27 research outputs found
Standardization procedure for flow cytometry data harmonization in prospective multicenter studies
One of the most challenging objective for clinical cytometry in prospective multicenter
immunomonitoring trials is to compare frequencies, absolute numbers of leukocyte populations and
further the mean fluorescence intensities of cell markers, especially when the data are generated from
different instruments. Here, we describe an innovative standardization workflow to compare all data
to carry out any large-scale, prospective multicentric flow cytometry analysis whatever the duration,
the number or type of instruments required for the realization of such project
Machine learning identifies a common signature for anti-SSA/Ro60 antibody expression across autoimmune diseases
Anti-Ro autoantibodies are among the most frequently detected extractable nuclear antigen autoantibodies, mainly associated with primary Sjögren's syndrome (pSS), systemic lupus erythematosus (SLE) and undifferentiated connective tissue disease (UCTD). Is there a common signature to all patients expressing anti-Ro60 autoantibodies regardless of their disease phenotype?Using high-throughput multi-omics data collected within the cross-sectional cohort from the PRECISESADS IMI project (genetic, epigenomic, transcriptomic, combined with flow cytometric data, multiplexed cytokines, classical serology and clinical data), we assessed by machine learning the integrated molecular profiling of 520 anti-Ro60-positive (anti-Ro60+ ) compared to 511 anti-Ro60-negative (anti-Ro60- ) patients with pSS, SLE and UCTD, and 279 healthy controls (HCs).The selected features for RNA-Seq, DNA methylation and GWAS data allowed a clear separation between anti-Ro60+ and anti-Ro60- patients. The different features selected by machine learning from the anti-Ro60+ patients constitute specific signatures when compared to anti-Ro60- patients and HCs. Remarkably, the transcript z-score of three genes (ATP10A, MX1 and PARP14), presenting an overexpression associated with a hypomethylation and genetic variation, and independently identified by the Boruta algorithm, was clearly higher in anti-Ro60+ patients compared to anti-Ro60- patients in all the diseases. We demonstrate that these signatures, enriched in interferon stimulated genes, were also found in anti-Ro60+ patients with rheumatoid arthritis and systemic sclerosis and remained stable over time and not influenced by treatment.Anti-Ro60+ patients present a specific inflammatory signature regardless of their disease suggesting that a dual therapeutic approach targeting both Ro-associated RNAs and anti-Ro60 autoantibodies should be considered
IgM antibodies against malondialdehyde and phosphorylcholine in different systemic rheumatic diseases
IgM antibodies against phosphorylcholine (anti-PC) and malondialdehyde (anti-MDA) may have protective properties in cardiovascular and rheumatic diseases. We here compare these antibodies in systemic rheumatic conditions and study their properties. Anti-PC and anti-MDA was measured using ELISA in patients with SLE (374), RA (354), Mixed connective tissue disease (MCTD, 77), Systemic sclerosis (SSc, 331), Sjögren's syndrome (SjS, 324), primary antiphospholipid syndrome (PAPs, 65), undifferentiated connective tissue disease (UCTD, 118) and 515 matched healthy controls (HC). Cardiovascular score (CV) was broadly defined based on clinical disease symptoms. Anti-PC and anti-MDA peptide/protein characterization were compared using a proteomics de novo sequencing approach. anti-MDA and anti-PC were extracted from total IgM. The proportion of Treg cells was determined by flow cytometry. The maximal difference between cases and controls was shown for MCTD: significantly lower IgM Anti-PC but not anti-MDA among patients (median 49.3RU/ml vs 70.4 in healthy controls, p(t-test) = 0.0037). IgM low levels were more prevalent in MCTD, SLE, SjS, SSc and UCTD. IgM anti-PC variable region profiles were different from and more homologous than anti-MDA. Anti-PC but not anti-MDA were significantly negatively correlated with CV in the whole patient group. In contrast to IgM anti-PC, anti-MDA did not promote polarization of Tregs. Taken together, Anti-PC is decreased in MCTD and also in SLE, SjS and SSc but not in other studied diseases. Anti-PC may thus differentiate between these. In contrast, anti-MDA did not show these differences between diseases studied. Anti-PC level is negatively correlated with CV in the patient group cohort. In contrast to anti-PC, anti-MDA did not promote Treg polarization. These findings could have both diagnostic and therapeutic implications, one possibility being active or passive immunization with PC in some rheumatic conditions
Genome-wide association study identifies Sjögren’s risk loci with functional implications in immune and glandular cells
Sjögren’s disease is a complex autoimmune disease with twelve established susceptibility
loci. This genome-wide association study (GWAS) identifies ten novel genome-wide significant
(GWS) regions in Sjögren’s cases of European ancestry: CD247, NAB1, PTTG1-
MIR146A, PRDM1-ATG5, TNFAIP3, XKR6, MAPT-CRHR1, RPTOR-CHMP6-BAIAP6, TYK2,
SYNGR1. Polygenic risk scores yield predictability (AUROC = 0.71) and relative risk of 12.08.
