infiltrating T cells.