Molecular subtypes explain lupus epigenomic heterogeneity unveiling new regulatory genetic risk variants.

The heterogeneity of systemic lupus erythematosus (SLE) can be explained by epigenetic alterations that disrupt transcriptional programs mediating environmental and genetic risk. This study evaluated the epigenetic contribution to SLE heterogeneity considering molecular and serological subtypes, genetics and transcriptional status, followed by drug target discovery. We performed a stratified epigenome-wide association studies of whole blood DNA methylation from 213 SLE patients and 221 controls. Methylation quantitative trait loci analyses, cytokine and transcription factor activity - epigenetic associations and methylation-expression correlations were conducted. New drug targets were searched for based on differentially methylated genes. In a stratified approach, a total of 974 differential methylation CpG sites with dependency on molecular subtypes and autoantibody profiles were found. Mediation analyses suggested that SLE-associated SNPs in the HLA region exert their risk through DNA methylation changes. Novel genetic variants regulating DNAm in disease or in specific molecular contexts were identified. The epigenetic landscapes showed strong association with transcription factor activity and cytokine levels, conditioned by the molecular context. Epigenetic signals were enriched in known and novel drug targets for SLE. This study reveals possible genetic drivers and consequences of epigenetic variability on SLE heterogeneity and disentangles the DNAm mediation role on SLE genetic risk and novel disease-specific meQTLs. Finally, novel targets for drug development were discovered.

Approaching Mass Cytometry Translational Studies by Experimental and Data Curation Settings.

Clinical studies are conducted to better understand the pathological mechanism of diseases and to find biomarkers associated with disease activity, drug response, or outcome prediction. Mass cytometry (MC) is a high-throughput single-cell technology that measures hundreds of cells per second with more than 40 markers per cell. Thus, it is a suitable tool for immune monitoring and biomarker discovery studies. Working in translational and clinical settings requires a careful experimental design to minimize, monitor, and correct the variations introduced during sample collection, preparation, acquisition, and analysis. In this review, we will focus on these important aspects of MC-related experiments and data curation in the context of translational clinical research projects.

Integrative non-pharmacological care for individuals at risk of rheumatoid arthritis.

There is increasing knowledge in the recognition of individuals at risk for progression to rheumatoid arthritis (RA) before the clinical manifestation of the disease. This prodromal phase preceding the manifestation of RA may represent a "window of opportunity" for preventive interventions that may transform the clinical approach to this disease. However, limited evidence exists in support of effective interventions to delay the onset or even halt the manifestation of RA. Given the multifactorial nature of RA development and disease progression, the latest guidelines for established RA stress the use of integrative interventions and multidisciplinary care strategies, combining pharmacologic treatment with non-pharmacological approaches. Accordingly, individuals at risk of RA could be offered an integrative, multifactorial intervention approach. Current data point toward pharmacological intervention reverting the subclinical inflammation and delay in the disease onset. In addition, targeting life style modifiable factors (smoking cessation, dental health, physical activity, and diet) may presumably improve RA prognosis in individuals at risk, mainly by changes in epigenetics, autoantibodies, cytokines profiles, and microbiome. Nonetheless, the benefits of multidisciplinary interventions to halt the manifestation of RA in at-risk individuals remain unknown. As there is a growing knowledge of possible pharmacological intervention in the preclinical phase, this narrative review aims to provide a comprehensive overview of non-pharmacological treatments in individuals at risk of RA. Considering the mechanisms preceding the clinical manifestation of RA we explored all aspects that would be worth modifying and that would represent an integrative non-pharmacological care for individuals at risk of RA.

Immune and molecular landscape behind non-response to Mycophenolate Mofetil and Azathioprine in lupus nephritis therapy.

