Microarray to deep sequencing: transcriptome and miRNA profiling to elucidate molecular pathways in systemic lupus erythematosus

Comparative Analysis of Shapley Values Enhances Transcriptomics Insights across Some Common Uterine Pathologies

Uterine pathologies pose a challenge to women's health on a global scale. Despite extensive research, the causes and origin of some of these common disorders are not well defined yet. This study presents a comprehensive analysis of transcriptome data from diverse datasets encompassing relevant uterine pathologies such as endometriosis, endometrial cancer and uterine leiomyomas. Leveraging the Comparative Analysis of Shapley values (CASh) technique, we demonstrate its efficacy in improving the outcomes of the classical differential expression analysis on transcriptomic data derived from microarray experiments. CASh integrates the microarray game algorithm with Bootstrap resampling, offering a robust statistical framework to mitigate the impact of potential outliers in the expression data. Our findings unveil novel insights into the molecular signatures underlying these gynecological disorders, highlighting CASh as a valuable tool for enhancing the precision of transcriptomics analyses in complex biological contexts. This research contributes to a deeper understanding of gene expression patterns and potential biomarkers associated with these pathologies, offering implications for future diagnostic and therapeutic strategies.

Analysis, validation, and discussion of key genes in placenta of patients with gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is a common complication during pregnancy, which can have harmful health consequences for both the mother and the fetus. Given the placenta's crucial role as an endocrine organ during pregnancy, exploring and validating key genes in the placenta hold significant potential in the realm of GDM prevention and treatment. In this study, differentially expressed genes (DEGs) were identified from two databases, GSE70493 and PRJNA646212, and verified by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) in placenta tissues. DEGs expression was detected in normal or high-glucose-treated HTR8/SVneo cells. We also investigated the relationship between DEGs and glucose levels in GDM patients. By selecting the intersection of the two databases, we screened 20 DEGs, which were validated in GDM patients. We observed an up-regulation of SLAMF, ALDH1A2, and CHI3L2, and a down-regulation of HLA-E, MYH11, HLA-DRB5, ITGAX, GZMB, NAIP, TMEM74B, RANBP3L, PAEP, WT-1, and CEP170. We conducted further investigations into the expression of DEGs in HTR8/SVneo cells exposed to high glucose, revealing a significant upregulation in the expression of SERPINA3, while the expressions of HLA-E, BCL6, NAIP, PAEP, MUC16, WT-1, and CEP170 were decreased. Moreover, some DEGs were confirmed to have a positive or negative correlation with blood glucose levels of GDM patients through correlation analysis. The identified DEGs are anticipated to exert potential implications in the prevention and management of GDM, thereby offering potential benefits for improving pregnancy outcomes and long-term prognosis of fetuses among individuals affected by GDM.

Sequencing technology as a major impetus in the advancement of studies into rheumatism: A bibliometric study

Background

Rheumatism covers a wide range of diseases with complex clinical manifestations and places a tremendous burden on humans. For many years, our understanding of rheumatism was seriously hindered by technology constraints. However, the increasing application and rapid advancement of sequencing technology in the past decades have enabled us to study rheumatism with greater accuracy and in more depth. Sequencing technology has made huge contributions to the field and is now an indispensable component and powerful tool in the study of rheumatism.

Methods

Articles on sequencing and rheumatism, published from 1 January 2000 to 25 April 2022, were retrieved from the Web of Science™ (Clarivate™, Philadelphia, PA, USA) database. Bibliometrix, the open-source tool, was used for the analysis of publication years, countries, authors, sources, citations, keywords, and co-words.

Results

The 1,374 articles retrieved came from 62 countries and 350 institutions, with a general increase in article numbers during the last 22 years. The leading countries in terms of publication numbers and active cooperation with other countries were the USA and China. The most prolific authors and most popular documents were identified to establish the historiography of the field. Popular and emerging research topics were assessed by keywords and co-occurrence analysis. Immunological and pathological process in rheumatism, classification, risks and susceptibility, and biomarkers for diagnosis were among the hottest themes for research.

Conclusions

Sequencing technology has been widely applied in the study of rheumatism and propells research in the area of discovering novel biomarkers, related gene patterns and physiopathology. We suggest that further efforts be made to advance the study of genetic patterns related to rheumatic susceptibility, pathogenesis, classification and disease activity, and novel biomarkers.

