Three decades of advancements in osteoarthritis research: insights from transcriptomic, proteomic, and metabolomic studies

OBJECTIVE

Osteoarthritis (OA) is a complex disease involving contributions from both local joint tissues and systemic sources. Patient characteristics, encompassing sociodemographic and clinical variables, are intricately linked with OA rendering its understanding challenging. Technological advancements have allowed for a comprehensive analysis of transcripts, proteomes and metabolomes in OA tissues/fluids through omic analyses. The objective of this review is to highlight the advancements achieved by omic studies in enhancing our understanding of OA pathogenesis over the last three decades.

DESIGN

We conducted an extensive literature search focusing on transcriptomics, proteomics and metabolomics within the context of OA. Specifically, we explore how these technologies have identified individual transcripts, proteins, and metabolites, as well as distinctive endotype signatures from various body tissues or fluids of OA patients, including insights at the single-cell level, to advance our understanding of this highly complex disease.

RESULTS

Omic studies reveal the description of numerous individual molecules and molecular patterns within OA-associated tissues and fluids. This includes the identification of specific cell (sub)types and associated pathways that contribute to disease mechanisms. However, there remains a necessity to further advance these technologies to delineate the spatial organization of cellular subtypes and molecular patterns within OA-afflicted tissues.

CONCLUSIONS

Leveraging a multi-omics approach that integrates datasets from diverse molecular detection technologies, combined with patients' clinical and sociodemographic features, and molecular and regulatory networks, holds promise for identifying unique patient endophenotypes. This holistic approach can illuminate the heterogeneity among OA patients and, in turn, facilitate the development of tailored therapeutic interventions.

Identified senescence endotypes in aged cartilage are reflected in the blood metabolome

Heterogeneous accumulation of senescent cells expressing the senescence-associated secretory phenotype (SASP) affects tissue homeostasis which leads to diseases, such as osteoarthritis (OA). In this study, we set out to characterize heterogeneity of cellular senescence within aged articular cartilage and explored the presence of corresponding metabolic profiles in blood that could function as representative biomarkers. Hereto, we set out to perform cluster analyses, using a gene-set of 131 senescence genes (N = 57) in a previously established RNA sequencing dataset of aged articular cartilage and a generated metabolic dataset in overlapping blood samples. Using unsupervised hierarchical clustering and pathway analysis, we identified two robust cellular senescent endotypes. Endotype-1 was enriched for cell proliferating pathways, expressing forkhead box protein O4 (FOXO4), RB transcriptional corepressor like 2 (RBL2), and cyclin-dependent kinase inhibitor 1B (CDKN1B); the FOXO mediated cell cycle was identified as possible target for endotype-1 patients. Endotype-2 showed enriched inflammation-associated pathways, expressed by interleukin 6 (IL6), matrix metallopeptidase (MMP)1/3, and vascular endothelial growth factor (VEGF)C and SASP pathways were identified as possible targets for endotype-2 patients. Notably, plasma-based metabolic profiles in overlapping blood samples (N = 21) showed two corresponding metabolic clusters in blood. These non-invasive metabolic profiles could function as biomarkers for patient-tailored targeting of senescence in OA.

Allelic expression imbalance in articular cartilage and subchondral bone refined genome-wide association signals in osteoarthritis

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 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 2 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 = 1.7x10-4) and ILF3-DT (meta-φ = 0.6, FDR = 1.75x10-5). Moreover, 12 drugs were interacting with 7 genes displaying AEI, of which 7 drugs have been already approved.

CONCLUSIONS

By prioritizing proxy transcript SNPs that mark AEI in cartilage and/or subchondral bone at loci harboring 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.

Cripto favors chondrocyte hypertrophy via TGF-β SMAD1/5 signaling during development of osteoarthritis

Chondrocytes in mice developing osteoarthritis (OA) exhibit an aberrant response to the secreted cytokine transforming growth factor (TGF)‐β, consisting in a potentiation of intracellular signaling downstream of the transmembrane type I receptor kinase activin receptor‐like kinase (ALK)1 against canonical TGF‐β receptor ALK5‐mediated signaling. Unfortunately, the underlying mechanisms remain elusive. In order to identify novel druggable targets for OA, we aimed to investigate novel molecules regulating the ALK1/ALK5 balance in OA chondrocytes. We performed gene expression analysis of TGF‐β signaling modulators in joints from three different mouse models of OA and found an upregulated expression of the TGF‐β co‐receptor Cripto (Tdgf1), which was validated in murine and human cartilage OA samples at the protein level. In vitro and ex vivo, elevated expression of Cripto favors the hypertrophic differentiation of chondrocytes, eventually contributing to tissue calcification. Furthermore, we found that Cripto participates in a TGF‐β–ALK1–Cripto receptor complex in the plasma membrane, thereby inducing catabolic SMAD1/5 signaling in chondrocytes. In conclusion, we demonstrate that Cripto is expressed in OA and plays a functional role promoting chondrocyte hypertrophy, thereby becoming a novel potential therapeutic target in OA, for which there is no efficient cure or validated biomarker. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