Lupus nephritis (LN) represents one of the most severe complications of systemic lupus erythematosus, leading to end-stage kidney disease in worst cases. Current first-line therapies for LN, including mycophenolate mofetil (MMF) and azathioprine (AZA), fail to induce long-term remission in 60-70% of the patients, evidencing the urgent need to delve into the molecular knowledge-gap behind the non-response to these therapies. A longitudinal cohort of treated LN patients including clinical, cellular and transcriptomic data, was analyzed. Gene-expression signatures behind non-response to different drugs were revealed by differential expression analysis. Drug-specific non-response mechanisms and cell proportion differences were identified. Blood cell subsets mediating non-response were described using single-cell RNASeq data. We show that AZA and MMF non-response implicates different cells and regulatory functions. Mechanistic models were used to suggest add-on therapies to improve their current performance. Our results provide new insights into the molecular mechanisms associated with treatment failures in LN.

Lack of strong innate immune reactivity renders macrophages alone unable to control productive Varicella-Zoster Virus infection in an isogenic human iPSC-derived neuronal co-culture model.

With Varicella-Zoster Virus (VZV) being an exclusive human pathogen, human induced pluripotent stem cell (hiPSC)-derived neural cell culture models are an emerging tool to investigate VZV neuro-immune interactions. Using a compartmentalized hiPSC-derived neuronal model allowing axonal VZV infection, we previously demonstrated that paracrine interferon (IFN)-α2 signalling is required to activate a broad spectrum of interferon-stimulated genes able to counteract a productive VZV infection in hiPSC-neurons. In this new study, we now investigated whether innate immune signalling by VZV-challenged macrophages was able to orchestrate an antiviral immune response in VZV-infected hiPSC-neurons. In order to establish an isogenic hiPSC-neuron/hiPSC-macrophage co-culture model, hiPSC-macrophages were generated and characterised for phenotype, gene expression, cytokine production and phagocytic capacity. Even though immunological competence of hiPSC-macrophages was shown following stimulation with the poly(dA:dT) or treatment with IFN-α2, hiPSC-macrophages in co-culture with VZV-infected hiPSC-neurons were unable to mount an antiviral immune response capable of suppressing a productive neuronal VZV infection. Subsequently, a comprehensive RNA-Seq analysis confirmed the lack of strong immune responsiveness by hiPSC-neurons and hiPSC-macrophages upon, respectively, VZV infection or challenge. This may suggest the need of other cell types, like T-cells or other innate immune cells, to (co-)orchestrate an efficient antiviral immune response against VZV-infected neurons.

Protocol for large scale whole blood immune monitoring by mass cytometry and Cyto Quality Pipeline.

Mass cytometry (MC) is a powerful large-scale immune monitoring technology. To maximize MC data quality, we present a protocol for whole blood analysis together with an R package, Cyto Quality Pipeline (CytoQP), which minimizes the experimental artifacts and batch effects to ensure data reproducibility. We describe the steps to stimulate, fix, and freeze blood samples before acquisition to make them suitable for retrospective studies. We then detail the use of barcoding and reference samples to facilitate multicenter and multi-batch experiments. For complete details on the use and execution of this protocol, please refer to Rybakowska et al. (2021a) and (2021b).

Immune mechanisms associated with cardiovascular disease in systemic lupus erythematosus: A path to potential biomarkers.

Systemic lupus erythematosus (SLE) patients display an increased risk of cardiovascular disease (CVD). With the improved clinical management of other classical severe manifestation of the disease, CVD is becoming one of the most relevant complications of SLE, and it is an important factor causing morbidity and mortality. Several immune constituents have been shown to be involved in the pathogenesis of atherosclerosis and endothelial damage in SLE patients, including specific circulating cell populations, autoantibodies, and inflammatory mediators. In this review, we summarize the presentation of CVD in SLE and the role of the autoimmune responses present in SLE patients in the induction of atherogenesis, endothelial impairment and cardiac disease. Additionally, we discuss the utility of these immune mediators as early CVD biomarkers and targets for clinical intervention in SLE patients.

Efficacy and safety of universal (TCRKO) ARI-0001 CAR-T cells for the treatment of B-cell lymphoma.