Drug Repositioning Identifies Six Drug Candidates for Systemic Autoimmune Diseases by Integrative Analyses of Transcriptomes from Scleroderma, Systemic Lupus Erythematosus, and Sjogren's Syndrome

The mechanisms of systemic autoimmune diseases (ADs) are still not clearly understood. Understanding the etiology of systemic ADs and identifying new therapeutic targets require a systems science approach. Using publicly available transcriptome data and bioinformatic analysis, we investigated the differential gene expression profiles of patients with scleroderma, systemic lupus erythematosus, and Sjogren's syndrome. Of these common differentially expressed gene signatures, 208 were regulated in the same direction (either upregulated or downregulated in all datasets) and used for drug repositioning. Six small molecule drug candidates (KU-0063794, YM-155 [sepantronium bromide], MST-312 [telomerase inhibitor IX], PLX-4720, ZM 336372, and 528116.cdx [PIK-75]) were discovered by drug repositioning as potential therapeutics for systemic ADs. The Search Tool for Chemical Interactions was used to find the anticipated target genes of the repositioned molecules. The PI3K/AKT pathway topped the list of common enriched pathways with the most anticipated target genes of the six repositioned small molecules. We also report here the molecular docking findings on the binding affinity between the repositioned drug candidates and genes from the protein-protein interaction network modules of anticipated target genes. Taken together, this study provides new insights and opens up new possibilities on both pathogenesis and treatment of systemic ADs through drug repositioning.

Vitamin D supplementation in systemic lupus erythematosus: relationship to disease activity, fatigue and the interferon signature gene expression

Background

In addition to the well-known role of vitamin D in calcium homeostasis and bone metabolism, vitamin D is important in the modulation of the immune system and inflammatory processes. Vitamin D deficiency is common in patients with systemic lupus erythematosus (SLE), possibly as a result of sun avoidance. The aim of this prospective open-label study was to assess the effect of the treatment of vitamin D deficiency and insufficiency in SLE patients, particularly with regards to disease activity, fatigue and interferon signature gene expression.

Methods

31 SLE patients, 13 with vitamin D deficiency and 18 with vitamin D insufficiency were treated with vitamin D3. They were supplemented with vitamin D3 8000 IU daily for 8 weeks if they were vitamin D deficient, or 8000 IU daily for 4 weeks if they were insufficient. This was followed by 2000 IU daily maintenance. They were assessed at baseline, after 6 and 12 months by means of an interview, filling in questionnaires and blood tests. The expression of 12 interferon signature genes in RNA extracted from whole blood was measured by using QuantiGene Plex technology.

Results

An improvement in disease activity measured by systemic lupus erythematosus disease activity index-2K (SLEDAI-2K; p = 0.028) and fatigue measured by fatigue severity scale (FSS; p = 0.071) at 12 months were noted. A significant decrease in anti-double stranded deoxyribonucleic acid (dsDNA) titre (p = 0.045) was also noted. The mean interferon signature gene expression score decreased from baseline to 6 months, however statistical significance was not achieved (p = 0.165).

Conclusions

Improved disease activity and fatigue have been noted when Vitamin D has been supplemented in vitamin D deficient/insufficient SLE patients. One possible mechanism could be the suppression of the interferon signature gene expression.

Trial registration: The study was registered with the ISRCTN registry on 12/04/2021 (Trial ID: ISRCTN59058825).

Current status of use of high throughput nucleotide sequencing in rheumatology

OBJECTIVE

Here, we assess the usage of high throughput sequencing (HTS) in rheumatic research and the availability of public HTS data of rheumatic samples.

METHODS

We performed a semiautomated literature review on PubMed, consisting of an R-script and manual curation as well as a manual search on the Sequence Read Archive for public available HTS data.

RESULTS

Of the 699 identified articles, rheumatoid arthritis (n=182 publications, 26%), systemic lupus erythematous (n=161, 23%) and osteoarthritis (n=152, 22%) are among the rheumatic diseases with the most reported use of HTS assays. The most represented assay is RNA-Seq (n=457, 65%) for the identification of biomarkers in blood or synovial tissue. We also find, that the quality of accompanying clinical characterisation of the sequenced patients differs dramatically and we propose a minimal set of clinical data necessary to accompany rheumatological-relevant HTS data.

