Cell Painting images offer valuable insights into a cell's state and enable many biological applications, but publicly available arrayed datasets only include hundreds of genes perturbed. The JUMP Cell Painting Consortium perturbed roughly 75% of the protein-coding genome in human U-2 OS cells, generating a rich resource of single-cell images and extracted features. These profiles capture the phenotypic impacts of perturbing 15,243 human genes, including overexpressing 12,609 genes (using open reading frames) and knocking out 7,975 genes (using CRISPR-Cas9). Here we mitigated technical artifacts by rigorously evaluating data processing options and validated the dataset's robustness and biological relevance. Analysis of phenotypic profiles revealed previously undiscovered gene clusters and functional relationships, including those associated with mitochondrial function, cancer and neural processes. The JUMP Cell Painting genetic dataset is a valuable resource for exploring gene relationships and uncovering previously unknown functions.

Image-based profiling has emerged as a powerful technology for various steps in basic biological and pharmaceutical discovery, but the community has lacked a large, public reference set of data from chemical and genetic perturbations. Here we present data generated by the Joint Undertaking for Morphological Profiling (JUMP)-Cell Painting Consortium, a collaboration between 10 pharmaceutical companies, six supporting technology companies, and two non-profit partners. When completed, the dataset will contain images and profiles from the Cell Painting assay for over 116,750 unique compounds, over-expression of 12,602 genes, and knockout of 7,975 genes using CRISPR-Cas9, all in human osteosarcoma cells (U2OS). The dataset is estimated to be 115 TB in size and capturing 1.6 billion cells and their single-cell profiles. File quality control and upload is underway and will be completed over the coming months at the Cell Painting Gallery: https://registry.opendata.aws/cellpainting-gallery . A portal to visualize a subset of the data is available at https://phenaid.ardigen.com/jumpcpexplorer/ .

Functional genomic screening with CRISPR has provided a powerful and precise new way to interrogate the phenotypic consequences of gene manipulation in high-throughput, unbiased analyses. However, some experimental paradigms prove especially challenging and require carefully and appropriately adapted screening approaches. In particular, negative selection (or sensitivity) screening, often the most experimentally desirable modality of screening, has remained a challenge in drug discovery. Here we assess whether our new, modular genome-wide pooled CRISPR library can improve negative selection CRISPR screening and add utility throughout the drug development pipeline. Our pooled library is split into three parts, allowing it to be scaled to accommodate the experimental challenges encountered during drug development, such as target identification using unlimited cell numbers compared with target identification studies for cell populations where cell numbers are limiting. To test our new library, we chose to look for drug-gene interactions using a well-described small molecule inhibitor targeting poly(ADP-ribose) polymerase 1 (PARP1), and in particular to identify genes which sensitise cells to this drug. We simulate hit identification and performance using each library partition and support these findings through orthogonal drug combination cell panel screening. We also compare our data with a recently published CRISPR sensitivity dataset obtained using the same PARP1 inhibitor. Overall, our data indicate that generating a comprehensive CRISPR knockout screening library where the number of guides can be scaled to suit the biological question being addressed allows a library to have multiple uses throughout the drug development pipeline, and that initial validation of hits can be achieved through high-throughput cell panels screens where clinical grade chemical or biological matter exist.