Autologous T cells expressing the Chimeric Antigen Receptor (CAR) have been approved as advanced therapy medicinal products (ATMPs) against several hematological malignancies. However, the generation of patient-specific CAR-T products delays treatment and precludes standardization. Allogeneic off-the-shelf CAR-T cells are an alternative to simplify this complex and time-consuming process. Here we investigated safety and efficacy of knocking out the TCR molecule in ARI-0001 CAR-T cells, a second generation αCD19 CAR approved by the Spanish Agency of Medicines and Medical Devices (AEMPS) under the Hospital Exemption for treatment of patients older than 25 years with Relapsed/Refractory acute B cell lymphoblastic leukemia (B-ALL). We first analyzed the efficacy and safety issues that arise during disruption of the TCR gene using CRISPR/Cas9. We have shown that edition of TRAC locus in T cells using CRISPR as ribonuleorproteins allows a highly efficient TCR disruption (over 80%) without significant alterations on T cells phenotype and with an increased percentage of energetic mitochondria. However, we also found that efficient TCRKO can lead to on-target large and medium size deletions, indicating a potential safety risk of this procedure that needs monitoring. Importantly, TCR edition of ARI-0001 efficiently prevented allogeneic responses and did not detectably alter their phenotype, while maintaining a similar anti-tumor activity ex vivo and in vivo compared to unedited ARI-0001 CAR-T cells. In summary, we showed here that, although there are still some risks of genotoxicity due to genome editing, disruption of the TCR is a feasible strategy for the generation of functional allogeneic ARI-0001 CAR-T cells. We propose to further validate this protocol for the treatment of patients that do not fit the requirements for standard autologous CAR-T cells administration.

Erratum: Physiological lentiviral vectors for the generation of improved CAR-T cells.

[This corrects the article DOI: 10.1016/j.omto.2022.05.003.].

Physiological lentiviral vectors for the generation of improved CAR-T cells.

Anti-CD19 chimeric antigen receptor (CAR)-T cells have achieved impressive outcomes for the treatment of relapsed and refractory B-lineage neoplasms. However, important limitations still remain due to severe adverse events (i.e., cytokine release syndrome and neuroinflammation) and relapse of 40%-50% of the treated patients. Most CAR-T cells are generated using retroviral vectors with strong promoters that lead to high CAR expression levels, tonic signaling, premature exhaustion, and overstimulation, reducing efficacy and increasing side effects. Here, we show that lentiviral vectors (LVs) expressing the transgene through a WAS gene promoter (AW-LVs) closely mimic the T cell receptor (TCR)/CD3 expression kinetic upon stimulation. These AW-LVs can generate improved CAR-T cells as a consequence of their moderate and TCR-like expression profile. Compared with CAR-T cells generated with human elongation factor α (EF1α)-driven-LVs, AW-CAR-T cells exhibited lower tonic signaling, higher proportion of naive and stem cell memory T cells, less exhausted phenotype, and milder secretion of tumor necrosis factor alpha (TNF-α) and interferon (IFN)-É£ after efficient destruction of CD19+ lymphoma cells, both in vitro and in vivo. Moreover, we also showed their improved efficiency using an in vitro CD19+ pancreatic tumor model. We finally demonstrated the feasibility of large-scale manufacturing of AW-CAR-T cells in guanosine monophosphate (GMP)-like conditions. Based on these data, we propose the use of AW-LVs for the generation of improved CAR-T products.

SIDT1 plays a key role in type I IFN responses to nucleic acids in plasmacytoid dendritic cells and mediates the pathogenesis of an imiquimod-induced psoriasis model.