CONCLUSION

HTS allows the analysis of a broad spectrum of molecular features in many samples at the same time. It offers enormous potential in novel personalised diagnosis and treatment strategies for patients with rheumatic diseases. Being established in cancer research and in the field of Mendelian diseases, rheumatic diseases are about to become the third disease domain for HTS, especially the RNA-Seq assay. However, we need to start a discussion about reporting of clinical characterisation accompany rheumatological-relevant HTS data to make clinical meaningful use of this data.

Identification of potential biomarkers associated with immune infiltration in the esophageal carcinoma tumor microenvironment

Tumor immune cell infiltration was significantly correlated with the progression and the effect of immunotherapy in cancers including esophageal carcinoma (ESCA). However, no biomarkers were identified which were associated with immune infiltration in ESCA. In the present study, a total of 128 common differentially expressed genes (DEGs) were identified between esophageal squamous cell carcinomas (ESCC) and esophageal adenocarcinomas (EAC). The results of gene ontology (GO) enrichment and Reactome pathway analysis displayed that the up-regulated DEGs were mainly involved in the regulation of extracellular matrix (ECM), while the down-regulated DEGs were mainly involved in the regulation of cornification and keratinocyte differentiation. The most significant module of up-regulated DEGs was selected by Molecular Complex Detection (MCODE). Top ten similar genes of COL1A2 were explored, then validation and the prognostic analysis of these genes displayed that COL1A2, COL1A1, COL3A1, ZNF469 and Periostin (POSTN) had the prognostic value which were up-regulated in ESCA. The expressions of COL1A2 and its four similar genes were mainly correlated with infiltrating levels of macrophages and dendritic cells (DCs) and showed strong correlations with diverse immune marker sets in ESCA. To summarize, COL1A2 and its four similar genes were identified as the potential biomarkers associated with immune infiltration in ESCA. These genes might be applied to immunotherapy for ESCA.

Kidney Tertiary Lymphoid Structures in Lupus Nephritis Develop into Large Interconnected Networks and Resemble Lymph Nodes in Gene Signature

Immune aggregates organized as tertiary lymphoid structures (TLS) are observed within the kidneys of patients with systemic lupus erythematosus and lupus nephritis (LN). Renal TLS was characterized in lupus-prone New Zealand black × New Zealand white F1 mice analyzing cell composition and vessel formation. RNA sequencing was performed on transcriptomes isolated from lymph nodes, macrodissected TLS from kidneys, and total kidneys of mice at different disease stages by using a personal genome machine and RNA sequencing. Formation of TLS was found in anti-double-stranded DNA antibody-positive mice, and the structures were organized as interconnected large networks with distinct T/B cell zones with adjacent dendritic cells, macrophages, plasma cells, high endothelial venules, supporting follicular dendritic cells network, and functional germinal centers. Comparison of gene profiles of whole kidney, renal TLS, and lymph nodes revealed a similar gene signature of TLS and lymph nodes. The up-regulated genes within the kidneys of lupus-prone mice during LN development reflected TLS formation, whereas the down-regulated genes were involved in metabolic processes of the kidney cells. A comparison with human LN gene expression revealed similar up-regulated genes as observed during the development of murine LN and TLS. In conclusion, kidney TLS have a similar cell composition, structure, and gene signature as lymph nodes and therefore may function as a kidney-specific type of lymph node.

Discovering the signature of a lupus-related microRNA profile in the Gene Expression Omnibus repository

Lupus is one of the most prevalent systemic autoimmune diseases. It is a multifactorial disease in which genetic, epigenetic and environmental factors play significant roles. The pathogenesis of lupus is not yet well understood. However, deregulation of microRNAs (miRNAs) - one of the post-transcriptional regulators of genes - can contribute to the development of autoimmune diseases. Over the last two decades, advances in the profiling of miRNA using microarray have received much attention, and it has been demonstrated that miRNAs play a regulatory role in the pathogenesis of lupus. Therefore, dysregulated miRNAs can be considered as promising diagnostic biomarkers for lupus. This article is an overview of lupus-related miRNA profiling studies and arrays in the Gene Expression Omnibus (GEO) database. The aims of our study were to widen current knowledge of known dysregulated miRNAs as potential biomarkers of SLE and to introduce a bioinformatics approach to using microarray data and finding novel miRNA and gene candidates for further study. We identified hsa-miR-4709-5p, hsa-miR-140, hsa-miR-145, hsa-miR-659, hsa-miR-134, hsa-miR-150, hsa-miR-584, hsa-miR-409 and hsa-miR-152 as potential biomarkers by integrated bioinformatics analysis.

