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Objective To identify FN1 transcripts associated with OA pathophysiology and investigate the downstream effects of modulating FN1 expression and relative transcript ratio. Methods FN1 transcriptomic data was obtained from our previously assessed RNA-seq dataset of lesioned and preserved OA cartilage samples from the Research osteoArthritis Articular Cartilage (RAAK) study. Differential transcript expression analysis was performed on all 27 FN1 transcripts annotated in the Ensembl database. Human primary chondrocytes were transduced with lentiviral particles containing short hairpin RNA (shRNA) targeting full-length FN1 transcripts or non-targeting shRNA. Subsequently, matrix deposition was induced in our 3D in vitro neo-cartilage model. Effects of changes in the FN1 transcript ratio on sulphated glycosaminoglycan (sGAG) deposition were investigated by Alcian blue staining and dimethylmethylene blue assay. Moreover, gene expression levels of 17 cartilage-relevant markers were determined by reverse transcription quantitative polymerase chain reaction. Results We identified 16 FN1 transcripts differentially expressed between lesioned and preserved cartilage. FN1-208, encoding migration-stimulating factor, was the most significantly differentially expressed protein coding transcript. Downregulation of full-length FN1 and a concomitant increased FN1-208 ratio resulted in decreased sGAG deposition as well as decreased ACAN and COL2A1 and increased ADAMTS-5, ITGB1 and ITGB5 gene expression levels. Conclusion We show that full-length FN1 downregulation and concomitant relative FN1-208 upregulation was unbeneficial for deposition of cartilage matrix, likely due to decreased availability of the classical RGD (Arg-Gly-Asp) integrin-binding site of fibronectin.

Objectives To investigate whether the deiodinase inhibitor iopanoic acid (IOP) has chondroprotective properties, a mechanical stress induced model of human aged explants was used to test both repeated dosing and slow release of IOP. Methods Human osteochondral explants subjected to injurious mechanical stress (65%MS) were treated with IOP or IOP encapsulated in poly lactic-co-glycolic acid–polyethylene glycol nanoparticles (NP-IOP). Changes to cartilage integrity and signalling were determined by Mankin scoring of histology, sulphated glycosaminoglycan (sGAG) release and expression levels of catabolic, anabolic and hypertrophic markers. Subsequently, on a subgroup of samples, RNA sequencing was performed on 65%MS (n = 14) and 65%MS+IOP (n = 7) treated cartilage to identify IOP’s mode of action. Results Damage from injurious mechanical stress was confirmed by increased cartilage surface damage in the Mankin score, increased sGAG release, and consistent upregulation of catabolic markers and downregulation of anabolic markers. IOP and, though less effective, NP-IOP treatment, reduced MMP13 and increased COL2A1 expression. In line with this, IOP and NP-IOP reduced cartilage surface damage induced by 65%MS, while only IOP reduced sGAG release from explants subjected to 65%MS. Lastly, differential expression analysis identified 12 genes in IOP’s mode of action to be mainly involved in reducing metabolic processes (INSIG1, DHCR7, FADS1 and ACAT2) and proliferation and differentiation (CTGF, BMP5 and FOXM1). Conclusion Treatment with the deiodinase inhibitor IOP reduced detrimental changes of injurious mechanical stress. In addition, we identified that its mode of action was likely on metabolic processes, cell proliferation and differentiation.

ObjectivesThe etiology of osteoarthritis revolves around the interplay between genetic predisposition and perturbing environmental cues, such as mechanical stress. The pericellular matrix, with its hallmark proteins collagen type VI and fibronectin, surrounds chondrocytes and is critical in transducing the biomechanical cues. The objective is to study the functional effects of an OA disease-risk mutation inCOL6A3in interaction with hyper-physiological mechanical cues in a tailored human induced pluripotent stem cells (hiPSCs) derived cartilage organoid model.MethodTo identify pathogenic OA mutations exome sequencing in symptomatic OA patients was performed. To study functional effects, CRISPR-Cas9 genome engineering was used to introduce the mutation in our established human induced pluripotent stem cell-derived in-vitro neo-cartilage organoid model in interaction with hyper-physiological mechanical loading conditions.ResultsA high-impact mutation inCOL6A3was identified that resulted in significantly lower binding between the PCM proteins COLVI and fibronectin (FN) and provoked an osteoarthritic chondrocyte state. Moreover, aberrant function of the PCM, secondary to theCOL6A3mutation, abolished the initial stress responses marked particularly by upregulation ofPTGS2encoding cyclooxygenase-2 (COX-2), after hyper-physiological mechanical loading conditions.ConclusionThese findings demonstrate that ablating the characteristic transient COX-2 response after injurious mechanical cues may have a direct negative impact on chondrocyte health.What is already knownThe etiology of osteoarthritis revolves around the interplay between genetic predisposition and perturbing environmental cues, such as mechanical stress.The pericellular matrix, with its hallmark proteins collagen type VI and fibronectin, surrounds the chondrocytes and is critical in transducing biomechanical cues from the extracellular matrix to chondrocytes henceforth it determines the chondrocyte mechanical environment.The mechanical environment of the chondrocytes is a critical factor that influences chondrocyte health as it determines the balance between synthesis and degradation of the articular cartilage extracellular matrix.What this study addsA sustainable human induced pluripotent stem cell-derived in-vitro neo-cartilage organoid model that is tailored to study detailed biologic effects of mechanical cues to chondrocytes.An OA disease-risk mutation inCOL6A3reduces the binding between collagen type VI to fibronectin and provoked an osteoarthritic chondrocyte state.Upon hyper-physiological mechanical loading, aberrant function of the pericellular matrix, secondary to theCOL6A3mutation, ablates the initial transient inflammatory response, characterized particularly byPTGS2encoding cyclooxygenase-2 (COX-2).How this study might affect research practice or policyInhibiting COX-2, as an important transient inflammatory response after hyper-physiological mechanical cues, could worsen the loss of structural integrity of the cartilage in osteoarthritis patients. Henceforth, prescription of COX-2 inhibitors as pain treatment for OA patients should be reconsidered.