Genetic screens have long been used as an approach to identify and validate new targets for drug discovery. The vast majority of these have been carried out in cell lines: mostly cancer cell lines. However, with improvements in tissue culture techniques, the increasing interest in using the immune system to tackle disease and the discovery of CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)-Cas9 mediated genome editing, screening primary cells that have not been subverted by transformation into immortal lines, is both appealing and feasible. We have successfully carried out a CRISPR-Cas9 screen in primary T cells using a combined lentivirus and electroporation protocol. Freshly isolated primary T cells are stimulated with anti-CD3 and anti-CD28 antibodies and then transduced with a pooled sgRNA library. After antibiotic selection, T cells successfully transduced with sgRNAs are electroporated to introduce Cas9 mRNA. We chose to validate this approach by carrying out a screen similar to that published by Birsoy et al., 2015, in which they ran a CRISPR-Cas9 screen in Jurkat T cells in the presence and absence of the electron transport chain inhibitor phenformin. In our screen, we exposed the CRISPR-Cas9 edited pool of primary T cells to a dose of phenformin that resulted in growth inhibition to a similar degree to that used by Birsoy and colleagues. Our data are in agreement with the published screen, showing that loss of the cytosolic aspartate aminotransferase GOT1 sensitises primary T cells to phenformin. We took multiple time points in our primary T cell screen and used T cells isolated from three different donors, allowing for the analysis of guide drop-out kinetics and reproducibility between donors. We anticipate that these data will be useful in building more complex screens that assess T cell biology in the presence of additional cells, such as myeloid derived suppressor cells (MDSCs). With a view to this, we have also carried out an arrayed siRNA screen in MDSCs to look for genes that when knocked down reduce the capacity of MDSCs to inhibit T cell proliferation. The endpoint for this screen is based on co-culture of siRNA transfected MDSCs with proliferating primary T cells. Using this complex data set, we have identified several potential targets, which when validated could provide new therapeutic targets through which the immunosuppressive nature of MDSCs in the tumour microenvironment can be mitigated. Birsoy, K., et al. (2015) http://dx.doi.org/10.1016/j.cell.2015.07.016 Citation Format: Bronwyn Joubert, Cristina Ghirelli, Isabelle Nett, John Prime, Glynn Martin, Jonathan Moore, Benedict Cross, Nicola J. McCarthy. RNA-based screens in primary human immune cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1213.

Introduction The direct anterior approach for total hip replacements has reported advantages of improved early function and muscle preservation. In an effort to improve healing and cosmesis, a change in the orientation of the incision has been proposed. Traditionally, the skin incision is in-line with the tensor fasciae latae muscle belly. The bikini incision is orthogonal to this orientation. The hypothesis was that muscle damage would be increased by using the bikini incision. Methods A traditional or bikini incision was performed on 18 cadaveric hips. On each of the 9 specimens, the traditional incision was performed on 1 side, and a bikini incision on the contralateral hip, with an even distribution of right or left side. Blinded anatomists performed the hip dissections, and assessed for muscle damage as well as for damage to the lateral femoral cutaneous nerve. Results No difference in muscle damage was identified in the tensor fasciae latae between muscle groups. Muscle damage was very minimal to the gluteus medius and minimus. Damage to the lateral femoral cutaneous nerve occurred equally for both the bikini and traditional skin incisions. Conclusions The bikini incision for the direct anterior approach to the hip can be performed safely, with no increase in muscle damage or damage to the lateral femoral cutaneous nerve compared to the traditional incision.

Objective: To identify novel biomarker(s) for knee osteoarthritis (OA) using a metabolomics approach.Method: We utilized a two-stage case-control study design. Plasma samples were collected from knee OA patients and healthy controls after 8-h fasting and metabolically profiled using a targeted metabolomics assay kit. Linear regression was used to identify novel metabolic markers for OA. Receiver operating characteristic (ROC) analysis was used to examine diagnostic values. Gene expression analysis was performed on human cartilage to explore the potential mechanism for the novel OA marker(s).Results: Sixty-four knee OA patients and 45 controls were included in the discovery stage and 72 knee OA patients and 76 age and sex matched controls were included in the validation stage. We identified and confirmed six metabolites that were significantly associated with knee OA, of which arginine was the most significant metabolite (P < 3.5 x 10(-13) ) with knee OA patients having on average 69 mu M lower than that in controls. ROC analysis showed that arginine had the greatest diagnostic value with area under the curve (AUC) of 0.984. The optimal cutoff of arginine concentration was 57 mM with 98.3% sensitivity and 89% specificity. The depletion of arginine in OA patients was most likely due to the over activity of arginine to ornithine pathway, leading to imbalance between cartilage repair and degradation.Conclusion: Arginine is significantly depleted in refractory knee OA patients. Further studies within a longitudinal setting are required to examine whether arginine can predict early OA changes. (c) 2015 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