BACKGROUND: Type I IFN (IFN-I) is a family of cytokines involved in the pathogenesis of autoimmune and autoinflammatory diseases such as psoriasis. SIDT1 is an ER-resident protein expressed in the lymphoid lineage, and involved in anti-viral IFN-I responses in vivo, through an unclear mechanism. Herein we have dissected the role of SIDT1 in the natural IFN-producing cells, the plasmacytoid dendritic cells (pDC). METHODS: The function of SIDT1 in pDC was determined by silencing its expression in human primary pDC and GEN2.2 cell line. SIDT1 role in vivo was assessed using the imiquimod-induced psoriasis model in the SIDT1-deficient mice (sidt1-/-). FINDINGS: Silencing of SIDT1 in GEN2.2 led to a blockade of the IFN-I response after stimulation of TLR7 and TLR9, without affecting the pro-inflammatory responses or upregulation of maturation markers. We found that SIDT1 migrates from the ER to the endosomal and lysosomal compartments together with TLR9 after CpG stimulation, participating in the access of the TLR9-CpG complex to lysosome-related vesicles, and therefore mediating the activation of TBK1 and the nuclear migration of IRF7, but not of NF-κB. sidt1-/- mice showed a significant decrease in severity parameters of the imiquimod-induced acute psoriasis-like model, associated with a decrease in the production of IFN-I and IFN-dependent chemokines. INTERPRETATION: Our findings indicate that SIDT1 is at the cross-road between the IFN-I and the proinflammatory pathways and constitutes a promising drug target for psoriasis and other diseases mediated by IFN-I responses. FUNDING: This work was supported by the Consejería de Salud y Familias de la Junta de Andalucía (PIER_S1149 and C2_S0050) and Instituto de Salud Carlos III (PI18/00082 and PI21/01151), partly supported by European FEDER funds, and prior funding to MEAR from the Alliance for Lupus Research and the Swedish Research Council.

PeacoQC: Peak-based selection of high quality cytometry data.

In cytometry analysis, a large number of markers is measured for thousands or millions of cells, resulting in high-dimensional datasets. During the measurement of these samples, erroneous events can occur such as clogs, speed changes, slow uptake of the sample etc., which can influence the downstream analysis and can even lead to false discoveries. As these issues can be difficult to detect manually, an automated approach is recommended. In order to filter these erroneous events out, we created a novel quality control algorithm, Peak Extraction And Cleaning Oriented Quality Control (PeacoQC), that allows for automated cleaning of cytometry data. The algorithm will determine density peaks per channel on which it will remove low quality events based on their position in the isolation tree and on their mean absolute deviation distance to these density peaks. To evaluate PeacoQC's cleaning capability, it was compared to three other existing quality control algorithms (flowAI, flowClean and flowCut) on a wide variety of datasets. In comparison to the other algorithms, PeacoQC was able to filter out all different types of anomalies in flow, mass and spectral cytometry data, while the other methods struggled with at least one type. In the quantitative comparison, PeacoQC obtained the highest median balanced accuracy and a similar running time compared to the other algorithms while having a better scalability for large files. To ensure that the parameters chosen in the PeacoQC algorithm are robust, the cleaning tool was run on 16 public datasets. After inspection, only one sample was found where the parameters should be further optimized. The other 15 datasets were analyzed correctly indicating a robust parameter choice. Overall, we present a fast and accurate quality control algorithm that outperforms existing tools and ensures high-quality data that can be used for further downstream analysis. An R implementation is available.

Integrative epigenomics in Sjögren´s syndrome reveals novel pathways and a strong interaction between the HLA, autoantibodies and the interferon signature.

Primary Sjögren's syndrome (SS) is a systemic autoimmune disease characterized by lymphocytic infiltration and damage of exocrine salivary and lacrimal glands. The etiology of SS is complex with environmental triggers and genetic factors involved. By conducting an integrated multi-omics study, we confirmed a vast coordinated hypomethylation and overexpression effects in IFN-related genes, what is known as the IFN signature. Stratified and conditional analyses suggest a strong interaction between SS-associated HLA genetic variation and the presence of Anti-Ro/SSA autoantibodies in driving the IFN epigenetic signature and determining SS. We report a novel epigenetic signature characterized by increased DNA methylation levels in a large number of genes enriched in pathways such as collagen metabolism and extracellular matrix organization. We identified potential new genetic variants associated with SS that might mediate their risk by altering DNA methylation or gene expression patterns, as well as disease-interacting genetic variants that exhibit regulatory function only in the SS population. Our study sheds new light on the interaction between genetics, autoantibody profiles, DNA methylation and gene expression in SS, and contributes to elucidate the genetic architecture of gene regulation in an autoimmune population.

Immune-Related Urine Biomarkers for the Diagnosis of Lupus Nephritis.