Objectives To present an unbiased approach to identify positional transcript single nucleotide polymorphisms (SNPs) of osteoarthritis (OA) risk loci by allelic expression imbalance (AEI) analyses using RNA sequencing of articular cartilage and subchondral bone from OA patients. Methods RNA sequencing from 65 articular cartilage and 24 subchondral bone from OA patients was used for AEI analysis. AEI was determined for all genes present in the 100 regions reported by the genome-wide association studies (GWAS) catalog that were also expressed in cartilage or bone. The count fraction of the alternative allele (φ) was calculated for each heterozygous individual with the risk SNP or with the SNP in linkage disequilibrium (LD) with it (r2 > 0.6). Furthermore, a meta-analysis was performed to generate a meta-φ (null hypothesis median φ = 0.49) and P-value for each SNP. Results We identified 30 transcript SNPs (28 in cartilage and two in subchondral bone) subject to AEI in 29 genes. Notably, 10 transcript SNPs were located in genes not previously reported in the GWAS catalog, including two long intergenic non-coding RNAs (lincRNAs), MALAT1 (meta-φ = 0.54, FDR = 1.7×10−4) and ILF3-DT (meta-φ = 0.6, FDR = 1.75×10−5). Moreover, 12 drugs were interacting with seven genes displaying AEI, of which seven drugs have been already approved. Conclusions By prioritizing proxy transcript SNPs that mark AEI in cartilage and/or subchondral bone at loci harbouring GWAS signals, we present an unbiased approach to identify the most likely functional OA risk-SNP and gene. We identified 10 new potential OA risk genes ready for further translation towards underlying biological mechanisms.

ObjectivesIn osteoarthritis, methylation of lysine 79 on histone H3 (H3K79me), a protective epigenetic mechanism, is reduced. Histone methylation levels are dynamically regulated by histone methyltransferases and demethylases. Here, we aimed to identify which histone demethylases regulate H3K79me in cartilage and investigate whether their targeting protects against osteoarthritis.MethodsWe determined histone demethylase expression in human non-osteoarthritis and osteoarthritis cartilage using qPCR. The role of histone demethylase families and subfamilies on H3K79me was interrogated by treatment of human C28/I2 chondrocytes with pharmacological inhibitors, followed by western blot and immunofluorescence. We performed C28/I2 micromasses to evaluate effects on glycosaminoglycans by Alcian blue staining. Changes in H3K79me after destabilisation of the medial meniscus (DMM) in mice were determined by immunohistochemistry. Daminozide, a KDM2/7 subfamily inhibitor, was intra-articularly injected in mice upon DMM. Histone demethylases targeted by daminozide were individually silenced in chondrocytes to dissect their role on H3K79me and osteoarthritis.ResultsWe documented the expression signature of histone demethylases in human non-osteoarthritis and osteoarthritis articular cartilage. Inhibition of Jumonji-C demethylase family increased H3K79me in human chondrocytes. Blockade of KDM2/7 histone demethylases with daminozide increased H3K79me and glycosaminoglycans. In mouse articular cartilage, H3K79me decayed rapidly upon induction of joint injury. Early and sustained intra-articular treatment with daminozide enhanced H3K79me and exerted protective effects in mice upon DMM. Individual silencing of KDM7A/B demethylases in human chondrocytes demonstrated that KDM7A/B mediate protective effects of daminozide on H3K79me and osteoarthritis.ConclusionTargeting KDM7A/B histone demethylases could be an attractive strategy to protect joints against osteoarthritis.

ObjectiveTo explore the co-expression network of the osteoarthritis (OA) risk gene WWP2 in articular cartilage and study cartilage characteristics when mimicking the effect of OA risk allele rs1052429-A on WWP2 expression in a human 3D in vitro model of cartilage.MethodsCo-expression behavior of WWP2 with genes expressed in lesioned OA articular cartilage (N=35 samples) was explored. By applying lentiviral particle mediated WWP2 upregulation in 3D in vitro pellet cultures of human primary chondrocytes (N=8 donors) the effects of upregulation on cartilage matrix deposition was evaluated. Finally, we transfected primary chondrocytes with miR-140 mimics to evaluate whether miR-140 and WWP2 are involved in similar pathways.ResultsUpon performing Spearman correlations in lesioned OA cartilage, 98 highly correlating genes (|ρ|>0.7) were identified. Among these genes, we identified GJA1, GDF10, STC2, WDR1, and WNK4. Subsequent upregulation of WWP2 on 3D chondrocyte pellet cultures resulted in a decreased expression of COL2A1 and ACAN and an increase in EPAS1 expression. Additionally, we observed a decreased expression of GDF10, STC2, and GJA1. Proteomics analysis identified 42 proteins being differentially expressed with WWP2 upregulation, which were enriched for ubiquitin conjugating enzyme activity. Finally, upregulation of miR-140 in 2D chondrocytes resulted in significant upregulation of WWP2 and WDR1.ConclusionsMimicking the effect of OA risk allele rs1052429-A on WWP2 expression initiates detrimental processes in the cartilage shown by a response in hypoxia associated genes EPAS1,GDF10, and GJA1 and a decrease in anabolic markers, COL2A1 and ACAN.

BackgroundDespite recent advances in the understanding of the genetic architecture of osteoarthritis (OA), only two genetic loci have been identified for OA of the hand, in part explained by the complexity of the different hand joints and heterogeneity of OA pathology.MethodsWe used data from the Rotterdam Study (RSI, RSII and RSIII) to create three hand OA phenotypes based on clustering patterns of radiographic OA severity to increase power in our modest discovery genome-wide association studies in the RS (n=8700), and sought replication in an independent cohort, the Framingham Heart Study (n=1203). We used multiple approaches that leverage different levels of information and functional data to further investigate the underlying biological mechanisms and candidate genes for replicated loci. We also attempted to replicate known OA loci at other joint sites, including the hips and knees.ResultsWe found two novel genome-wide significant loci for OA in the thumb joints. We identifiedWNT9Aas a possible novel causal gene involved in OA pathogenesis. Furthermore, several previously identified genetic loci for OA seem to confer risk for OA across multiple joints:TGFa,RUNX2,COL27A1,ASTN2,IL11andGDF5loci.ConclusionsWe identified a robust novel genetic locus for hand OA on chromosome 1, of whichWNT9Ais the most likely causal gene. In addition, multiple genetic loci were identified to be associated with OA across multiple joints. Our study confirms the potential for novel insight into the genetic architecture of OA by using biologically meaningful stratified phenotypes.