This study was to investigate how OA patients with metabolic syndrome (MetS) are different metabolically from OA patients without MetS components and healthy individuals. A two-stage case–control study design was utilized. Synovial fluid (SF) and plasma samples were collected from patients undergoing total knee joint replacement due to primary OA and healthy controls (only plasma) and metabolically profiled using UPLC-MS coupled with assay kit which measures 186 metabolites. Orthogonal projection to latent structure-discriminant analysis and linear regression were used to identify metabolic markers for discriminating OA patients with MetS components from those without and healthy individuals. 54 paired SF and plasma samples from knee OA patients and 30 plasma samples from healthy controls were included in the discovery stage, and 143 plasma samples (72 from knee OA patients and 71 from the age, sex, and BMI matched controls) were included in the validation stage. OA patients with MetS can be clearly discriminated from OA patients without MetS based on the metabolite profiles of both SF and plasma and the separation appeared to be driven by type 2 diabetes but not obesity, hypertension, or dyslipidemia. When compared with OA patients with diabetes, OA without diabetes, and healthy controls, phosphatidylcholine acyl-alkyl C34:3 (PC ae C34:3) and phosphatidylcholine acyl-alkyl C36:3 (PC ae C36:3) were identified and confirmed to be associated with the concurrence of OA and diabetes (all p < 0.003). The study demonstrated that altered phosphatidylcholine metabolism was associated with both OA and diabetes mellitus.

Purpose: The potential cost savings of single-stage bilateral total hip arthroplasty (THA) are unclear, and the risks associated with it are not well defined. We sought to compare the costs and perioperative complications of single-stage bilateral THA via the direct anterior approach (DAA) to a two-stage bilateral protocol.Methods: We retrospectively reviewed patients who underwent a single-stage bilateral DAA THA and compared them to a two-stage THA group. We conducted a cost analysis from both the hospital perspective and the Ministry of Health (MOH) perspective.Results: 24 patients were included in this study. The 2 groups were similar in age (58.9 vs 63.9 yrs), height (169.2 vs 170.9 cm), weight (80.2 vs 78.6 kg), BMI (27.9 vs 26.3 kg/m(2)), ASA score (2.2 vs 2.2), and CCI score (2.3 vs 2.9). The mean cost per patient from the hospital perspective for the single-stage group was $10,728.13 (SD = 621.46) compared to $12,670.63 (SD = 519.72) for the two-stage group (Mean Difference = $1,942.50, 95% CI = $1,457.49 to $2,427.51, p<0.001). Similarly, from the MOH perspective, the cost for the single-stage group was $12,552.34 (SD = 644.93) compared to $14,740.58 (SD = 598.07) for the two-stage group (Mean Difference = $2,188.24, 95% CI = $1,661.67 to $2,714.81, p<0.001). There were no significant differences in complication rate between groups. The largest percent of total cost savings from a hospital perspective was attributed to cost of operating room staff and OR set-up (55%).Conclusions: Our results suggest that single-stage bilateral DAA THA results in significant cost savings compared to two-stage DAA THA.

OBJECTIVE:To identify novel biomarker(s) for predicting advanced knee OA.METHODS:Study participants were derived from the Newfoundland Osteoarthritis Study and the Tasmania Older Adult Cohort Study. All knee OA cases were patients who underwent total knee replacement (TKR) due to primary OA. Metabolic profiling was performed on fasting plasma. Four thousand and eighteen plasma metabolite ratios that were highly correlated with that in SF in our previous study were generated as surrogates for joint metabolism.RESULTS:The discovery cohort included 64 TKR cases and 45 controls and the replication cohorts included a cross-sectional cohort of 72 TKR cases and 76 controls and a longitudinal cohort of 158 subjects, of whom 36 underwent TKR during the 10-year follow-up period. We confirmed the previously reported association of the branched chain amino acids to histidine ratio with advanced knee OA (P = 9.3 × 10(-7)) and identified a novel metabolic marker-the lysophosphatidylcholines (lysoPCs) to phosphatidylcholines (PCs) ratio-that was associated with advanced knee OA (P = 1.5 × 10(-7)) after adjustment for age, sex and BMI. When the subjects of the longitudinal cohort were categorized into two groups based on the optimal cut-off of the ratio of 0.09, we found the subjects with the ratio ⩾0.09 were 2.3 times more likely to undergo TKR than those with the ratio <0.09 during the 10-year follow-up (95% CI: 1.2, 4.3, P = 0.02).CONCLUSION:We identified the ratio of lysoPCs to PCs as a novel metabolic marker for predicting advanced knee OA. Further studies are required to examine whether this ratio can predict early OA change.