FAIMS-MS might contribute to phosphopeptides identification in plasma

FAIMS interface is gaining popularity because of the impressive 100-fold signal to noise enhancement in addition to the recent coupling to the Orbitrap technology, the most important analyzer developed in the last 20 years. The selection of group of ions and effective removal of single-charged ones at particular compensation voltages increases around 50% the proteome coverage at expenses of lower peptides coverage. However, specific setting for phosphoproteome analysis is yet poorly described. Here we have found the maximum transmission for several tryptic phosphopeptides isolated from a single complex mixture and we have set an experimental method based on five compensation voltages partially different to the ones described previously, demonstrating the relevance of voltages higher than 47 V, with an increase of around 20% of unique phosphopeptides. Using this experimental setup two complex phosphoproteomes isolates (SH-SY5Y cell line and plasma) were analyzed and found increments of 50% on phosphopeptides identification with the proposed method with respect to a previous one, for the cell line extract. Meanwhile for plasma 109 of the detected phosphopeptides are found for first time in this body fluid, presumably due to the release of intracellular proteins. With this FAIMS setup, 60% of the proteins identified are classified as very low abundant proteins.

[Gossypibomas in neurosurgery]

INTRODUCTION

The term «gossypiboma» comes from the Latin gossypium, which refers to a genus of cotton plants, and from the Swahili word boma, which translates as «place of concealment». It may be mistaken for tumorous lesions or abscesses due to the way it is encapsulated, as evidenced in imaging examinations, and its variable and non-specific clinical features, which give rise to difficulty in its diagnosis and significant morbidity.

AIM

To synthesise the available evidence on the presence of gossypibomas during neurosurgical procedures.

DEVELOPMENT

A review was performed that included a search for articles in English and Spanish published in the last 15 years in PubMed, Ebsco Host, Embase, Mediclatina, Cochrane, Lilacs and Scopus, between January and June 2019, using the keywords «gossypiboma», «textiloma», «neurosurgery» and «neurosurgical procedures». In all, a total of 630 articles were found in the search, although, after selecting them by title and abstract, 22 case report articles were included for this review process. Altogether 36 individuals were identified, of whom 21 (58.3%) were women, and whose mean age was 56.1 years. Surgical sponges were observed as gossypibomas in 20 cases (55.6%).

CONCLUSIONS

Gossypiboma is a complication secondary to surgical procedures that presents fairly unspecific signs and symptoms. The time that elapses before it appears usually ranges from a few days to several years after surgery and is correlated with multiple medical and legal implications.

Exploring the QSAR's predictive truthfulness of the novel N-tuple discrete derivative indices on benchmark datasets

Graph derivative indices (GDIs) have recently been defined over N-atoms (N = 2, 3 and 4) simultaneously, which are based on the concept of derivatives in discrete mathematics (finite difference), metaphorical to the derivative concept in classical mathematical analysis. These molecular descriptors (MDs) codify topo-chemical and topo-structural information based on the concept of the derivative of a molecular graph with respect to a given event (S) over duplex, triplex and quadruplex relations of atoms (vertices). These GDIs have been successfully applied in the description of physicochemical properties like reactivity, solubility and chemical shift, among others, and in several comparative quantitative structure activity/property relationship (QSAR/QSPR) studies. Although satisfactory results have been obtained in previous modelling studies with the aforementioned indices, it is necessary to develop new, more rigorous analysis to assess the true predictive performance of the novel structure codification. So, in the present paper, an assessment and statistical validation of the performance of these novel approaches in QSAR studies are executed, as well as a comparison with those of other QSAR procedures reported in the literature. To achieve the main aim of this research, QSARs were developed on eight chemical datasets widely used as benchmarks in the evaluation/validation of several QSAR methods and/or many different MDs (fundamentally 3D MDs). Three to seven variable QSAR models were built for each chemical dataset, according to the original dissection into training/test sets. The models were developed by using multiple linear regression (MLR) coupled with a genetic algorithm as the feature wrapper selection technique in the MobyDigs software. Each family of GDIs (for duplex, triplex and quadruplex) behaves similarly in all modelling, although there were some exceptions. However, when all families were used in combination, the results achieved were quantitatively higher than those reported by other authors in similar experiments. Comparisons with respect to external correlation coefficients (q²_ext) revealed that the models based on GDIs possess superior predictive ability in seven of the eight datasets analysed, outperforming methodologies based on similar or more complex techniques and confirming the good predictive power of the obtained models. For the q²_ext values, the non-parametric comparison revealed significantly different results to those reported so far, which demonstrated that the models based on DIVATI's indices presented the best global performance and yielded significantly better predictions than the 12 0-3D QSAR procedures used in the comparison. Therefore, GDIs are suitable for structure codification of the molecules and constitute a good alternative to build QSARs for the prediction of physicochemical, biological and environmental endpoints.