Osteoarthritis (OA) is a degenerative joint disease, and inflammation within an arthritic joint plays a critical role in disease progression. Pro-inflammatory cytokines, specifically IL-1 and TNF-alpha, induce aberrant expression of catabolic and degradative enzymes and inflammatory cytokines in OA and result in a challenging environment for cartilage repair and regeneration. MicroRNAs (miRNAS) are small noncoding RNAs and are important regulatory molecules that act by binding to target messenger RNAs (mRNAs) to reduce protein synthesis and have been implicated in many diseases, including OA. The goal of this study was to understand the mechanisms of miRNA regulation of the transcriptome of tissue-engineered cartilage in response to IL-1 beta and TNF-alpha using an in vitro murine induced pluripotent stem cell (miPSC) model system. We performed miRNA and mRNA sequencing to determine the temporal and dynamic responses of genes to specific inflammatory cytokines as well as miRNAs that are differentially expressed (DE) in response to both cytokines or exclusively to IL-1 beta or TNF-alpha. Through integration of mRNA and miRNA sequencing data, we created networks of miRNA-mRNA interactions which may be controlling the response to inflammatory cytokines. Within the networks, hub miRNAs, miR-29b-3p, miR-17-5p, and miR-20a-5p, were identified. As validation of these findings, we found that delivery of miR-17-5p and miR-20a-5p mimics significantly decreased degradative enzyme activity levels while also decreasing expression of inflammation-related genes in cytokine-treated cells. This study utilized an integrative approach to determine the miRNA interactome controlling the response to inflammatory cytokines and novel mediators of inflammation-driven degradation in tissue-engineered cartilage.

Objectives OA is a complex genetic disease with different risk factors contributing to its development. One of the genes, TNFRSF11B, previously identified with gain-of-function mutation in a family with early-onset OA with chondrocalcinosis, is among the highest upregulated genes in lesioned OA cartilage (RAAK-study). Here, we determined the role of TNFRSF11B overexpression in development of OA. Methods Human primary articular chondrocytes (9 donors RAAK study) were transduced using lentiviral particles with or without TNFRSF11B. Cells were cultured for 1 week in a 3 D in-vitro chondrogenic model. TNFRSF11B overexpression was confirmed by RT-qPCR, immunohistochemistry and ELISA. Effects of TNFRSF11B overexpression on cartilage matrix deposition, matrix mineralization, and genes highly correlated to TNFRSF11B in RNA-sequencing dataset (r >0.75) were determined by RT-qPCR. Additionally, glycosaminoglycans and collagen deposition were visualized with Alcian blue staining and immunohistochemistry (COL1 and COL2). Results Overexpression of TNFRSF11B resulted in strong upregulation of MMP13, COL2A1 and COL1A1. Likewise, mineralization and osteoblast characteristic markers RUNX2, ASPN and OGN showed a consistent increase. Among 30 genes highly correlated to TNFRSF11B, expression of only eight changed significantly, with BMP6 showing the highest increase (9-fold) while expression of RANK and RANKL remained unchanged indicating previously unknown downstream pathways of TNFRSF11B in cartilage. Conclusion Results of our 3D in vitro chondrogenesis model indicate that upregulation of TNFRSF11B in lesioned OA cartilage may act as a direct driving factor for chondrocyte to osteoblast transition observed in OA pathophysiology. This transition does not appear to act via the OPG/RANK/RANKL triad common in bone remodeling.

Celiac disease (CeD) is triggered by gluten and results in inflammation and villous atrophy of the small intestine. We aimed to explore the role of miRNA-mediated deregulation of the transcriptome in CeD. Duodenal biopsies of CeD patients (n = 33) and control subjects (n = 10) were available for miRNA-sequencing, with RNA-sequencing also available for controls (n = 5) and CeD (n = 6). Differential expression analysis was performed to select CeD-associated miRNAs and genes. MiRNA‒target transcript pairs selected from public databases that also displayed a strong negative expression correlation in the current dataset (R &lt, −0.7) were used to construct a CeD miRNA‒target transcript interaction network. The network includes 2030 miRNA‒target transcript interactions, including 423 experimentally validated pairs. Pathway analysis found that interactions are involved in immune-related pathways (e.g., interferon signaling) and metabolic pathways (e.g., lipid metabolism). The network includes 13 genes previously prioritized to be causally deregulated by CeD-associated genomic variants, including STAT1. CeD-associated miRNAs might play a role in promoting inflammation and decreasing lipid metabolism in the small intestine, thereby contributing unbalanced cell turnover in the intestinal crypt. Some CeD-associated miRNAs deregulate genes that are also affected by genomic CeD-risk variants, adding an additional layer of complexity to the deregulated transcriptome in CeD.

Objective: To identify and validate circulating micro RNAs (miRNAs) that mark gene expression changes in articular cartilage early in osteoarthritis (OA) pathophysiology process. Methods: Within the ongoing RAAK study, human preserved OA cartilage and plasma (N = 22 paired samples) was collected for RNA sequencing (respectively mRNA and miRNA). Spearman correlation was determined for 114 cartilage genes consistently and significantly differentially expressed early in osteoarthritis and 384 plasma miRNAs. Subsequently, the minimal number of circulating miRNAs serving to discriminate between progressors and non-progressors was assessed by regression analysis and area under receiver operating curves (AUC) was calculated with progression data and plasma miRNA sequencing from the GARP study (N = 71). Results: We identified strong correlations (ρ ≥ |0.7|) among expression levels of 34 unique plasma miRNAs and 21 genes, including 4 genes that correlated with multiple miRNAs. The strongest correlation was between let-7d-5p and EGFLAM (ρ = −0.75, P = 6.9 × 10−5). Regression analysis of the 34 miRNAs resulted in a set of 7 miRNAs that, when applied to the GARP study, demonstrated clinically relevant predictive value with AUC &gt, 0.8 for OA progression over 2 years and near-clinical value for progression over 5 years- (AUC = 0.8). Conclusions: We show that plasma miRNAs levels reflect gene expression levels in cartilage and can be exploited to represent ongoing pathophysiological processes in articular cartilage. We advocate that identified signature of 7 plasma miRNAs can contribute to direct further studies toward early biomarkers predictive for progression of osteoarthritis over 2 and 5 years.

