Gene expression patterns in peripheral blood cells associated with radiographic severity in African Americans with early rheumatoid arthritis

Whole-transcriptome sequencing identifies key differentially expressed circRNAs/lncRNAs/miRNAs/mRNAs and linked ceRNA networks in adult degenerative scoliosis

Background

Adult degenerative scoliosis (ADS) is forecast to be a prevalent disabling condition in an aging society. Universally, its pathogenesis is perceived as intervertebral disc degeneration (IDD), however, a thought-provoking issue is why precisely a subset of patients with disc degeneration develop ADS. Exploring the diversities between common IDD and ADS would contribute to unraveling the etiological mechanisms of ADS. Therefore, we aimed to integrate the circRNA, lncRNA, miRNA, and mRNA expression profiles from normal adults (Normal), patients with lumbar disc herniation (LDH), and ADS by whole transcriptome sequencing, which identifies critical functional ncRNA and ceRNA networks and crosstalk between the various transcripts.

Methods

The fresh whole blood samples (n = 3/group) were collected from ADS patients, LDH patients, and healthy volunteers (Normal group), which were examined for mRNA, miRNA, lncRNA, and circRNA expression and screened for differentially expressed (DE) ncRNAs. Then, Gene Ontology (GO) and KEGG analyses were performed for gene annotation and enrichment pathways on the DE RNAs, which were constructed as a lncRNA-miRNA-mRNA network. Eventually, DE RNAs were validated by qRT-PCR targeting disc nucleus pulposus (NP) tissue in ADS and LDH group (n = 10/group).

Results

Compared to the LDH group, we identified 3322 DE mRNAs, 221 DE lncRNAs, 20 DE miRNAs, and 15 DE circRNAs in the ADS. In contrast to Normal, 21 miRNAs and 19 circRNAs were differentially expressed in the ADS. The expression of multiple differentially expressed ncRNAs was confirmed by qRT-PCR analysis to be consistent with the sequencing results. In addition, GO, and KEGG analysis demonstrated that most DE mRNAs and ncRNAs target genes are involved in various biological processes, including Endocytosis, Apoptosis, Rap1 signaling pathway, Notch signaling pathway, and others. The constructed lncRNA-miRNA-mRNA co-expression network was primarily related to angiogenesis and regulation.

Conclusion

By focusing on comparing asymmetric and symmetric disc degeneration, whole-transcriptome sequencing and bioinformatics analysis systematically screened for key ncRNAs in the development of ADS, which provided an abundance of valuable candidates for the elucidation of regulatory mechanisms. The DE ncRNAs and the lncRNA-miRNA-mRNA network are intrinsically involved in the regulation of mediator and angiogenesis, which may contribute to the insight into the pathogenesis of ADS.

Whole blood transcriptomic profiles can differentiate vulnerability to chronic low back pain

The mechanisms underlying the transition from acute to chronic pain remain unclear. Here, we sought to characterize the transcriptome associated with chronic low back pain as well as the transcriptome of the transition from acute to chronic low back pain. For the analysis, we compared the whole blood transcriptome of: (a) patients at the onset of low back pain who no longer had pain within 6 weeks after onset (acute) with patients who developed chronic low back pain at 6 months (chronic T5); and, (b) patients at the onset of low back pain (chronic T1) who developed chronic pain at 6 months with healthy pain-free (normal) controls. The majority of differentially expressed genes were protein coding. We illustrate a unique chronic low back pain transcriptome characterized by significant enrichment for known pain genes, extracellular matrix genes, and genes from the extended major histocompatibility complex (MHC) genomic locus. The transcriptome of the transition from acute to chronic low back pain was characterized by significant upregulation of antigen presentation pathway (MHC class I and II) genes and downregulation of mitochondrial genes associated with oxidative phosphorylation, suggesting a unique genomic signature of vulnerability to low back pain chronicity.

[Upcoming value of gene expression analysis in rheumatology]

Rheumatoid arthritis (RA) is a chronic inflammatory disease of unknown etiology, which involves disturbance in immune system signaling pathway functions, damage of other tissues, pain and joint destruction. Modern treatment attempts to improve pathophysiological and biochemical mechanisms damaged by the disease. However, due to the RA patient heterogeneity personalized approach to treatment is required; the choice of personalized treatment is complicated by the variability of patient's response to treatment. Gene expression analysis might serve a tool for the disease control and therapy personification for inhibition of inflammation and pain as well as for prevention of joint destruction.

