Stratification of rheumatoid arthritis cohort using Ayurveda based deep phenotyping approach identifies novel genes in a GWAS

Background and aim

Genome wide association studies have scaled up both in terms of sample size and range of complex disorders investigated, but these have explained relatively little phenotypic variance. Of the several reasons, phenotypic heterogeneity seems to be a likely contributor for missing out genetic associations of large effects. Ayurveda, the traditional Indian system of medicine is one such tool which adopts a holistic deep phenotyping approach and classifies individuals based on their body constitution/prakriti. We hypothesized that Ayurveda based phenotypic stratification of healthy and diseased individuals will allow us to achieve much desired homogeneous cohorts which would facilitate detection of genetic association of large effects. In this proof of concept study, we performed a genome wide association testing of clinically diagnosed rheumatoid arthritis patients and healthy controls, who were re-phenotyped into Vata, Pitta and Kapha predominant prakriti sub-groups.

Experimental procedure

Genotypes of rheumatoid arthritis cases (Vata = 49; Pitta = 117; Kapha = 78) and controls (Vata = 33; Pitta = 175; Kapha = 85) were retrieved from the total genotype data, used in a recent genome-wide association study performed in our laboratory. A total of 528461 SNPs were included after quality control. Prakriti-wise genome-wide association analysis was employed.

Results and conclusion

This study identified (i) prakriti-specific novel disease risk genes of high effect sizes; (ii) putative candidates of novel therapeutic potential; and (iii) a good correlation between genetic findings and clinical knowledge in Ayurveda. Adopting Ayurveda based deep phenotyping may facilitate explaining hitherto undiscovered heritability in complex traits and may propel much needed progress in personalized medicine.

Monocyte-derived and M1 macrophages from ankylosing spondylitis patients released higher TNF-α and expressed more IL1B in response to BzATP than macrophages from healthy subjects

Macrophages participate in the pathogenesis of ankylosing spondylitis (AS) by producing inflammatory cytokines. Extracellular adenosine triphosphate (eATP), released during cell stress, acts through purinergic receptors (P2XR and P2YR) and induces inflammatory responses. We investigated the effect of 2ʹ(3ʹ)-O-(4-benzoyl benzoyl) ATP (BzATP) (a prototypic agonist of P2X7R) on the production of inflammatory cytokines in both monocyte-generated (M2-like) and M1 macrophages from patients and controls. Macrophages were differentiated from isolated periphery-monocytes (n = 14 in each group) by macrophage colony-stimulating factor (M-CSF). Using LPS and IFN-γ, macrophages were skewed toward M1 type and were treated with BzATP. Gene expression and protein release of IL-1β, IL-23, and TNF-α were evaluated by real-time PCR and ELISA methods respectively before and after treatment. BzATP significantly increased the protein release of TNF-α and the expression of TNFA and IL1B in monocyte-generated macrophages. Besides, BzATP treatment significantly upregulated IL1B expression, reduced TNFA and IL23A expression, and TNF-α release in M1 macrophages from both groups. Monocyte-generated and M1 macrophages from AS patients released higher TNF-α and expressed more IL1B in response to the same concentration of BzATP treatment respectively. Based on our results, AS macrophages were more sensitive to BzATP treatment and responded more intensively. Besides, the diverse effects of BzATP on monocyte-derived and M1 macrophages in our study may represent the differed inflammatory properties of these two groups of macrophages in response to eATP in the body.

P2 receptors mRNA expression profiles in macrophages from ankylosing spondylitis patients and healthy individuals

BACKGROUND

Ankylosing spondylitis (AS) is a multifactorial rheumatic disease which mainly involves the axial skeleton. Macrophages and extracellular nucleotides have been shown to contribute to the inflammation process in autoimmune diseases. Membrane-bound purinergic P2 receptors might be involved in the modulation of immune cells in AS. Therefore, we aimed to analyze the messenger RNA (mRNA) expression of P2 receptors in the macrophages of AS patients and healthy controls.

METHODS

Twenty-three AS patients and 23 age- and sex-matched healthy individuals were included in our study. Whole blood-separated monocytes of study participants were stimulated by macrophage colony-stimulating factor for 7 days and differentiated to macrophages. Monocyte and macrophage markers were analyzed by flow cytometry. SYBR green real-time polymerase chain reaction was used to measure the relative expression levels of P2RX₁ , P2RX₂ , P2RX₃ , P2RX₄ , P2RX₅ , P2RX₆ , P2RX₇ , P2RY₁ , P2RY₂ , P2RY₄ , P2RY₆ , P2RY₁₁ , P2RY₁₂ , P2RY₁₃ , P2RY₁₄ , and PANX1 genes.

RESULTS

P2RY₁₃ and P2RY₆ genes had the highest expression levels in macrophages among P2RY genes. P2RY₁ mRNA expression was significantly down-regulated (-1.75 fold) and P2RY₁₄ was up-regulated (2.6 fold) in macrophages of AS patients compared to healthy individuals. P2RX₄ gene had the highest expression in monocyte-derived macrophages, followed by P2RX₇ and P2RX₁  genes. There was no significant difference in P2X receptor mRNA expression level between macrophages of AS patients and healthy individuals.