BackgroundFailing of intrinsic chondrocyte repair after mechanical stress is known as one of the most important initiators of osteoarthritis. Nonetheless, insight into these early mechano-pathophysiological processes in age-related human articular cartilage is still lacking. Such insights are needed to advance clinical development. To highlight important molecular processes of osteoarthritis mechano-pathology, the transcriptome-wide changes following injurious mechanical stress on human aged osteochondral explants were characterized.MethodsFollowing mechanical stress at a strain of 65% (65%MS) on human osteochondral explants (n65%MS= 14 versusncontrol= 14), RNA sequencing was performed. Differential expression analysis between control and 65%MS was performed to determine mechanical stress-specific changes. Enrichment for pathways and protein-protein interactions was analyzed with Enrichr and STRING.ResultsWe identified 156 genes significantly differentially expressed between control and 65%MS human osteochondral explants. Of note,IGFBP5(FC = 6.01; FDR = 7.81 × 10−3) andMMP13(FC = 5.19; FDR = 4.84 × 10−2) were the highest upregulated genes, whileIGFBP6(FC = 0.19; FDR = 3.07 × 10−4) was the most downregulated gene. Protein-protein interactions were significantly higher than expected by chance (P= 1.44 × 10−15with connections between 116 out of 156 genes). Pathway analysis showed, among others, enrichment for cellular senescence, insulin-like growth factor (IGF) I and II binding, and focal adhesion.ConclusionsOur results faithfully represent transcriptomic wide consequences of mechanical stress in human aged articular cartilage withMMP13, IGF binding proteins, and cellular senescence as the most notable results. Acquired knowledge on the as such identified initial, osteoarthritis-related, detrimental responses of chondrocytes may eventually contribute to the development of effective disease-modifying osteoarthritis treatments.

Objective To gain insight in the expression profile of long non-coding RNAs (lncRNAs) in OA subchondral bone. Methods RNA sequencing data of macroscopically preserved and lesioned OA subchondral bone of patients that underwent joint replacement surgery due to OA (N = 22 pairs; 5 hips, 17 knees, Research osteoArthrits Articular Tissue (RAAK study) was run through an in-house pipeline to detect expression of lncRNAs. Differential expression analysis between preserved and lesioned bone was performed. Spearman correlations were calculated between differentially expressed lncRNAs and differentially expressed mRNAs identified previously in the same samples. Primary osteogenic cells were transfected with locked nucleic acid (LNA) GapmeRs targeting AC005165.1 lncRNA, to functionally investigate its potential mRNA targets. Results In total, 2816 lncRNAs were well-expressed in subchondral bone and we identified 233 lncRNAs exclusively expressed in knee and 307 lncRNAs exclusively in hip. Differential expression analysis, using all samples (N = 22 pairs; 5 hips, 17 knees), resulted in 21 differentially expressed lncRNAs [false discovery rate (FDR) < 0.05, fold change (FC) range 1.19–7.39], including long intergenic non-protein coding RNA (LINC) 1411 (LINC01411, FC = 7.39, FDR = 2.20 × 10−8), AC005165.1 (FC = 0.44, FDR = 2.37 × 10−6) and empty spiracles homeobox 2 opposite strand RNA (EMX2OS, FC = 0.41, FDR = 7.64 × 10−3). Among the differentially expressed lncRNAs, five were also differentially expressed in articular cartilage, including AC005165.1, showing similar direction of effect. Downregulation of AC005165.1 in primary osteogenic cells resulted in consistent downregulation of highly correlated frizzled related protein (FRZB). Conclusion The current study identified a novel lncRNA, AC005165.1, being dysregulated in OA articular cartilage and subchondral bone. Downregulation of AC005165.1 caused a decreased expression of OA risk gene FRZB, an important member of the wnt pathway, suggesting that AC005165.1 could be an attractive potential therapeutic target with effects in articular cartilage and subchondral bone.

Triple negative breast cancer (TNBC), a clinically aggressive breast cancer subtype, affects 15–35% of women from Latin America. Using an approach of direct integration of copy number and global miRNA profiling data, performed simultaneously in the same tumor specimens, we identified a panel of 17 miRNAs specifically associated with TNBC of ancestrally characterized patients from Latin America, Brazil. This panel was differentially expressed between the TNBC and non-TNBC subtypes studied (p ≤ 0.05, FDR ≤ 0.25), with their expression levels concordant with the patterns of copy number alterations (CNAs), present mostly frequent at 8q21.3-q24.3, 3q24-29, 6p25.3-p12.2, 1q21.1-q44, 5q11.1-q22.1, 11p13-p11.2, 13q12.11-q14.3, 17q24.2-q25.3 and Xp22.33-p11.21. The combined 17 miRNAs presented a high power (AUC = 0.953 (0.78–0.99);95% CI) in discriminating between the TNBC and non-TNBC subtypes of the patients studied. In addition, the expression of 14 and 15 of the 17miRNAs was significantly associated with tumor subtype when adjusted for tumor stage and grade, respectively. In conclusion, the panel of miRNAs identified demonstrated the impact of CNAs in miRNA expression levels and identified miRNA target genes potentially affected by both CNAs and miRNA deregulation. These targets, involved in critical signaling pathways and biological functions associated specifically with the TNBC transcriptome of Latina patients, can provide biological insights into the observed differences in the TNBC clinical outcome among racial/ethnic groups, taking into consideration their genetic ancestry.

ObjectiveTo uncover the microRNA (miRNA) interactome of the osteoarthritis (OA) pathophysiological process in the cartilage.MethodsWe performed RNA sequencing in 130 samples (n=35 and n=30 pairs for messenger RNA (mRNA) and miRNA, respectively) on macroscopically preserved and lesioned OA cartilage from the same patient and performed differential expression (DE) analysis of miRNA and mRNAs. To build an OA-specific miRNA interactome, a prioritisation scheme was applied based on inverse Pearson’s correlations and inverse DE of miRNAs and mRNAs. Subsequently, these were filtered by those present in predicted (TargetScan/microT-CDS) and/or experimentally validated (miRTarBase/TarBase) public databases. Pathway enrichment analysis was applied to elucidate OA-related pathways likely mediated by miRNA regulatory mechanisms.ResultsWe found 142 miRNAs and 2387 mRNAs to be differentially expressed between lesioned and preserved OA articular cartilage. After applying prioritisation towards likely miRNA-mRNA targets, a regulatory network of 62 miRNAs targeting 238 mRNAs was created. Subsequent pathway enrichment analysis of these mRNAs (or genes) elucidated that genes within the ‘nervous system development’ are likely mediated by miRNA regulatory mechanisms (familywise error=8.4×10−5). Herein NTF3 encodes neurotrophin-3, which controls survival and differentiation of neurons and which is closely related to the nerve growth factor.ConclusionsBy an integrated approach of miRNA and mRNA sequencing data of OA cartilage, an OA miRNA interactome and related pathways were elucidated. Our functional data demonstrated interacting levels at which miRNA affects expression of genes in the cartilage and exemplified the complexity of functionally validating a network of genes that may be targeted by multiple miRNAs.