Purpose: We previously reported that SMAD3 was associated with the total burden of radiographic ‎osteoarthritis (OA). SMAD3 is a mediator of TGF-β signalling pathway that is known to be ‎involved in the cartilage maintenance and repair. SMAD3 knocked-out mice are deficient for ‎Collagen and Aggrecan, and develop OA-like features in the joints. The aim of the present study ‎was to investigate the SMAD3 gene expression in osteoarthritic and healthy human cartilage and ‎to examine whether the gene expression is regulated by the promoter DNA methylation.‎ Methods: Osteoarthritic cartilage samples were collected from patients who underwent total hip/knee joint ‎replacement surgery due to primary OA. Healthy cartilage samples were obtained from patients ‎with hip fracture without any evidence of hip OA. DNA and RNA were extracted from the ‎cartilage samples using Qiagen's AllPrep DNA/RNA Mini Kit. Quantitative PCR experiment ‎was done using ABI-7500 real time PCR system to measure RNA expression after cDNA ‎synthesis by ThermoScript cDNA synthesis kit. DNA Methylation was assayed by Sequonom's ‎EpiTYPER after DNA bisulphate conversion using Qiagen's EpiTect Bisulfite Kit. Mann-‎Whitney test was utilized to examine the association between OA cases and controls for SMAD3 ‎expression and its promoter DNA methylation levels. Spearman's rank correlation analysis was ‎performed to examine the association between the promoter methylation and gene expression. A ‎P-value less than 0.05 was considered as significant. ‎ Results: A total of 49 OA patients (38 hip OA and 11 knee OA) and 51 controls were included in the ‎study. Mean age was 64.4 in OA patients and 78.7 in controls. Four CpG sites, located ∼450bp ‎upstream of the first SMAD3 exon, were assayed, and we found no difference in methylation ‎between OA cases and controls after adjusting for age. The expression experiment was ‎performed for 38 patients with OA (32 hips and 6 knees) and 28 healthy controls, and we found ‎that the SMAD3 gene was expressed in OA cartilage on average 1.8 times higher than controls ‎‎(p=0.0005). Similar results were obtained when we looked at hip and knee OA separately ‎‎(p=0.01). We found no association between SMAD3 expression and the methylation at the ‎promoter region of the gene. ‎ Conclusions: Our study demonstrated that SMAD3 is up-regulated in OA. This up-regulation, however, cannot ‎be explained by the changes in the promoter DNA methylation. Given that TGF-β/SMAD3 ‎pathway may play a protective role in the cartilage, the up-regulation of SMAD3 is more likely ‎due to the consequence of OA, thus reflecting repairing activity stimulated by the cartilage lesion ‎in OA. ‎

Objective.To compare SMAD3 gene expression between human osteoarthritic and healthy cartilage and to examine whether expression is regulated by the promoter DNA methylation of the gene.Methods.Human cartilage samples were collected from patients undergoing total hip/knee joint replacement surgery due to primary osteoarthritis (OA), and from patients with hip fractures as controls. DNA/RNA was extracted from the cartilage tissues. Real-time quantitative PCR was performed to measure gene expression, and Sequenom EpiTyper was used to assay DNA methylation. Mann-Whitney test was used to compare the methylation and expression levels between OA cases and controls. Spearman rank correlation coefficient was calculated to examine the association between the methylation and gene expression.Results.A total of 58 patients with OA (36 women, 22 men; mean age 64 ± 9 yrs) and 55 controls (43 women, 12 men; mean age 79 ± 10 yrs) were studied. SMAD3 expression was on average 83% higher in OA cartilage than in controls (p = 0.0005). No difference was observed for DNA methylation levels in the SMAD3 promoter region between OA cases and controls. No correlation was found between SMAD3 expression and promoter DNA methylation.Conclusion.Our study demonstrates that SMAD3 is significantly overexpressed in OA. This overexpression cannot be explained by DNA methylation in the promoter region. The results suggest that the transforming growth factor-β/SMAD3 pathway may be overactivated in OA cartilage and has potential in developing targeted therapies for OA.