The kidney is one of the main organs affected by the autoimmune disease systemic lupus erythematosus. Lupus nephritis (LN) concerns 30-60% of adult SLE patients and it is significantly associated with an increase in the morbidity and mortality. The definitive diagnosis of LN can only be achieved by histological analysis of renal biopsies, but the invasiveness of this technique is an obstacle for early diagnosis of renal involvement and a proper follow-up of LN patients under treatment. The use of urine for the discovery of non-invasive biomarkers for renal disease in SLE patients is an attractive alternative to repeated renal biopsies, as several studies have described surrogate urinary cells or analytes reflecting the inflammatory state of the kidney, and/or the severity of the disease. Herein, we review the main findings in the field of urine immune-related biomarkers for LN patients, and discuss their prognostic and diagnostic value. This manuscript is focused on the complement system, antibodies and autoantibodies, chemokines, cytokines, and leukocytes, as they are the main effectors of LN pathogenesis.

Data processing workflow for large-scale immune monitoring studies by mass cytometry.

Mass cytometry is a powerful tool for deep immune monitoring studies. To ensure maximal data quality, a careful experimental and analytical design is required. However even in well-controlled experiments variability caused by either operator or instrument can introduce artifacts that need to be corrected or removed from the data. Here we present a data processing pipeline which ensures the minimization of experimental artifacts and batch effects, while improving data quality. Data preprocessing and quality controls are carried out using an R pipeline and packages like CATALYST for bead-normalization and debarcoding, flowAI and flowCut for signal anomaly cleaning, AOF for files quality control, flowClean and flowDensity for gating, CytoNorm for batch normalization and FlowSOM and UMAP for data exploration. As proper experimental design is key in obtaining good quality events, we also include the sample processing protocol used to generate the data. Both, analysis and experimental pipelines are easy to scale-up, thus the workflow presented here is particularly suitable for large-scale, multicenter, multibatch and retrospective studies.

Integrative Analysis Reveals a Molecular Stratification of Systemic Autoimmune Diseases.

OBJECTIVE: Clinical heterogeneity, a hallmark of systemic autoimmune diseases, impedes early diagnosis and effective treatment, issues that may be addressed if patients could be classified into groups defined by molecular pattern. This study was undertaken to identify molecular clusters for reclassifying systemic autoimmune diseases independently of clinical diagnosis. METHODS: Unsupervised clustering of integrated whole blood transcriptome and methylome cross-sectional data on 955 patients with 7 systemic autoimmune diseases and 267 healthy controls was undertaken. In addition, an inception cohort was prospectively followed up for 6 or 14 months to validate the results and analyze whether or not cluster assignment changed over time. RESULTS: Four clusters were identified and validated. Three were pathologic, representing "inflammatory," "lymphoid," and "interferon" patterns. Each included all diagnoses and was defined by genetic, clinical, serologic, and cellular features. A fourth cluster with no specific molecular pattern was associated with low disease activity and included healthy controls. A longitudinal and independent inception cohort showed a relapse-remission pattern, where patients remained in their pathologic cluster, moving only to the healthy one, thus showing that the molecular clusters remained stable over time and that single pathogenic molecular signatures characterized each individual patient. CONCLUSION: Patients with systemic autoimmune diseases can be jointly stratified into 3 stable disease clusters with specific molecular patterns differentiating different molecular disease mechanisms. These results have important implications for future clinical trials and the study of nonresponse to therapy, marking a paradigm shift in our view of systemic autoimmune diseases.

Stabilization of Human Whole Blood Samples for Multicenter and Retrospective Immunophenotyping Studies.