OBJECTIVE To identify key determinants of the interactive pathophysiologic processes in subchondral bone and cartilage in osteoarthritis (OA). METHODS We performed RNA sequencing on macroscopically preserved and lesional OA subchondral bone from patients in the Research Arthritis and Articular Cartilage study who underwent joint replacement surgery due to OA (n = 24 sample pairs: 6 hips and 18 knees). Unsupervised hierarchical clustering and differential expression analyses were conducted. Results were combined with data on previously identified differentially expressed genes in cartilage (partly overlapping samples) as well as data on recently identified OA risk genes. RESULTS We identified 1,569 genes that were significantly differentially expressed between lesional and preserved subchondral bone, including CNTNAP2 (fold change [FC] 2.4, false discovery rate [FDR] 3.36 × 10-5 ) and STMN2 (FC 9.6, FDR 2.36 × 10-3 ). Among these 1,569 genes, 305 were also differentially expressed, and with the same direction of effect, in cartilage, including the recently recognized OA susceptibility genes IL11 and CHADL. Upon differential expression analysis with stratification for joint site, we identified 509 genes that were exclusively differentially expressed in subchondral bone of the knee, including KLF11 and WNT4. These genes that were differentially expressed exclusively in the knee were enriched for involvement in epigenetic processes, characterized by, e.g., HIST1H3J and HIST1H3H. CONCLUSION IL11 and CHADL were among the most consistently differentially expressed genes OA pathophysiology-related genes in both bone and cartilage. As these genes were recently also identified as robust OA risk genes, they classify as attractive therapeutic targets acting on 2 OA-relevant tissues.

The Brazilian population is a product of asymmetric admixture among European men and Amerindian and African women. However, Brazilian subcontinental ancestry is scarcely documented, especially regarding its African roots. Here, we aimed to unveil the uniparental continental and subcontinental contributions from distinct Brazilian regions, including South (n = 43), Southeast (n = 71), the poorly genetically characterized Central-Western region (n = 323), and a subset of unique Brazilian Amerindians (n = 24), in the context of their genome-wide ancestral contributions. The overwhelming majority of European Y haplogroups (85%) contrast sharply with the predominant African and Amerindian mtDNA haplogroups (73.2%) in admixed populations, whereas in Amerindians, non-Native haplogroups could only be detected through the paternal line. Our in-depth investigation of uniparental markers showed signals of an Andean and Central-Brazilian Amerindian maternal contribution to Southeastern and Central-Western Brazil (83.1 ± 2.1% and 56.9 ± 0.2%, respectively), the last having the highest paternal Amerindian ancestry yet described for an admixed Brazilian region (9.7%) and contrasting with higher Southern-Brazilian Amerindian contribution to Southern Brazil (59.6 ± 1%). Unlike the higher African Bantu contribution previously reported for the South and Southeast, a relevant Western African non-Bantu contribution was detected in those regions (85.7 ± 5% and 71.8 ± 10.8% respectively). In contrast, a higher Bantu contribution was described for the first time in the Central-West (64.8 ± 1.3% maternal and 86.9 ± 9.6% paternal). We observed sex-biased signatures consistent with the historically recorded Brazilian colonization and added new insights in the subcontinental maternal ancestry of Brazilians from regions never studied at this level.

Osteoarthritis is a complex degenerative joint disease. Here, we investigate matched genotype and methylation profiles of primary chondrocytes from macroscopically intact (low-grade) and degraded (high-grade) osteoarthritis cartilage and from synoviocytes collected from 98 osteoarthritis-affected individuals undergoing knee replacement surgery. We perform an epigenome-wide association study of knee cartilage degeneration and report robustly replicating methylation markers, which reveal an etiologic mechanism linked to the migration of epithelial cells. Using machine learning, we derive methylation models of cartilage degeneration, which we validate with 82% accuracy in independent data. We report a genome-wide methylation quantitative trait locus (mQTL) map of articular cartilage and synovium and identify 18 disease-grade-specific mQTLs in osteoarthritis cartilage. We resolve osteoarthritis GWAS loci through causal inference and colocalization analyses and decipher the epigenetic mechanisms that mediate the effect of genotype on disease risk. Together, our findings provide enhanced insights into epigenetic mechanisms underlying osteoarthritis in primary tissues.

Mauricio Lima Barreto - Fundacao Oswaldo Cruz. Instituto Goncalo Moniz. Salvador, BA, Brasil. Documento produzido em parceria ou por autor vinculado a Fiocruz, mas nao consta a informacao no documento.

Objective To identify OA subtypes based on cartilage transcriptomic data in cartilage tissue and characterize their underlying pathophysiological processes and/or clinically relevant characteristics. Methods This study includes n = 66 primary OA patients (41 knees and 25 hips), who underwent a joint replacement surgery, from which macroscopically unaffected (preserved, n = 56) and lesioned (n = 45) OA articular cartilage were collected [Research Arthritis and Articular Cartilage (RAAK) study]. Unsupervised hierarchical clustering analysis on preserved cartilage transcriptome followed by clinical data integration was performed. Protein–protein interaction (PPI) followed by pathway enrichment analysis were done for genes significant differentially expressed between subgroups with interactions in the PPI network. Results Analysis of preserved samples (n = 56) resulted in two OA subtypes with n = 41 (cluster A) and n = 15 (cluster B) patients. The transcriptomic profile of cluster B cartilage, relative to cluster A (DE-AB genes) showed among others a pronounced upregulation of multiple genes involved in chemokine pathways. Nevertheless, upon investigating the OA pathophysiology in cluster B patients as reflected by differentially expressed genes between preserved and lesioned OA cartilage (DE-OA-B genes), the chemokine genes were significantly downregulated with OA pathophysiology. Upon integrating radiographic OA data, we showed that the OA phenotype among cluster B patients, relative to cluster A, may be characterized by higher joint space narrowing (JSN) scores and low osteophyte (OP) scores. Conclusion Based on whole-transcriptome profiling, we identified two robust OA subtypes characterized by unique OA, pathophysiological processes in cartilage as well as a clinical phenotype. We advocate that further characterization, confirmation and clinical data integration is a prerequisite to allow for development of treatments towards personalized care with concurrently more effective treatment response.

