scholarly journals Nucleic Acid-Sensing and Interferon-Inducible Pathways Show Differential Methylation in MZ Twins Discordant for Lupus and Overexpression in Independent Lupus Samples: Implications for Pathogenic Mechanism and Drug Targeting

Genes ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1898
Author(s):  
Miranda Marion ◽  
Paula Ramos ◽  
Prathyusha Bachali ◽  
Adam Labonte ◽  
Kip Zimmerman ◽  
...  
Keyword(s):  
Gene Expression ◽  
Nucleic Acid ◽  
Lupus Erythematosus ◽  
Whole Blood ◽  
Cell Types ◽  
Differential Methylation ◽  
European Ancestry ◽  
Tissue Type ◽  
Type I ◽  
Mz Twins

Systemic lupus erythematosus (SLE) is a chronic, multisystem, autoimmune inflammatory disease with genomic and non-genomic contributions to risk. We hypothesize that epigenetic factors are a significant contributor to SLE risk and may be informative for identifying pathogenic mechanisms and therapeutic targets. To test this hypothesis while controlling for genetic background, we performed an epigenome-wide analysis of DNA methylation in genomic DNA from whole blood in three pairs of female monozygotic (MZ) twins of European ancestry, discordant for SLE. Results were replicated on the same array in four cell types from a set of four Danish female MZ twin pairs discordant for SLE. Genes implicated by the epigenetic analyses were then evaluated in 10 independent SLE gene expression datasets from the Gene Expression Omnibus (GEO). There were 59 differentially methylated loci between unaffected and affected MZ twins in whole blood, including 11 novel loci. All but two of these loci were hypomethylated in the SLE twins relative to the unaffected twins. The genes harboring these hypomethylated loci exhibited increased expression in multiple independent datasets of SLE patients. This pattern was largely consistent regardless of disease activity, cell type, or renal tissue type. The genes proximal to CpGs exhibiting differential methylation (DM) in the SLE-discordant MZ twins and exhibiting differential expression (DE) in independent SLE GEO cohorts (DM-DE genes) clustered into two pathways: the nucleic acid-sensing pathway and the type I interferon pathway. The DM-DE genes were also informatically queried for potential gene–drug interactions, yielding a list of 41 drugs including a known SLE therapy. The DM-DE genes delineate two important biologic pathways that are not only reflective of the heterogeneity of SLE but may also correlate with distinct IFN responses that depend on the source, type, and location of nucleic acid molecules and the activated receptors in individual patients. Cell- and tissue-specific analyses will be critical to the understanding of genetic factors dysregulating the nucleic acid-sensing and IFN pathways and whether these factors could be appropriate targets for therapeutic intervention.

scholarly journals Telomere length varies substantially between blood cell types in a reptile

2020 ◽  
Vol 7 (6) ◽  
pp. 192136 ◽  
Author(s):  
Mats Olsson ◽  
Nicholas J. Geraghty ◽  
Erik Wapstra ◽  
Mark Wilson
Keyword(s):  
Blood Cell ◽  
Telomere Length ◽  
Whole Blood ◽  
Phylogenetic Analyses ◽  
Natural Populations ◽  
Cell Types ◽  
Tissue Type ◽  
Telomeric Dna ◽  
Blood Cell Type ◽  
Widespread Phenomenon

Telomeres are repeat sequences of non-coding DNA-protein molecules that cap or intersperse metazoan chromosomes. Interest in telomeres has increased exponentially in recent years, to now include their ongoing dynamics and evolution within natural populations where individuals vary in telomere attributes. Phylogenetic analyses show profound differences in telomere length across non-model taxa. However, telomeres may also differ in length within individuals and between tissues. The latter becomes a potential source of error when researchers use different tissues for extracting DNA for telomere analysis and scientific inference. A commonly used tissue type for assessing telomere length is blood, a tissue that itself varies in terms of nuclear content among taxa, in particular to what degree their thrombocytes and red blood cells (RBCs) contain nuclei or not. Specifically, when RBCs lack nuclei, leucocytes become the main source of telomeric DNA. RBCs and leucocytes differ in lifespan and how long they have been exposed to ‘senescence' and erosion effects. We report on a study in which cells in whole blood from individual Australian painted dragon lizards ( Ctenophorus pictus ) were identified using flow cytometry and their telomere length simultaneously measured. Lymphocyte telomeres were on average 270% longer than RBC telomeres, and in azurophils (a reptilian monocyte), telomeres were more than 388% longer than those in RBCs. If this variation in telomere length among different blood cell types is a widespread phenomenon, and DNA for comparative telomere analyses are sourced from whole blood, evolutionary inference of telomere traits among taxa may be seriously complicated by the blood cell type comprising the main source of DNA.