Personalized therapy design for systemic lupus erythematosus based on the analysis of protein-protein interaction networks

We analyzed protein expression data for Lupus patients, which have been obtained from publicly available databases. A combination of systems biology and statistical thermodynamics approaches was used to extract topological properties of the associated protein-protein interaction networks for each of the 291 patients whose samples were used to provide the molecular data. We have concluded that among the many proteins that appear to play critical roles in this pathology, most of them are either ribosomal proteins, ubiquitination pathway proteins or heat shock proteins. We propose some of the proteins identified in this study to be considered for drug targeting.

Correlation of microRNA expression profile with clinical response to tumor necrosis factor inhibitor in treating rheumatoid arthritis patients: A prospective cohort study

Background

This study aimed to explore the correlation of circulating microRNA (miRNA) expression profile with clinical response to tumor necrosis factor (TNF) inhibitor in treating rheumatoid arthritis (RA) patients.

Methods

Baseline PBMC samples from eight responders and eight non‐responders after 24‐week TNF inhibitor (etanercept) treatment were subjected to miRNA microarray. Then, top 10 dysregulated miRNAs were selected and further validated by quantitative polymerase chain reaction (qPCR) in baseline PBMC samples from 92 RA patients treated with 24‐week TNF inhibitor (etanercept). Responders and non‐responders were divided referring to the decline in disease activity score in 28 joints.

Results

In microarray assay, total 59 upregulated and 78 downregulated miRNAs were identified in responders compared to non‐responders, which were mainly enriched in regulating immune‐ and inflammation‐related biological processes and pathways. The top 10 dysregulated miRNAs were as follows: miR‐192‐5p, miR‐146a‐5p, miR‐19b‐3p, miR‐320c, miR‐335‐5p, miR‐149‐3p, miR‐766‐3p, let‐7a‐5p, miR‐24‐3p, and miR‐1226‐5p. In qPCR validation, miR‐146a‐5p was increased, while let‐7a‐5p was decreased in responders compared with non‐responders. Multivariate logistic analysis illuminated that miR‐146a‐5p and CRP independently correlated with higher clinical response, while let‐7a‐5p and biologics history independently associated with lower clinical response. Subsequently, receiver operating characteristic curve showed that combination of these four independent factors presented with a great predictive value for clinical response with area under curve: 0.863, 95% CI 0.781‐0.945.

Conclusion

miRNA expression profile is closely implicated in the treatment efficacy of TNF inhibitor, and combined measurement of miR‐146a‐5p, let‐7a‐5p, CRP, and biologics history disclosed a great predictive value for clinical response to TNF inhibitor in RA patients.

Bioinformatics analysis of microRNA expression between patients with and without latent tuberculosis infections