Summary Osteoarthritis affects over 300 million people worldwide. Here, we conduct a genome-wide association study meta-analysis across 826,690 individuals (177,517 with osteoarthritis) and identify 100 independently associated risk variants across 11 osteoarthritis phenotypes, 52 of which have not been associated with the disease before. We report thumb and spine osteoarthritis risk variants and identify differences in genetic effects between weight-bearing and non-weight-bearing joints. We identify sex-specific and early age-at-onset osteoarthritis risk loci. We integrate functional genomics data from primary patient tissues (including articular cartilage, subchondral bone, and osteophytic cartilage) and identify high-confidence effector genes. We provide evidence for genetic correlation with phenotypes related to pain, the main disease symptom, and identify likely causal genes linked to neuronal processes. Our results provide insights into key molecular players in disease processes and highlight attractive drug targets to accelerate translation., Graphical abstract, Highlights • A multicohort study identifies 52 previously unknown osteoarthritis genetic risk variants • Similarities and differences in osteoarthritis genetic risk depend on joint sites • Osteoarthritis genetic components are associated with pain-related phenotypes • High-confidence effector genes highlight potential targets for drug intervention, A multicohort genome-wide association meta-analysis of osteoarthritis highlights the impact of joint site types on the features of genetic risk variants and the link between osteoarthritis genetics and pain-related phenotypes, pointing toward potential targets for therapeutic intervention.

Pemphigus foliaceus (PF) is an autoimmune blistering disease of the skin, clinically characterized by erosions and, histopathologically, by acantholysis. PF is endemic in the Brazilian Central-Western region. Numerous single nucleotide polymorphisms (SNPs) have been shown to affect the susceptibility for PF, including SNPs at long non-coding RNA (lncRNA) genes, which are known to participate in many physiological and pathogenic processes, such as autoimmunity. Here, we investigated whether the genetic variation of immune-related lncRNA genes affects the risk for endemic and sporadic forms of PF. We analysed 692 novel SNPs for PF from 135 immune-related lncRNA genes in 227 endemic PF patients and 194 controls. The SNPs were genotyped by Illumina microarray and analysed by applying logistic regression at additive model, with correction for sex and population structure. Six associated SNPs were also evaluated in an independent German cohort of 76 sporadic PF patients and 150 controls. Further, we measured the expression levels of two associated lncRNA genes (LINC-PINT and LY86-AS1) by quantitative PCR, stratified by genotypes, in peripheral blood mononuclear cells of healthy subjects. We found 27 SNPs in 11 lncRNA genes associated with endemic PF (p < .05 without overlapping with protein-coding genes). Among them, the LINC-PINT SNP rs10228040*A (OR = 1.47, p = .012) was also associated with increased susceptibility for sporadic PF (OR = 2.28, p = .002). Moreover, the A+ carriers of LY86-AS1*rs12192707 mark lowest LY86-AS1 RNA levels, which might be associated with a decreasing autoimmune response. Our results suggest a critical role of lncRNA variants in immunopathogenesis of both PF endemic and sporadic forms.

OBJECTIVE To identify robustly differentially expressed long noncoding RNAs (lncRNAs) with osteoarthritis (OA) pathophysiology in cartilage and to explore potential target messenger RNA (mRNA) by establishing coexpression networks, followed by functional validation. METHODS RNA sequencing was performed on macroscopically lesioned and preserved OA cartilage from patients who underwent joint replacement surgery due to OA (n = 98). Differential expression analysis was performed on lncRNAs that were annotated in GENCODE and Ensembl databases. To identify potential interactions, correlations were calculated between the identified differentially expressed lncRNAs and the previously reported differentially expressed protein-coding genes in the same samples. Modulation of chondrocyte lncRNA expression was achieved using locked nucleic acid GapmeRs. RESULTS By applying our in-house pipeline, we identified 5,053 lncRNAs that were robustly expressed, of which 191 were significantly differentially expressed (according to false discovery rate) between lesioned and preserved OA cartilage. Upon integrating mRNA sequencing data, we showed that intergenic and antisense differentially expressed lncRNAs demonstrate high, positive correlations with their respective flanking sense genes. To functionally validate this observation, we selected P3H2-AS1, which was down-regulated in primary chondrocytes, resulting in the down-regulation of P3H2 gene expression levels. As such, we can confirm that P3H2-AS1 regulates its sense gene P3H2. CONCLUSION By applying an improved detection strategy, robustly differentially expressed lncRNAs in OA cartilage were detected. Integration of these lncRNAs with differential mRNA expression levels in the same samples provided insight into their regulatory networks. Our data indicates that intergenic and antisense lncRNAs play an important role in regulating the pathophysiology of OA.

Background Despite recent advances in the understanding of the genetic architecture of osteoarthritis (OA), only two genetic loci have been identified for OA of the hand, in part explained by the complexity of the different hand joints and heterogeneity of OA pathology. Methods We used data from the Rotterdam Study (RSI, RSII and RSIII) to create three hand OA phenotypes based on clustering patterns of radiographic OA severity to increase power in our modest discovery genome-wide association studies in the RS (n=8700), and sought replication in an independent cohort, the Framingham Heart Study (n=1203). We used multiple approaches that leverage different levels of information and functional data to further investigate the underlying biological mechanisms and candidate genes for replicated loci. We also attempted to replicate known OA loci at other joint sites, including the hips and knees. Results We found two novel genome-wide significant loci for OA in the thumb joints. We identified WNT9A as a possible novel causal gene involved in OA pathogenesis. Furthermore, several previously identified genetic loci for OA seem to confer risk for OA across multiple joints: TGFa, RUNX2, COL27A1, ASTN2, IL11 and GDF5 loci. Conclusions We identified a robust novel genetic locus for hand OA on chromosome 1, of which WNT9A is the most likely causal gene. In addition, multiple genetic loci were identified to be associated with OA across multiple joints. Our study confirms the potential for novel insight into the genetic architecture of OA by using biologically meaningful stratified phenotypes.

ObjectiveTo identify robustly differentially expressed long non-coding RNAs (lncRNAs) with osteoarthritis (OA) pathophysiology in cartilage. Moreover to explore potential target mRNAs by establishing co-expression networks, followed by functional validation.MethodsRNA sequencing was performed on macroscopically lesioned and preserved OA cartilage of patients who underwent a joint replacement surgery due to OA (N=98). Differential expression (DE) analysis was performed on lncRNAs that were annotated in GENCODE and Ensembl. To identify potential interactions, correlations were calculated between the identified DE lncRNAs and previously reported DE protein-coding genes in the same samples. Modulation of chondrocyte lncRNA expression was achieved using LNA GapmeRs.ResultsBy applying our in-house pipeline we identified 5,053 lncRNAs to be robustly expressed, of which 191 were FDR significant differentially expressed between lesioned and preserved OA cartilage. Upon integrating mRNA sequencing data, we showed that intergenic and antisense DE lncRNAs show high, positive correlations with their flanking, respectively, sense genes. To functionally validate this observation we selectedP3H2-AS1, which was downregulated in primary chondrocytes, resulting in downregulation ofP3H2gene expression levels. As such, we can confirm thatP3H2-AS1regulates its sense geneP3H2.ConclusionBy applying an improved detection strategy, robustly differentially expressed lncRNAs in OA cartilage were detected. Integration of these lncRNAs with differential mRNA expression levels in the same samples showed insight into their regulatory networks. Our data signifies that intergenic, as well as antisense lncRNAs play an important role in regulating the pathophysiology of OA.