scholarly journals Machine learning applied to whole-blood RNA-sequencing data uncovers distinct subsets of patients with systemic lupus erythematosus

2019 ◽  
Author(s):  
William A Figgett ◽  
Katherine Monaghan ◽  
Milica Ng ◽  
Monther Alhamdoosh ◽  
Eugene Maraskovsky ◽  
...  
Keyword(s):  
Gene Expression ◽  
Machine Learning ◽  
Systemic Lupus Erythematosus ◽  
Clinical Trials ◽  
Lupus Erythematosus ◽  
Whole Blood ◽  
Rna Seq ◽  
Systemic Lupus ◽  
Disease Heterogeneity ◽  
Healthy Donors

ABSTRACTObjectiveSystemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease that is difficult to treat. There is currently no optimal stratification of patients with SLE, and thus responses to available treatments are unpredictable. Here, we developed a new stratification scheme for patients with SLE, based on the whole-blood transcriptomes of patients with SLE.MethodsWe applied machine learning approaches to RNA-sequencing (RNA-seq) datasets to stratify patients with SLE into four distinct clusters based on their gene expression profiles. A meta-analysis on two recently published whole-blood RNA-seq datasets was carried out and an additional similar dataset of 30 patients with SLE and 29 healthy donors was contributed in this research; 141 patients with SLE and 51 healthy donors were analysed in total.ResultsExamination of SLE clusters, as opposed to unstratified SLE patients, revealed underappreciated differences in the pattern of expression of disease-related genes relative to clinical presentation. Moreover, gene signatures correlated to flare activity were successfully identified.ConclusionGiven that disease heterogeneity has confounded research studies and clinical trials, our approach addresses current unmet medical needs and provides a greater understanding of SLE heterogeneity in humans. Stratification of patients based on gene expression signatures may be a valuable strategy to harness disease heterogeneity and identify patient populations that may be at an increased risk of disease symptoms. Further, this approach can be used to understand the variability in responsiveness to therapeutics, thereby improving the design of clinical trials and advancing personalised therapy.

scholarly journals Genomic dissection of Systemic Lupus Erythematosus: Distinct Susceptibility, Activity and Severity Signatures

2018 ◽  
Author(s):  
Nikolaos I. Panousis ◽  
George Bertsias ◽  
Halit Ongen ◽  
Irini Gergianaki ◽  
Maria Tektonidou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Systemic Lupus Erythematosus ◽  
Disease Activity ◽  
Lupus Erythematosus ◽  
Whole Blood ◽  
Personalized Therapy ◽  
Flare Activity ◽  
Rna Seq ◽  
Healthy Individuals ◽  
Systemic Lupus

AbstractRecent genetic and genomics approaches have yielded novel insights in the pathogenesis of Systemic Lupus Erythematosus (SLE) but the diagnosis, monitoring and treatment still remain largely empirical1,2. We reasoned that molecular characterization of SLE by whole blood transcriptomics may facilitate early diagnosis and personalized therapy. To this end, we analyzed genotypes and RNA-seq in 142 patients and 58 matched healthy individuals to define the global transcriptional signature of SLE. By controlling for the estimated proportions of circulating immune cell types, we show that the Interferon (IFN) and p53 pathways are robustly expressed. We also report cell-specific, disease-dependent regulation of gene expression and define a core/susceptibility and a flare/activity disease expression signature, with oxidative phosphorylation, ribosome regulation and cell cycle pathways being enriched in lupus flares. Using these data, we define a novel index of disease activity/severity by combining the validated Systemic Lupus Erythematosus Disease Activity Index (SLEDAI)1 with a new variable derived from principal component analysis (PCA) of RNA-seq data. We also delineate unique signatures across disease endo-phenotypes whereby active nephritis exhibits the most extensive changes in transcriptome, including prominent drugable signatures such as granulocyte and plasmablast/plasma cell activation. The substantial differences in gene expression between SLE and healthy individuals enables the classification of disease versus healthy status with median sensitivity and specificity of 83% and 100%, respectively. We explored the genetic regulation of blood transcriptome in SLE and found 3142 cis-expression quantitative trait loci (eQTLs). By integration of SLE genome-wide association study (GWAS) signals and eQTLs from 44 tissues from the Genotype-Tissue Expression (GTEx) consortium, we demonstrate that the genetic causality of SLE arises from multiple tissues with the top causal tissue being the liver, followed by brain basal ganglia, adrenal gland and whole blood. Collectively, our study defines distinct susceptibility and activity/severity signatures in SLE that may facilitate diagnosis, monitoring, and personalized therapy.

scholarly journals Hematopoietic Lineage Transcriptome Stability and Representation in PAXgene™ Collected Peripheral Blood Utilising SPIA Single-Stranded cDNA Probes for Microarray