Whole blood is often collected for large-scale immune monitoring studies to track changes in cell frequencies and responses using flow (FC) or mass cytometry (MC). In order to preserve sample composition and phenotype, blood samples should be analyzed within 24 h after bleeding, restricting the recruitment, analysis protocols, as well as biobanking. Herein, we have evaluated two whole blood preservation protocols that allow rapid sample processing and long-term stability. Two fixation buffers were used, Phosphoflow Fix and Lyse (BD) and Proteomic Stabilizer (PROT) to fix and freeze whole blood samples for up to 6 months. After analysis by an 8-plex panel by FC and a 26-plex panel by MC, manual gating of circulating leukocyte populations and cytokines was performed. Additionally, we tested the stability of a single sample over a 13-months period using 45 consecutive aliquots and a 34-plex panel by MC. We observed high correlation and low bias toward any cell population when comparing fresh and 6 months frozen blood with FC and MC. This correlation was confirmed by hierarchical clustering. Low coefficients of variation (CV) across studied time points indicate good sample preservation for up to 6 months. Cytokine detection stability was confirmed by low CVs, with some differences between fresh and fixed conditions. Thirteen months regular follow-up of PROT samples showed remarkable sample stability. Whole blood can be preserved for phenotyping and cytokine-response studies provided the careful selection of a compatible antibody panel. However, possible changes in cell morphology, differences in antibody affinity, and changes in cytokine-positive cell frequencies when compared to fresh blood should be considered. Our setting constitutes a valuable tool for multicentric and retrospective studies. © 2020 International Society for Advancement of Cytometry.

Key steps and methods in the experimental design and data analysis of highly multi-parametric flow and mass cytometry.

High-dimensional, single-cell cell technologies revolutionized the way to study biological systems, and polychromatic flow cytometry (FC) and mass cytometry (MC) are two of the drivers of this revolution. As up to 30-50 dimensions respectively can be measured per single-cell, they allow deep phenotyping combined with cellular functions studies, like cytokine production or protein phosphorylation. In parallel, the bioinformatics field develops algorithms that are able to process incoming data and extract the most useful and meaningful biological information. However, the success of automated analysis tools depends on the generation of high-quality data. In this review we present the most recent FC and MC computational approaches that are used to prepare, process and interpret high-content cytometry data. We also underscore proper experimental design as a key step for obtaining good quality data.

Metagene projection characterizes GEN2.2 and CAL-1 as relevant human plasmacytoid dendritic cell models.

MOTIVATION: Plasmacytoid dendritic cells (pDC) play a major role in the regulation of adaptive and innate immunity. Human pDC are difficult to isolate from peripheral blood and do not survive in culture making the study of their biology challenging. Recently, two leukemic counterparts of pDC, CAL-1 and GEN2.2, have been proposed as representative models of human pDC. Nevertheless, their relationship with pDC has been established only by means of particular functional and phenotypic similarities. With the aim of characterizing GEN2.2 and CAL-1 in the context of the main circulating immune cell populations we have performed microarray gene expression profiling of GEN2.2 and carried out an integrated analysis using publicly available gene expression datasets of CAL-1 and the main circulating primary leukocyte lineages. RESULTS: Our results show that GEN2.2 and CAL-1 share common gene expression programs with primary pDC, clustering apart from the rest of circulating hematopoietic lineages. We have also identified common differentially expressed genes that can be relevant in pDC biology. In addition, we have revealed the common and differential pathways activated in primary pDC and cell lines upon CpG stimulatio. AVAILABILITY AND IMPLEMENTATION: R code and data are available in the supplementary material. CONTACT: pedro.carmona@genyo.es or concepcion.maranon@genyo.es. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Myeloid Populations in Systemic Autoimmune Diseases.

Systemic autoimmune diseases (SADs) encompass a wide spectrum of clinical signs as a reflection of their complex physiopathology. A variety of mechanisms related with the innate immune system are in the origin of the loss of self-tolerance in these diseases, and for most of them, the myeloid leukocytes are key actors. Monocytes, macrophages, dendritic cells, and neutrophils are first-line immune effectors located in the interface between innate and adaptive immunity. They are crucial in the organization of the local and systemic responses to damage-associated molecular patterns (DAMPs) and determine the intensity, orientation, and duration of the local immune response through the expression of chemokines, costimulatory or protolerogenic factors. In this review, we summarize the current knowledge about the role of the main myeloid populations in the induction and maintenance of systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), primary antiphospholipid antibody syndrome (PAPS), systemic sclerosis (SSc), and Sjögren's syndrome (SjS), based on the data from both mouse preclinical models and patients. According to these data, our challenge in the next few years is to better dissect the fine mechanisms underlying the pathological role of myeloid cells in these diseases in order to define specific cell subsets or proteins that can be potential targets for drug development.