Tuberculosis (TB) is a globally prevalent infectious disease. The mechanisms of latent TB infection (LTBI) remain to be fully elucidated and may provide novel approaches for diagnosis. As therapeutic targets and molecular diagnostic markers, microRNAs (miRs) have been studied and utilized in various diseases. In the present study, the differentially expressed miRs (DEMs) in LTBI were screened and analyzed to determine the underlying mechanisms and identify potential biomarkers, thereby contributing to the diagnosis of LTBI. The GSE25435 and GSE29190 datasets from Gene Expression Omnibus were selected for analysis. The 2 datasets were analyzed individually using the Bioconductor package to screen the DEMs with specific cut-off criteria [P<0.01 and |log (fold change)|≥1]. Target gene prediction and interaction network construction were performed using Targetscan, the Search Tool for the Retrieval of Interacting Genes and Proteins and Cytoscape individually, and were merged using the latter tool. The hub genes were finally selected based on their degree of connectivity (DC). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using the KEGG and GENCLIP. A total of 144 DEMs were identified from the 2 datasets. By exploring the overlapping miRs in the two datasets, Homo sapiens (hsa)-miR-29a and hsa-miR-15b were identified to be decreased, while hsa-miR-576-5p, hsa-miR-500 and hsa-miR-155 were identified to be upregulated. hsa-miR-500a-3p and hsa-miR-29a-3p, as well as 4 genes, namely cell division cycle (CDC)42, actin α1, skeletal muscle (ACTA1), phosphatase and tensin homolog (PTEN) and fos proto-oncogene (FOS), were selected as the key factors in this regulatory network. A total of 9 signaling pathways, including phosphoinositide-3 kinase (PI3K)/AKT and 11 biological processes, were identified to be associated with LTBI. In conclusion, the present analysis identified hsa-miR-500a-3p and hsa-miR-29a-3p, as well as CDC42, ACTA1, PTEN and FOS, as the most promising biomarkers and therapeutic candidates for LTBI. The PI3K/AKT signaling pathway is the key signaling pathway implicated in LTBI, and an in-depth investigation of the efficiency of PI3K/AKT signaling inhibitors may be used to prevent a chronic state of infection in LTBI.

Differential expression profiles and functional analysis of plasma miRNAs associated with chronic myeloid leukemia phases

Aim: This study was aimed to investigate the expression profiles and biological function of plasma miRNAs at different phases of chronic myeloid leukemia (CML). Materials & methods: Differentially expressed miRNAs were identified by microarray. The candidate miRNAs were validated by quantitative real-time PCR at chronic phase, accelerated phase and blast crisis. The functional analysis of miRNAs was carried out by using DAVID. Results: The putative targets of dysregulated miRNAs were involved in important signaling pathways. Plasma let-7b-5p and miR-451a expression was lower in CML patients, and plasma miR-451a gradually decreased from chronic phase to accelerated phase and blast crisis. Conclusion: Dysregulated plasma miRNAs maybe play regulatory roles in pathogenesis of CML. Let-7b-5p and miR-451a can be used as potential biomarkers for the diagnosis and prognosis of CML.

Differential microRNA expression profiles in tamoxifen-resistant human breast cancer cell lines induced by two methods

Tamoxifen (TAM) resistance has become a severe problem for endocrine therapy of breast cancer. The present study investigated the association between microRNA (miRNA) expression and TAM resistance in breast cancer. The TAM-resistant breast cancer MCF-7C and MCF-7T cell lines were established using the human breast cancer cell line MCF-7 as the parental cell line and 4-hydroxytamoxifen (OHT) as the screening drug in vitro. The MCF-7C cell line was established by dose stepwise induction beginning with a low concentration of OHT; the MCF-7T cell line was established by temporal stepwise induction beginning with a high concentration of OHT. Differential miRNA expression profiles between TAM-sensitive (MCF-7) and TAM-resistant (MCF-7C and MCF-7T) breast cancer cell lines were detected and analyzed using RNA sequencing technology. The results of western blot analysis indicated that the level of ERα protein expression in drug-resistant cells was significantly increased. A total of 1,646 miRNAs were detected in all samples, including 1,376 known miRNAs and 270 predicted miRNAs. There were 118 miRNAs expressed at significantly different levels between MCF-7C and MCF-7 cells (P<0.05); among them, 67 miRNAs were upregulated (P<0.05) and 51 miRNA were downregulated (P<0.05). There were 42 miRNAs expressed at significantly different levels between MCF-7T and MCF-7 (P<0.05); among them, 23 miRNAs were upregulated (P<0.05) and 19 miRNAs were downregulated (P<0.05). There were 126 miRNAs with significant differences between MCF-7C and MCF-7T (P<0.05); among them, 76 miRNAs were upregulated (P<0.05) and 50 miRNAs were downregulated. On the basis of the results of the present study, we hypothesize that miR-21, miR-146a, miR-148a, miR-34a and miR-27a may serve important roles in mediating TAM resistance in breast cancer, and have potential as therapeutic targets for TAM-resistant breast cancer.