2008 ◽  
Vol 3 ◽  
pp. BMI.S938 ◽  
Author(s):  
Laura Kennedy ◽  
J. Keith Vass ◽  
D. Ross Haggart ◽  
Steve Moore ◽  
Michael E. Burczynski ◽  
...  
Keyword(s):  
Gene Expression ◽  
Blood Cell ◽  
Whole Blood ◽  
Peripheral Blood ◽  
Expression Profiles ◽  
Cell Types ◽  
Great Promise ◽  
Microarray Probe ◽  
Blood Samples ◽  
Transcriptional Profiles

Peripheral blood as a surrogate tissue for transcriptome profiling holds great promise for the discovery of diagnostic and prognostic disease biomarkers, particularly when target tissues of disease are not readily available. To maximize the reliability of gene expression data generated from clinical blood samples, both the sample collection and the microarray probe generation methods should be optimized to provide stabilized, reproducible and representative gene expression profiles faithfully representing the transcriptional profiles of the constituent blood cell types present in the circulation. Given the increasing innovation in this field in recent years, we investigated a combination of methodological advances in both RNA stabilisation and microarray probe generation with the goal of achieving robust, reliable and representative transcriptional profiles from whole blood. To assess the whole blood profiles, the transcriptomes of purified blood cell types were measured and compared with the global transcriptomes measured in whole blood. The results demonstrate that a combination of PAXgene™ RNA stabilising technology and single-stranded cDNA probe generation afforded by the NuGEN Ovation RNA amplification system V2™ enables an approach that yields faithful representation of specific hematopoietic cell lineage transcriptomes in whole blood without the necessity for prior sample fractionation, cell enrichment or globin reduction. Storage stability assessments of the PAXgene™ blood samples also advocate a short, fixed room temperature storage time for all PAXgene™ blood samples collected for the purposes of global transcriptional profiling in clinical studies.

scholarly journals Identification of highly active systemic lupus erythematosus by combined type I interferon and neutrophil gene scores vs classical serologic markers

Rheumatology ◽  
2020 ◽  
Vol 59 (11) ◽  
pp. 3468-3478
Author(s):  
François Chasset ◽  
Camillo Ribi ◽  
Marten Trendelenburg ◽  
Uyen Huynh-Do ◽  
Pascale Roux-Lombard ◽  
...  
Keyword(s):  
Gene Expression ◽  
Disease Activity ◽  
Lupus Erythematosus ◽  
High Disease Activity ◽  
Polymorphonuclear Neutrophil ◽  
Type I ◽  
Individual Gene ◽  
Protein Levels ◽  
Highly Active ◽  
I Gene

Abstract Objectives In SLE, heterogeneous clinical expression and activity may reflect diverse pathogenic and/or effector mechanisms. We investigated SLE heterogeneity by assessing the expression of three gene sets representative of type I IFN (IFN-I), polymorphonuclear neutrophil (PMN) and plasmablast (PB) signatures in a well-characterized, multidisciplinary cohort of SLE patients. We further assessed whether individual gene products could be representative of these three signatures. Methods Whole blood, serum and clinical data were obtained from 140 SLE individuals. Gene expression was assessed by NanoString technology, using a panel of 37 probes to compute six IFN-I, one PMN and one PB scores. Protein levels were measured by ELISA. Results Depending on the score, 45–50% of SLE individuals showed high IFN-I gene expression. All six IFN-I scores were significantly associated with active skin involvement, and two of six were associated with arthritis. IFN-induced Mx1 protein (MX1) level was correlated with IFN-I score (P < 0.0001) and associated with a similar clinical phenotype. In all, 25% of SLE individuals showed high PMN gene expression, associated with SLE fever, serositis, leukopoenia and glucocorticoid use. PB gene expression was highly affected by immunosuppressant agents, with no association with SLE features. Combined IFN-I and PMN gene scores were significantly associated with high disease activity and outperformed anti-dsDNA and anti-C1q autoantibody and complement levels for predicting SLE activity. Conclusion IFN-I and PMN gene scores segregate with distinct SLE clinical features, and their combination may identify high disease activity. MX1 protein level performed similar to IFN-I gene expression.

scholarly journals Induction of Human Liver X Receptor α Gene Expression Via an Autoregulatory Loop Mechanism

2002 ◽  
Vol 16 (3) ◽  
pp. 506-514 ◽  
Author(s):  
Yu Li ◽  
Charles Bolten ◽  
B. Ganesh Bhat ◽  
Jessica Woodring-Dietz ◽  
Suzhen Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Regulatory Element ◽  
Critical Role ◽  
Cell Types ◽  
Plasma Lipoproteins ◽  
Type I ◽  
Type Ii ◽  
Downstream Target ◽  
X Receptors