CONCLUSIONS

Our results indicate that AS patients show altered expression levels of P2 receptor genes. Moreover, these changes might be associated with disease activity and patients' status.

Identification of Expressed miRNAs in Human Rheumatoid Arthritis Using Computational Approach - Discovery of a New miR-7167 from Human

BACKGROUND

Rheumatoid Arthritis (RA) is a chronic inflammatory and autoimmune disease leading to bones and joints destruction. It is one of the major causes of lifetime disability and mortality among humans in the developing and developed countries. It was evident that epigenetic dysregulation is related to the pathogenesis of RA. MicroRNAs (miRNAs) are small non-coding RNAs that are epigenetic regulators for diverse biological processes and also provided novel molecular insights in the formation of arthritis.

OBJECTIVE

The influences of miRNAs in the alteration of gene regulation during the pathogenesis of arthritis were exposed in recent years.

METHOD

The computational approach to identify miRNA through EST-based homology is more powerful, economical and time-efficient. In this study, we applied EST-based homology search to identify miRNAs responsible for the development of arthritis in human beings.

RESULTS

Our study on 36519 ESTs in human RA condition revealed the expression of four miRNAs, HSA-miR-198, HSA-miR-4647, has-miR-7167-5p and has-miR-7167-3p. The present study is the first report about has-miR-7167 that was homologous to Macaca mulatta.

CONCLUSION

The predicted targets of these identified miRNAs revealed many biological functions in the pathogenesis of RA. Further elaborated studies on these miRNAs will help to understand their function in the development of RA and the use of miRNAs as therapeutic targets in the future.

Identification of pathways significantly associated with spondyloarthropathy/ankylosing spondylitis using the sub‑pathway method

The aim of the present study was to extract potential sub-pathway biomarkers for spondyloarthropathy (SpA)/ankylosing spondylitis (AS) using a sub-pathway strategy. SpA/AS-relevant data, reference pathways and long non-coding (lnc)RNA-micro (mi)RNA-mRNA interactions were downloaded. The seed pathways based on Kyoto Encyclopedia of Genes and Genomes pathways and the mRNAs in the co-expressed lncRNA-mRNA interactions were extracted. Sub-pathways regulated by lncRNA were selected after establishing condition-specific lncRNA competitively regulated pathways (LCRP) network. Significant sub-pathways were further identified using the attract method. These significant sub-pathways were evaluated in the other independent published AS microarray data (E-GEOD-25101) using in silico validation. In addition, to uncover SpA/AS-relevant lncRNAs, the degree analysis for all nodes in the LCRP network was conducted. A total of 35 lncRNAs, 131 mRNAs and 145 co-expressed interactions were identified. When entering these 131 mRNAs into the reference pathways, 82 seed pathways were extracted, which were transformed into undirected graphs, and the 35 lncRNAs were mapped to the pathway graphs to further establish the condition-specific LCRP network. Based on degree analysis, four hub lncRNAs were selected, including C14orf169, LINC00242, LINC00116 and LINC00482. It was identified that 35 lncRNAs competitively regulating sub-pathways were involved in 56 complete pathways. Among these, the top three sub-pathways were path: 04010_1, which was a subregion of the mitogen-activated protein kinase (MAPK) signaling pathway; path: 04062-1, an important subregion in the chemokine signaling pathway; and path: 04066_2, was a part of HIF-1 signaling pathway. Furthermore, it was validated consistently in the separate microarray data set E-GEOD-25101. Cancer-associated pathways and hub node C14orf169 were identified in validation. Sub-pathways, including the MAPK signaling pathway and chemokine signaling pathway, and hub lncRNA (C14orf169) may serve important roles in SpA/AS.

Identification of potential target genes for ankylosing spondylitis treatment

This study aimed to identify the potential target genes for the treatment of ankylosing spondylitis (AS).Dataset GSE25101 was downloaded from Gene Expression Omnibus, including 16 AS and 16 normal control blood samples. Differentially expressed genes (DEGs) were identified using unmatched t-test in limma package with adjusted P < .05. Gene ontology-biological process (GO-BP) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted using multifaceted analysis tool for human transcriptome. Protein-protein interaction (PPI) network was constructed using STRING and Cytoscape, and module analysis was performed using MCODE plug-in. Webgestal was utilized to predict transcriptional factor (TF)-microRNA-target network and Comparative Toxicogenomics Database (CTD) was applied to predict chemical-target network.A total of 334 DEGs were identified, including 136 upregulated genes and 198 downregulated genes. According to STRING, a PPI network was constructed and 1 significant clustered module was screen out with score = 6.33. MAPK7 (degree = 11) and NDUFS4 (degree = 10) were 2 important nodes in PPI network, and both of them were significantly enriched in cAMP mediated signaling pathway (P = 2.02E-02). MAPK7 could be regulated by NFY. Both MAPK7 and NDUFS4 were 2 potential targets for Indomethacin.MAPK7 and NDUFS4 played important roles in the pathogenesis of AS via cAMP mediated signaling pathway. Both of them could be targeted by Indomethacin.