MicroRNAs (miRNAs) play an essential role in gene expression and affect the development of tumours, including breast cancer (BC). Polymorphisms in miRNA genes can affect the interaction of miRNAs with their target messenger RNA by interfering, creating or disrupting target sites. The single nucleotide polymorphism (SNP) rs2910164, located in the seed region of miR146a, was shown to be associated with BC among different populations. In the present study, we investigated whether rs2910164 is associated with BC in 326 patients and 411 controls from a Brazilian population of predominantly European ancestry. The presence of the allele rs2910164*C was associated with an increased risk of BC (OR=1.4, 95% CI=1.03-1.85, p = 0.03). We also analysed publicly available RNA-seq data to evaluate if miR146a is differentially expressed in different subtypes of BC. Genotyping was performed by polymerase chain reaction with sequence-specific primers (PCR-SSP). By leveraging public data from TCGA database, we analysed 461 patients and found that miR146a is significantly more expressed in BC than in non-tumor tissue (1.47 fold, p = 0.02) and is expressed to a greater degree in aggressive BC subtypes.

MicroRNAs derived from extracellular vesicles (EV-miRNAs) are circulating miRNAs considered as potential new diagnostic markers for cancer that can be easily detected in liquid biopsies. In this study, we performed RNA sequencing analysis as a screening strategy to identify EV-miRNAs derived from serum of clinically well-annotated breast cancer (BC) patients from the south of Brazil. EVs from three groups of samples (healthy controls (CT), luminal A (LA), and triple-negative (TNBC)) were isolated from serum using a precipitation method and analyzed by RNA-seq (screening phase). Subsequently, four EV-miRNAs (miR-142-5p, miR-150-5p, miR-320a, and miR-4433b-5p) were selected to be quantified by quantitative real-time PCR (RT-qPCR) in individual samples (test phase). A panel composed of miR-142-5p, miR-320a, and miR-4433b-5p distinguished BC patients from CT with an area under the curve (AUC) of 0.8387 (93.33% sensitivity, 68.75% specificity). The combination of miR-142-5p and miR-320a distinguished LA patients from CT with an AUC of 0.9410 (100% sensitivity, 93.80% specificity). Interestingly, decreased expression of miR-142-5p and miR-150-5p were significantly associated with more advanced tumor grades (grade III), while the decreased expression of miR-142-5p and miR-320a was associated with a larger tumor size. These results provide insights into the potential application of EVs-miRNAs from serum as novel specific markers for early diagnosis of BC.

Pemphigus foliaceus (PF) is a blistering autoimmune skin disease rare in most of the world but endemic in certain regions of Brazil. PF is characterized by the detachment of epidermal cells and the presence of autoantibodies against desmoglein 1. In previous studies, we have shown that genetic polymorphisms and variable expression levels of certain leucocyte receptor complex (LRC) genes were associated with PF. However, the role of the LRC on PF susceptibility remained to be investigated. Here, we analysed 527 tag single nucleotide polymorphisms (SNPs) distributed within the 1·5 Mb LRC. After quality control, a total of 176 SNPs were analysed in 229 patients with PF and 194 controls. Three SNPs were associated with differential susceptibility to PF. The intergenic variant rs465169 [odds ratio (OR) = 1·50; P = 0·004] is located in a region that might regulate several immune-related genes, including VSTM1, LILRB1/2, LAIR1/2, LILRA3/4 and LENG8. The rs35336528 (OR = 3·44; P = 0·009) and rs1865097 (OR = 0·57; P = 0·005) SNPs in LENG8 and FCAR genes, respectively, were also associated with PF. Moreover, we found four haplotypes with SNPs within the KIR3DL2/3, LAIR2 and LILRB1 genes associated with PF (P < 0·05), which corroborate previously reported associations. Thus, our results confirm the importance of the LRC for differential susceptibility to PF and reveal new markers that might influence expression levels of several LRC genes, as well as candidates for further functional studies.

// Bruna Sugita 1 , Mandeep Gill 2 , Akanskha Mahajan 2 , Anju Duttargi 2 , Saurabh Kirolikar 2 , Rodrigo Almeida 1 , Kenny Regis 2 , Olusayo L. Oluwasanmi 2 , Fabio Marchi 3 , Catalin Marian 4, 8 , Kepher Makambi 2, 5 , Bhaskar Kallakury 6 , Laura Sheahan 7 , Iglenir J.Cavalli 1 , Enilze M. Ribeiro 1 , Subha Madhavan 2, 7 , Simina Boca 2, 7 , Yuriy Gusev 2, 7 , Luciane R. Cavalli 2 1 Department of Genetics, Federal University of Parana, Curitiba, PR, Brazil 2 Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC, USA 3 International Research Center-CIPE, A. C. Camargo Cancer Center, Sao Paulo, SP, Brazil 4 The Ohio State University Comprehensive Cancer Center, Division of Cancer Prevention and Control, College of Medicine, The Ohio State University, Columbus, Ohio 5 Departments of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University, Washington, DC USA 6 Department of Pathology, Georgetown University Medical Center, Washington, DC, USA 7 Innovation Center for Biomedical Informatics, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC, USA 8 The University of Medicine and Pharmacy Timisoara, Timisoara, Romania Correspondence to: Luciane R. Cavalli, email: lrc@georgetown.edu Keywords: microRNA, triple negative breast cancer, African American, non-Hispanic white, copy number Received: July 02, 2016 Accepted: October 25, 2016 Published: November 02, 2016 ABSTRACT Triple Negative Breast Cancer (TNBC), a clinically aggressive subtype of breast cancer, disproportionately affects African American (AA) women when compared to non-Hispanic Whites (NHW). MiRNAs(miRNAs) play a critical role in these tumors, through the regulation of cancer driver genes. In this study, our goal was to characterize and compare the patterns of miRNA expression in TNBC of AA ( n = 27) and NHW women ( n = 30). A total of 256 miRNAs were differentially expressed between these groups, and distinct from the ones observed in their respective non-TNBC subtypes. Fifty-five of these miRNAs were mapped in cytobands carrying copy number alterations (CNAs); 26 of them presented expression levels concordant with the observed CNAs. Receiving operating characteristic (ROC) analysis showed a good power (AUC ≥ 0.80; 95% CI) for over 65% of the individual miRNAs and a high combined power with superior sensitivity and specificity (AUC = 0.88 (0.78−0.99); 95% CI) of the 26 miRNA panel in discriminating TNBC between these populations. Subsequent miRNA target analysis revealed their involvement in the interconnected PI3K/AKT, MAPK and insulin signaling pathways. Additionally, three miRNAs of this panel were associated with early age at diagnosis. Altogether, these findings indicated that there are different patterns of miRNA expression between TNBC of AA and NHW women and that their mapping in genomic regions with high levels of CNAs is not merely physical, but biologically relevant to the TNBC phenotype. Once validated in distinct cohorts of AA women, this panel can potentially represent their intrinsic TNBC genome signature.