The effect of vitamin D on disease activity, fatigue and interferon signature gene expression in systemic lupus erythematosus

Systemic Lupus Erythematosus (SLE) is multi-system autoimmune disorder, whose pathogenesis involves several cascades that lead to the production of interferon alpha, which then mediates the manifestations of the disease. In SLE, the overexpression of interferon regulated genes, produce a unique interferon signature. This has a positive correlation with disease activity. Vitamin D deficiency is highly prevalent in SLE; the role of vitamin D in the course and prognosis of SLE is unknown. Vitamin D deficiency has been associated with a higher disease activity in SLE. Fatigue is also highly prevalent in SLE; its aetiology is multi-factorial. There is limited evidence on the relationship between vitamin D, fatigue and interferon signature gene expression. Further studies on this will establish whether treatment of vitamin D deficiency in SLE, has any significant effect on the level of fatigue and disease activity, and whether this could be due to the suppression of interferon signature gene expression.

Diagnostic and prognostic tests in systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a chronic autoimmune inflammatory disease characterized by autoantibodies directed against numerous self-nuclear antigens. Because of the heterogeneous nature of lupus, it has been challenging to identify markers that are sensitive and specific enough for its diagnosis and monitoring. However, with the sequencing of the human genome, rapid development of high-throughput approaches has allowed for a better understanding of the etiopathogenesis of complex diseases, including SLE. Here we present a review of the latest advancements in biomarker discovery during the "omics" era, using these novel technologies, for assisting in the diagnosis and prognosis of patients with SLE.

RNA-seq Analysis Reveals Unique Transcriptome Signatures in Systemic Lupus Erythematosus Patients with Distinct Autoantibody Specificities

Systemic lupus erythematosus (SLE) patients exhibit immense heterogeneity which is challenging from the diagnostic perspective. Emerging high throughput sequencing technologies have been proved to be a useful platform to understand the complex and dynamic disease processes. SLE patients categorised based on autoantibody specificities are reported to have differential immuno-regulatory mechanisms. Therefore, we performed RNA-seq analysis to identify transcriptomics of SLE patients with distinguished autoantibody specificities. The SLE patients were segregated into three subsets based on the type of autoantibodies present in their sera (anti-dsDNA+ group with anti-dsDNA autoantibody alone; anti-ENA+ group having autoantibodies against extractable nuclear antigens (ENA) only, and anti-dsDNA+ENA+ group having autoantibodies to both dsDNA and ENA). Global transcriptome profiling for each SLE patients subsets was performed using Illumina® Hiseq-2000 platform. The biological relevance of dysregulated transcripts in each SLE subsets was assessed by ingenuity pathway analysis (IPA) software. We observed that dysregulation in the transcriptome expression pattern was clearly distinct in each SLE patients subsets. IPA analysis of transcripts uniquely expressed in different SLE groups revealed specific biological pathways to be affected in each SLE subsets. Multiple cytokine signaling pathways were specifically dysregulated in anti-dsDNA+ patients whereas Interferon signaling was predominantly dysregulated in anti-ENA+ patients. In anti-dsDNA+ENA+ patients regulation of actin based motility by Rho pathway was significantly affected. The granulocyte gene signature was a common feature to all SLE subsets; however, anti-dsDNA+ group showed relatively predominant expression of these genes. Dysregulation of Plasma cell related transcripts were higher in anti-dsDNA+ and anti-ENA+ patients as compared to anti-dsDNA+ ENA+. Association of specific canonical pathways with the uniquely expressed transcripts in each SLE subgroup indicates that specific immunological disease mechanisms are operative in distinct SLE patients' subsets. This 'sub-grouping' approach could further be useful for clinical evaluation of SLE patients and devising targeted therapeutics.