Abstract The liver X receptors (LXRs), members of the nuclear receptor superfamily, play an important role in controlling lipid homeostasis by activating several genes involved in reverse cholesterol transport. These include members of the ATP binding cassette (ABC) superfamily of transporter proteins ABCA1 and ABCG1, surface constituents of plasma lipoproteins like apolipoprotein E, and cholesterol ester transport protein. They also play an important role in fatty acid metabolism by activating the sterol regulatory element-binding protein 1c gene. Here, we identify human LXRα (hLXRα) as an autoinducible gene. Induction in response to LXR ligands is observed in multiple human cell types including macrophages and occurs within 2–4 h. Analysis of the hLXRα promoter revealed three LXR response elements (LXREs); one exhibits strong affinity for both LXRα:RXR and LXRβ:RXR (a type I LXRE), and deletion and mutational studies indicate it plays a critical role in LXR-mediated induction. The other two LXREs are identical to each other, exist within highly conserved Alu repeats, and exhibit selective binding to LXRα:RXR (type II LXREs). In transfections, the type I LXRE acts as a strong mediator of both LXRα and LXRβ activity, whereas the type II LXRE acts as a weaker and selective mediator of LXRα activity. Our data suggest a model in which LXR ligands trigger an autoregulatory loop leading to selective induction of hLXRα gene expression. This would lead to increased hLXRα levels and transcription of its downstream target genes such as ABCA1, providing a simple yet exquisite mechanism for cells to respond to LXR ligands and cholesterol loading.

scholarly journals Gene Expression: the Key to Understanding HIV-1 Infection?

2020 ◽  
Vol 84 (2) ◽  
Author(s):  
Melinda Judge ◽  
Erica Parker ◽  
Denise Naniche ◽  
Peter Le Souëf
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Host Response ◽  
Acute Infection ◽  
Cell Types ◽  
Tissue Type ◽  
Full Potential ◽  
Cell Tissue ◽  
Gene Expression Dysregulation ◽  
Living With Hiv

SUMMARY Gene expression profiling of the host response to HIV infection has promised to fill the gaps in our knowledge and provide new insights toward vaccine and cure. However, despite 20 years of research, the biggest questions remained unanswered. A literature review identified 62 studies examining gene expression dysregulation in samples from individuals living with HIV. Changes in gene expression were dependent on cell/tissue type, stage of infection, viremia, and treatment status. Some cell types, notably CD4+ T cells, exhibit upregulation of cell cycle, interferon-related, and apoptosis genes consistent with depletion. Others, including CD8+ T cells and natural killer cells, exhibit perturbed function in the absence of direct infection with HIV. Dysregulation is greatest during acute infection. Differences in study design and data reporting limit comparability of existing research and do not as yet provide a coherent overview of gene expression in HIV. This review outlines the extraordinarily complex host response to HIV and offers recommendations to realize the full potential of HIV host transcriptomics.

scholarly journals Analysis of Gene Expression from Systemic Lupus Erythematosus Synovium Reveals a Profile of Activated Immune Cells and Inflammatory Pathways

2020 ◽  
Author(s):  
Erika L. Hubbard ◽  
Michelle D. Catalina ◽  
Sarah Heuer ◽  
Prathyusha Bachali ◽  
Robert Robl ◽  
...  
Keyword(s):  
Gene Expression ◽  
Systemic Lupus Erythematosus ◽  
Immune Cells ◽  
Lupus Erythematosus ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Inflammatory Cells ◽  
Cell Types ◽  
Systemic Lupus ◽  
Common Manifestation

ABSTRACTArthritis is a common manifestation of systemic lupus erythematosus (SLE) yet understanding of the underlying pathogenic mechanisms remains incomplete. We, therefore, interrogated gene expression profiles of SLE synovium to gain insight into the nature of lupus arthritis (LA), using osteoarthritis (OA) and rheumatoid arthritis (RA) as comparators. Knee synovia from SLE, OA, and RA patients were analyzed for differentially expressed genes (DEGs) and also by Weighted Gene Co-expression Network Analysis (WGCNA) to identify modules of highly co-expressed genes. Genes upregulated and/or co-expressed in LA revealed numerous immune/inflammatory cells dominated by a myeloid phenotype, whereas OA was characteristic of fibroblasts and RA of T- and B-cells. Upstream regulator analysis identified CD40L and inflammatory cytokines as drivers of the LA gene expression profile. Genes governing trafficking of immune cells into the synovium by chemokines were identified, but not in situ generation of germinal centers. GSVA confirmed activation of specific myeloid and lymphoid cell types in LA. Numerous therapies were predicted to target LA, including TNF, NFκB, MAPK, and CDK inhibitors. Detailed gene expression analysis identified a unique pattern of cellular components and physiologic pathways operative in LA, as well as drugs potentially able to target this common manifestation of SLE.

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