Interrogation of bioinformatics databases refine the associations, define local regulatory
networks of GWS SNPs from the 95% credible set, and expand the implicated gene list to
>40. Many GWS SNPs are eQTLs for genes within topologically associated domains in
immune cells and/or eQTLs in the main target tissue, salivary glands.United States Department of Health & Human Services
National Institutes of Health (NIH) - USA HHSN268200782096C
HHSN268201100011I
HHSN268201200008I
R01AR073855
R01AR065953
R01AR074310
P50AR060804
R01AR050782
R01DE018209
R33AR076803
R21AR079089NIDCR Sjogren's Syndrome Clinic
NIDCR Division of Intramural Research at the National Institutes of Health funds Z01-DE000704German Research Foundation (DFG) EXC 2155
390874280Research Council of Norway 240421
316120Western Norway Regional Health Authority (Helse Vest) 911807
912043Swedish Research Council for Medicine and Health
Swedish Rheumatism Association
King Gustav V's 80-year Foundation
Swedish Society of Medicine
Swedish Cancer SocietySjogren's Syndrome Foundation
Phileona Foundation
Stockholm County Council
Swedish Research CouncilEuropean Commission 2017-000641Assistance Publique-Hopitaux de Paris (Ministry of Health) P060228French society of RheumatologyUnited States Department of Health & Human Services
National Institutes of Health (NIH) - USA
NIH National Institute on Aging (NIA) RC2 AG036495
RC4 AG039029
United States Department of Health & Human Services
National Institutes of Health (NIH) - USA
NIH National Institute of Dental & Craniofacial Research (NIDCR)
United States Department of Health & Human Services
National Institutes of Health (NIH) - USA
NIH National Eye Institute (NEI)
United States Department of Health & Human Services
National Institutes of Health (NIH) - USA
NIH Office of Research on Women's Health (ORWH) N01-DE-32636
NIDCR through CIDR's NIH contrac
IgM antibodies against malondialdehyde and phosphorylcholine in different systemic rheumatic diseases
IgM antibodies against phosphorylcholine (anti-PC) and malondialdehyde (anti-MDA) may have protective properties in cardiovascular and rheumatic diseases. We here compare these antibodies in systemic rheumatic conditions and study their properties. Anti-PC and anti-MDA was measured using ELISA in patients with SLE (374), RA (354), Mixed connective tissue disease (MCTD, 77), Systemic sclerosis (SSc, 331), Sjögren's syndrome (SjS, 324), primary antiphospholipid syndrome (PAPs, 65), undifferentiated connective tissue disease (UCTD, 118) and 515 matched healthy controls (HC). Cardiovascular score (CV) was broadly defined based on clinical disease symptoms. Anti-PC and anti-MDA peptide/protein characterization were compared using a proteomics de novo sequencing approach. anti-MDA and anti-PC were extracted from total IgM. The proportion of Treg cells was determined by flow cytometry. The maximal difference between cases and controls was shown for MCTD: significantly lower IgM Anti-PC but not anti-MDA among patients (median 49.3RU/ml vs 70.4 in healthy controls, p(t-test) = 0.0037). IgM low levels were more prevalent in MCTD, SLE, SjS, SSc and UCTD. IgM anti-PC variable region profiles were different from and more homologous than anti-MDA. Anti-PC but not anti-MDA were significantly negatively correlated with CV in the whole patient group. In contrast to IgM anti-PC, anti-MDA did not promote polarization of Tregs. Taken together, Anti-PC is decreased in MCTD and also in SLE, SjS and SSc but not in other studied diseases. Anti-PC may thus differentiate between these. In contrast, anti-MDA did not show these differences between diseases studied. Anti-PC level is negatively correlated with CV in the patient group cohort. In contrast to anti-PC, anti-MDA did not promote Treg polarization. These findings could have both diagnostic and therapeutic implications, one possibility being active or passive immunization with PC in some rheumatic conditions.PRECISESADS Clinical Consortium Members: Te research leading to these results has received support from the Innovative Medicines Initiative Joint Undertaking under grant agreement n°115565, resources of which are composed of fnancial contribution from the European Union’s Seventh Framework Programme (FP7/2007–2013) and EFPIA companies in kind contribution. Swedish Heart Lung foundation and Swedish Rheumatism Association also contributed to fnancing. Open access funding provided by Karolinska Institute.Ye
Epigenome-Wide Comparative Study Reveals Key Differences Between Mixed Connective Tissue Disease and Related Systemic Autoimmune Diseases