Potential serum and urine biomarkers in patients with lupus nephritis and the unsolved problems

Lupus nephritis (LN) is one of the most frequent and serious complications in the patients with systemic lupus erythematosus. Autoimmune-mediated inflammation in both renal glomerular and tubulointerstitial tissues is the major pathological finding of LN. In clinical practice, the elevated anti-dsDNA antibody titer concomitant with reduced complement C3 and C4 levels has become the predictive and disease-activity surrogate biomarkers in LN. However, more and more evidences suggest that autoantibodies other than anti-dsDNA antibodies, such as anti-nucleosome, anti-C1q, anti-C3b, anti-cardiolipin, anti-endothelial cell, anti-ribonuclear proteins, and anti-glomerular matrix (anti-actinin) antibodies, may also involve in LN. Researchers have demonstrated that the circulating preformed and in situ-formed immune complexes as well as the direct cytotoxic effects by those cross-reactive autoantibodies mediated kidney damage. On the other hand, many efforts had been made to find useful urine biomarkers for LN activity via measurement of immune-related mediators, surface-enhanced laser desorption/ionization time-of-flight mass spectrometry proteomic signature, and assessment of mRNA and exosomal-derived microRNA from urine sediment cell. Our group had also devoted to this field with some novel findings. In this review, we briefly discuss the possible mechanisms of LN and try to figure out the potential serum and urine biomarkers in LN. Finally, some of the unsolved problems in this field are discussed.

Identification of extracellular miRNA in archived serum samples by next-generation sequencing from RNA extracted using multiple methods

miRNAs act as important regulators of gene expression by promoting mRNA degradation or by attenuating protein translation. Since miRNAs are stably expressed in bodily fluids, there is growing interest in profiling these miRNAs, as it is minimally invasive and cost-effective as a diagnostic matrix. A technical hurdle in studying miRNA dynamics is the ability to reliably extract miRNA as small sample volumes and low RNA abundance create challenges for extraction and downstream applications. The purpose of this study was to develop a pipeline for the recovery of miRNA using small volumes of archived serum samples. The RNA was extracted employing several widely utilized RNA isolation kits/methods with and without addition of a carrier. The small RNA library preparation was carried out using Illumina TruSeq small RNA kit and sequencing was carried out using Illumina platform. A fraction of five microliters of total RNA was used for library preparation as quantification is below the detection limit. We were able to profile miRNA levels in serum from all the methods tested. We found out that addition of nucleic acid based carrier molecules had higher numbers of processed reads but it did not enhance the mapping of any miRBase annotated sequences. However, some of the extraction procedures offer certain advantages: RNA extracted by TRIzol seemed to align to the miRBase best; extractions using TRIzol with carrier yielded higher miRNA-to-small RNA ratios. Nuclease free glycogen can be carrier of choice for miRNA sequencing. Our findings illustrate that miRNA extraction and quantification is influenced by the choice of methodologies. Addition of nucleic acid- based carrier molecules during extraction procedure is not a good choice when assaying miRNA using sequencing. The careful selection of an extraction method permits the archived serum samples to become valuable resources for high-throughput applications.

Drug repositioning in SLE: crowd-sourcing, literature-mining and Big Data analysis

Lupus patients are in need of modern drugs to treat specific manifestations of their disease effectively and safely. In the past half century, only one new treatment has been approved by the US Food and Drug Administration (FDA) for systemic lupus erythematosus (SLE). In 2014–2015, the FDA approved 71 new drugs, only one of which targeted a rheumatic disease and none of which was approved for use in SLE. Repositioning/repurposing drugs approved for other diseases using multiple approaches is one possible means to find new treatment options for lupus patients. “Big Data” analysis approaches this challenge from an unbiased standpoint whereas literature mining and crowd sourcing for candidates assessed by the CoLTs (Combined Lupus Treatment Scoring) system provide a hypothesis-based approach to rank potential therapeutic candidates for possible clinical application. Both approaches mitigate risk since the candidates assessed have largely been extensively tested in clinical trials for other indications. The usefulness of a multi-pronged approach to drug repositioning in lupus is highlighted by orthogonal confirmation of hypothesis-based drug repositioning predictions by “Big Data” analysis of differentially expressed genes from lupus patient samples. The goal is to identify novel therapies that have the potential to affect disease processes specifically. Involvement of SLE patients and the scientists that study this disease in thinking about new drugs that may be effective in lupus though crowd-sourcing sites such as LRxL-STAT ( www.linkedin.com/in/lrxlstat ) is important in stimulating the momentum needed to test these novel drug targets for efficacy in lupus rapidly in small, proof-of-concept trials conducted by LuCIN, the Lupus Clinical Investigators Network ( www.linkedin.com/in/lucinstat ).