Tissue-specific transcript annotation and expression profiling with complementary next-generation sequencing technologies

Next-generation sequencing is excellently suited to evaluate the abundance of mRNAs to study gene expression. Here we compare two alternative technologies, cap analysis of gene expression (CAGE) and serial analysis of gene expression (SAGE), for the same RNA samples. Along with quantifying gene expression levels, CAGE can be used to identify tissue-specific transcription start sites, while SAGE monitors 3′-end usage. We used both methods to get more insight into the transcriptional control of myogenesis, studying differential gene expression in differentiated and proliferating C2C12 myoblast cells with statistical evaluation of reproducibility and differential gene expression. Both CAGE and SAGE provided highly reproducible data (Pearson's correlations >0.92 among biological triplicates). With both methods we found around 10 000 genes expressed at levels 2 transcripts per million (0.3 copies per cell), with an overlap of 86%. We identified 4304 and 3846 genes differentially expressed between proliferating and differentiated C2C12 cells by CAGE and SAGE, respectively, with an overlap of 2144. We identified 196 novel regulatory regions with preferential use in proliferating or differentiated cells. Next-generation sequencing of CAGE and SAGE libraries provides consistent expression levels and can enrich current genome annotations with tissue-specific promoters and alternative 3′-UTR usage.

Bases para un programa de mejora de alpacas en la region altoandina de Huancavelica-Perú

El estudio se desarrolló en 544 alpacas Huacaya de color blanco localizadas en 19 centros de producción de la Región de Huancavelica, ubicadas un rango de altitud entre 4000 y 4800 msnm. Antes de la esquila se tomaron muestras del vellón de aproximadamente 20 g de la zona del costillar y posterior a ella se registró el peso de vellón grasiento (PVG), sexo, edad y unidad productiva de cada animal. El diámetro de fibra (DF), coeficiente de variación del diámetro de fibra (CVDF) y el factor de picazón (FP) fue determinado utilizando el Sirolan-Laserscan. En función a los datos obtenidos se realizó el planteamiento de un esquema de mejora y sobre ello se estimó la respuesta a la selección bajo distintos escenarios. Los promedios ±E.E. del PVG, DF, CVDF y FP fueron de 2300±39 g, 21,56±0,12 mm, 22,82±0,12% y 6,33 ± 0,30% respectivamente. El PVG y el DF muestran variaciones significativas (p

Inactivation of the p53 pathway in retinoblastoma

Most human tumours have genetic mutations in their Rb and p53 pathways, but retinoblastoma is thought to be an exception. Studies suggest that retinoblastomas, which initiate with mutations in the gene retinoblastoma 1 (RB1), bypass the p53 pathway because they arise from intrinsically death-resistant cells during retinal development. In contrast to this prevailing theory, here we show that the tumour surveillance pathway mediated by Arf, MDM2, MDMX and p53 is activated after loss of RB1 during retinogenesis. RB1-deficient retinoblasts undergo p53-mediated apoptosis and exit the cell cycle. Subsequently, amplification of the MDMX gene and increased expression of MDMX protein are strongly selected for during tumour progression as a mechanism to suppress the p53 response in RB1-deficient retinal cells. Our data provide evidence that the p53 pathway is inactivated in retinoblastoma and that this cancer does not originate from intrinsically death-resistant cells as previously thought. In addition, they support the idea that MDMX is a specific chemotherapeutic target for treating retinoblastoma.

[Enterobiasis in students from Ciudad Bolivar, Venezuela]

Enterobius vermicularis is a nematode with a peculiar biological cycle, thus requiring a special diagnostic technique. In order to determine the prevalence of E. vermicularis infection among schoolchildren in Ciudad Bolívar, Venezuela, 282 children aged 5-14 years old were evaluated between november 1995 and august 1996 by the Graham technique (three perianal swabs with adhesive cellulose tape). The prevalence of enterobiasis in the studied children was estimated 19.1% (54/282). There was no difference between sexes (P > 0.05), but there was a difference between ages (x2 = 13.8; 1.g. = 4), being the infection more frequent between 5 and 8 years. Symptoms were observed in 90.7% of the schoolchildren. Anal pruritus was the most common clinical finding (81.6%). Other less frequent manifestations were enuresis (28.6%) and vulvitis in girls (26.1%). This intestinal parasitosis occurs with high frequency among schoolchildren in Ciudad Bolívar with characteristic and identifiable symptoms in most cases. The Graham method must be used for its diagnosis. This test is not routinely performed in our laboratories unless specifically requested by the attending physician.