The clinical utility of gene expression examination in rheumatology

Rheumatoid arthritis (RA) is a chronic inflammatory disease with unknown etiology that affects various pathways within the immune system, involves many other tissues and is associated with pain and joint destruction. Current treatments fail to address pathophysiological and biochemical mechanisms involved in joint degeneration and the induction of pain. Moreover, RA patients are extremely heterogeneous and require specific treatments, the choice of which is complicated by the fact that not all patients equally respond to therapy. Gene expression analysis offer tools for patient management and personalization of patient’s care to meet individual needs in controlling inflammation and pain and delaying joint destruction.

Expression of Interferon-γ Receptor Genes in Peripheral Blood Mononuclear Cells Is Associated With Rheumatoid Arthritis and Its Radiographic Severity in African Americans

OBJECTIVE

The factors responsible for radiographic severity in African American patients with rheumatoid arthritis (RA) are poorly understood. We sought to identify genes whose expression in peripheral blood mononuclear cells is associated with radiographic severity in RA.

METHODS

In the first phase of the study, we performed real-time quantitative polymerase chain reaction to analyze the expression of 182 candidate genes in 40 African American RA patients with extremes of radiographic damage (low versus high radiographic scores) and disease duration (≤2 years versus >2 years) and 20 healthy African American control subjects; the genes were selected based on plausible immune pathways. In the second phase, we analyzed the expression of the genes that were shown to be significantly associated with radiographic scores in 576 African American patients with RA and 51 African American control subjects who had not been studied previously, accounting for autoantibody status and disease duration.

RESULTS

We observed significant differences in IFNGR1 expression between patients with RA and control subjects (adjusted P [P(adj)] = 6 × 10(-14)) and in IFNGR2 expression between RA patients with erosions and those with no erosions (P(adj) = 0.01 by Wilcoxon's rank sum test). We also observed significant correlations between IFNGR2 expression and radiographic scores (P(adj) = 0.03 for erosions, P(adj) = 0.04 for joint space narrowing, and P(adj) = 0.03 for total radiographic score [zero-inflated negative binomial regression model]) and annualized progression rate (P(adj) = 0.0024 by Spearman's correlation analysis).

CONCLUSION

These findings have important implications with respect to the role of interferon-γ (IFNγ) in the pathogenesis of RA and may lead to identification of a biomarker for radiographic damage. Additional studies are needed to define the cell subsets responsible for the association of IFNγ receptor gene expression with radiographic findings, which downstream mechanisms are involved, and generalizability to other RA populations.

Simple regression for correcting ΔCt bias in RT-qPCR low-density array data normalization

BACKGROUND

Reverse transcription quantitative PCR (RT-qPCR) is considered the gold standard for quantifying relative gene expression. Normalization of RT-qPCR data is commonly achieved by subtracting the Ct values of the internal reference genes from the Ct values of the target genes to obtain ΔCt. ΔCt values are then used to derive ΔΔCt when compared to a control group or to conduct further statistical analysis.

RESULTS

We examined two rheumatoid arthritis RT-qPCR low density array datasets and found that this normalization method introduces substantial bias due to differences in PCR amplification efficiency among genes. This bias results in undesirable correlations between target genes and reference genes, which affect the estimation of fold changes and the tests for differentially expressed genes. Similar biases were also found in multiple public mRNA and miRNA RT-qPCR array datasets we analysed. We propose to regress the Ct values of the target genes onto those of the reference genes to obtain regression coefficients, which are then used to adjust the reference gene Ct values before calculating ΔCt.

CONCLUSIONS

The per-gene regression method effectively removes the ΔCt bias. This method can be applied to both low density RT-qPCR arrays and individual RT-qPCR assays.

Gene expression analysis in RA: towards personalized medicine

Gene expression has recently been at the forefront of advance in personalized medicine, notably in the field of cancer and transplantation, providing a rational for a similar approach in rheumatoid arthritis (RA). RA is a prototypic inflammatory autoimmune disease with a poorly understood etiopathogenesis. Inflammation is the main feature of RA; however, many biological processes are involved at different stages of the disease. Gene expression signatures offer management tools to meet the current needs for personalization of RA patients' care. This review analyses currently available information with respect to RA diagnostic, prognostic and prediction of response to therapy with a view to highlight the abundance of data, whose comparison is often inconclusive due to the mixed use of material source, experimental methodologies and analysis tools, reinforcing the need for harmonization if gene expression signatures are to become a useful clinical tool in personalized medicine for RA patients.