Mixed Connective Tissue Disease (MCTD) is a rare complex systemic autoimmune disease (SAD) characterized by the presence of increased levels of anti-U1 ribonucleoprotein autoantibodies and signs and symptoms that resemble other SADs such as systemic sclerosis (SSc), rheumatoid arthritis (RA), and systemic lupus erythematosus (SLE). Due to its low prevalence, this disease has been very poorly studied at the molecular level. We performed for the first time an epigenome-wide association study interrogating DNA methylation data obtained with the Infinium MethylationEPIC array from whole blood samples in 31 patients diagnosed with MCTD and 255 healthy subjects. We observed a pervasive hypomethylation involving 170 genes enriched for immune-related function such as those involved in type I interferon signaling pathways or in negative regulation of viral genome replication. We mostly identified epigenetic signals at genes previously implicated in other SADs, for example MX1, PARP9, DDX60, or IFI44L, for which we also observed that MCTD patients exhibit higher DNA methylation variability compared with controls, suggesting that these sites might be involved in plastic immune responses that are relevant to the disease. Through methylation quantitative trait locus (meQTL) analysis we identified widespread local genetic effects influencing DNA methylation variability at MCTD-associated sites. Interestingly, for IRF7, IFI44 genes, and the HLA region we have evidence that they could be exerting a genetic risk on MCTD mediated through DNA methylation changes. Comparison of MCTD-associated epigenome with patients diagnosed with SLE, or Sjogren's Syndrome, reveals a common interferon-related epigenetic signature, however we find substantial epigenetic differences when compared with patients diagnosed with rheumatoid arthritis and systemic sclerosis. Furthermore, we show that MCTD-associated CpGs are potential epigenetic biomarkers with high diagnostic value. Our study serves to reveal new genes and pathways involved in MCTD, to illustrate the important role of epigenetic modifications in MCTD pathology, in mediating the interaction between different genetic and environmental MCTD risk factors, and as potential biomarkers of SADs
Expression Quantitative Trait Locus Analysis in Systemic Sclerosis Identifies New Candidate Genes Associated With Multiple Aspects of Disease Pathology
Objective: To identify the genetic variants that affect gene expression (expression quantitative trait loci [eQTLs]) in systemic sclerosis (SSc) and to investigate their role in the pathogenesis of the disease.
Methods: We performed an eQTL analysis using whole-blood sequencing data from 333 SSc patients and 524 controls and integrated them with SSc genome-wide association study (GWAS) data. We integrated our findings from expression modeling, differential expression analysis, and transcription factor binding site enrichment with key clinical features of SSc.
Results: We detected 49,123 validated cis-eQTLs from 4,539 SSc-associated single-nucleotide polymorphisms (SNPs) (PGWAS 0.05). As a result, 233 candidates were identified, 134 (58%) of them associated with hallmarks of SSc and 105 (45%) of them differentially expressed in the blood cells, skin, or lung tissue of SSc patients. Transcription factor binding site analysis revealed enriched motifs of 24 transcription factors (5%) among SSc eQTLs, 5 of which were found to be differentially regulated in the blood cells (ELF1 and MGA), skin (KLF4 and ID4), and lungs (TBX4) of SSc patients. Ten candidate genes (4%) can be targeted by approved medications for immune-mediated diseases, of which only 3 have been tested in clinical trials in patients with SSc.
Conclusion: The findings of the present study indicate a new layer to the molecular complexity of SSc, contributing to a better understanding of the pathogenesis of the disease
A new molecular classification to drive precision treatment strategies in primary Sjögren’s syndrome
There is currently no approved treatment for primary Sjögren's syndrome, a disease that primarily affects adult women. The difficulty in developing effective therapies is -in part- because of the heterogeneity in the clinical manifestation and pathophysiology of the disease. Finding common molecular signatures among patient subgroups could improve our understanding of disease etiology, and facilitate the development of targeted therapeutics. Here, we report, in a cross-sectional cohort, a molecular classification scheme for Sjögren's syndrome patients based on the multi-omic profiling of whole blood samples from a European cohort of over 300 patients, and a similar number of age and gender-matched healthy volunteers. Using transcriptomic, genomic, epigenetic, cytokine expression and flow cytometry data, combined with clinical parameters, we identify four groups of patients with distinct patterns of immune dysregulation. The biomarkers we identify can be used by machine learning classifiers to sort future patients into subgroups, allowing the re-evaluation of response to treatments in clinical trials
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