Motivation Transcription factors (TFs) are key regulators of gene expression, and can activate or repress multiple target genes, forming regulatory units, or regulons. Understanding downstream effects of these regulators includes evaluating how TFs cooperate or compete within regulatory networks. Here we present RTNduals, an R/Bioconductor package that implements a general method for analyzing pairs of regulons. Results RTNduals identifies a dual regulon when the number of targets shared between a pair of regulators is statistically significant. The package extends the RTN (Reconstruction of Transcriptional Networks) package, and uses RTN transcriptional networks to identify significant co-regulatory associations between regulons. The Supplementary Information reports two case studies for TFs using the METABRIC and TCGA breast cancer cohorts. Availability and implementation RTNduals is written in the R language, and is available from the Bioconductor project at http://bioconductor.org/packages/RTNduals/. Supplementary information Supplementary data are available at Bioinformatics online.

Osteoarthritis (OA) is the most prevalent chronic age-related arthritic disease that mainly affects the diarthrodial joints. Nevertheless, there is no treatment currently available that can effectively reduce symptoms or slow down or stop disease progression. The lack of disease-modifying therapies could be explained by the complex pathogenesis of OA, which is still not completely understood. Intertwined epigenetic mechanisms such as DNA methylation, histone modifications, and noncoding RNAs (ncRNAs) have been indicated as important cellular tools to maintain tissue homeostasis upon environmental challenges. The current review illustrates that dysfunctional epigenetic control mechanisms in the articular cartilage likely play an important role in driving OA pathophysiology.

Genome-wide and fine mapping studies have shown that more than 90% of genetic variants associated with autoimmune diseases (AID) are located in non-coding regions of the human genome and especially in regulatory sequences, including microRNAs (miRNA) target sites. MiRNAs are small endogenous noncoding RNAs that modulate gene expression at the post-transcriptional level. Single nucleotide polymorphisms (SNPs) located within the 3′ untranslated region of their target mRNAs (miRSNP) can alter miRNA binding sites. Yet, little is known about their effect on regulation by miRNA and the consequences for AID. Conversely, it is well known that two or more AID may share part of their genetic background. Here, we hypothesized that miRSNPs could be associated with more than one AID. To identify miRSNPs associated with AID, we integrated results from three different prediction tools (Polymirts, miRSNP, and miRSNPscore) using a naïve Bayes classifier approach to identify miRSNPs predicted to affect binding sites of miRNAs. Further, to detect miRSNPs associated with two or more AID, we integrated predictions with summary statistics from 12 AID studies. In addition, to prioritize miRSNPs, miRNAs and AID-associated target genes, we used public expression quantitative trait locus (eQTL) data and mRNA-seq and small RNA-seq data. We identified 34 miRNSPs associated with at least two AID. Furthermore, we found 86 miRNAs predicted to target 18 of the associated gene's mRNAs. Our integrative approach revealed new insights into miRNAs and AID associated target genes. Thus, it helped to prioritize AID noncoding risk SNPs that might be involved in the causal mechanisms, providing valuable information for further functional studies.

Although genome-wide association studies and fine mapping have identified 39 non-HLA loci associated with celiac disease (CD), it is difficult to pinpoint the functional variants and susceptibility genes in these loci. We applied integrative approaches to annotate and prioritize functional single nucleotide polymorphisms (SNPs), genes and pathways affected in CD. CD-associated SNPs were intersected with regulatory elements categorized by the ENCODE project to prioritize functional variants, while results from cis-expression quantitative trait loci (eQTL) mapping in 1469 blood samples were combined with co-expression analyses to prioritize causative genes. To identify the key cell types involved in CD, we performed pathway analysis on RNA-sequencing data from different immune cell populations and on publicly available expression data on non-immune tissues. We discovered that CD SNPs are significantly enriched in B-cell-specific enhancer regions, suggesting that, besides T-cell processes, B-cell responses play a major role in CD. By combining eQTL and co-expression analyses, we prioritized 43 susceptibility genes in 36 loci. Pathway and tissue-specific expression analyses on these genes suggested enrichment of CD genes in the Th1, Th2 and Th17 pathways, but also predicted a role for four genes in the intestinal barrier function. We also discovered an intricate transcriptional connectivity between CD susceptibility genes and interferon-gamma, a key effector in CD, despite the absence of CD-associated SNPs in the IFNG locus. Using systems biology, we prioritized the CD-associated functional SNPs and genes. By highlighting a role for B cells in CD, which classically has been described as a T-cell-driven disease, we offer new insights into the mechanisms and pathways underlying CD.

Many scientific experiments in Bioinformatics are executed as computational workflows. Frequently, it is necessary to re-run an experiment under the original circumstances in which it was run to recognize and validate it. Data provenance concerns the origin of data. Knowing the data source facilitates the understanding and analysis of the results, by detailing and documenting the history and the paths of the input data, from the beginning to the end of an experiment. Therefore, in this context, data provenance can be applied when experimenting traceability. This document presents AProvBio, an architecture that can perform the data provenance of scientific experiments in bioinformatics automatically, using the provenance data model PROV-DM and in a graph database. The architecture can perform the automatic provenance type prospectively, retrospectively and with user-defined data. Thus, the architecture stores and captures information obtained during the execution of the data generation processes with user-defined data information, such as features and versions of the programs used. A graph model, based on the PROV-DM model, was proposed for storing the data provenance. The PROV-DM can be represented by a graph, it allows for a more natural modelling, as well as expressing queries at a more natural level, and the implementation of efficient algorithms to perform specific operations.