Background: Evidence suggests that epigenetics plays a role in osteoarthrits (OA). The aim of the study was to describethe genome wide DNA methylation changes in hip and knee OA and identify novel genes and pathwaysinvolved in OA by comparing the DNA methylome of the hip and knee osteoarthritic cartilage tissues withthose of OA-free individuals.Methods: Cartilage samples were collected from hip or knee joint replacement patients either due to primary OA or hip fractures as controls. DNA was extracted from the collected cartilage and assayed by Illumina Infinium HumanMethylation450 BeadChip array, which allows for the analysis of >480,000 CpG sites. Student T-test was conducted for each CpG site and those sites with at least 10 % methylation difference and a p value <0.0005 were defined as differentially methylated regions (DMRs) for OA. A sub-analysis was also done for hip and knee OA separately. DAVID v6.7 was used for the functional annotation clustering of the DMR genes. Clustering analysis was done using multiple dimensional scaling and hierarchical clustering methods.Results: The study included 5 patients with hip OA, 6 patients with knee OA and 7 hip cartilage samples from OA-free individuals. The comparisons of hip, knee and combined hip/knee OA patients with controls resulted in 26, 72, and 103 DMRs, respectively. The comparison between hip and knee OA revealed 67 DMRs. The overall number of the sites after considering the overlaps was 239, among which 151 sites were annotated to 145 genes. One-fifth of these genes were reported in previous studies. The functional annotation clustering of the identified genes revealed clusters significantly enriched in skeletal system morphogenesis and development. The analysis revealed significant difference among OA and OA-free cartilage, but less different between hip OA and knee OA.Conclusions: We found that a number of CpG sites and genes across the genome were differentially methylated in OA patients, a remarkable portion of which seem to be involved in potential etiologic mechanisms of OA. Genes involved in skeletal developmental pathways and embryonic organ morphogenesis may be a potential area for further OA studies.

In vitro and animal model of osteoarthritis (OA) studies suggest that TGF-β signalling is involved in OA, but human data is limited. We undertook this study to elucidate the role of TGF-β signalling pathway in OA by comparing the expression levels of TGFB1 and BMP2 as ligands, SMAD3 as an intracellular mediator, and MMP13 as a targeted gene between human osteoarthritic and healthy cartilage.

Purpose: Osteoarthritis (OA) is a progressive, chronic condition characterized by focal damage to articular cartilage, chronic inflammation and alterations to the extracellular matrix, leading to pain, stiffness and a loss of physical function. OA's initiation and progression are caused by various environmental and genetic factors. One common factor believed to play a significant role in OA is environmentally-triggered epigenetic alterations, specifically DNA methylation. Of particular interest in the study of OA is the loss and degradation of collagen caused by matrix metalloproteinase – 13 (MMP-13). Several studies have examined the association between OA and methylation in MMP-13. Furthermore, MMP-13 has been suggested as a potential therapeutic target for OA treatment. However, these studies have reported conflicting results. The aim of this study was to determine the gene expression and potential corresponding methylation levels in the promoter region of MMP-13 in patients diagnosed with hip OA versus healthy controls. Methods: A hospital-based case-control study design was utilized. Cartilage samples were collected from patients undergoing total hip replacement due to primary hip OA and hip fracture patients who required a hemiarthroplasty but did not have evidence of OA. RNA and DNA were extracted from the same cartilage samples. MMP-13 expression was examined from RNA using real-time quantitative PCR. Using DNA, methylation levels of seven CpG sites located in the promoter region of MMP-13 (up to 600 bp from the first exon) were assayed using Sequenom EpiTYPER. This method uses mass spectrometry to separate methylated and non-methylated DNA segments into distinct signals. Results: A total of 38 subjects were included in the analysis, 23 patients diagnosed with hip OA (13 females, 10 males) and 15 healthy controls (12 females, 3 males). The mean age was 63 in OA cases and 77 in controls. Our gene expression analysis indicated that OA patients had a five-fold increase in MMP-13 expression compared to controls. This difference was statistically significant with a p-value of 0.0095, based on student's T-test. Due to the skewed distribution of the gene expression data, this significance was verified using Mann-Whitney test. Among the 7 CpG sites in the MMP-13 promoter region analyzed, we found one site with significantly altered methylation pattern in OA patients versus controls. The CpG site 218 bp upstream of the first exon showed a trend towards lower methylation in OA patients at an average of 44% versus controls at 57%, with a p-value of 0.009. This methylation level was significantly correlated with gene expression in OA cases, with a correlation coefficient of 0.55 and a corresponding p-value of 0.0068 based on Spearman's rank correlation. This correlation was not seen in controls however. Furthermore, we found that methylation was confounded by age with a trend toward increasing methylation corresponding with advancing age. Conclusions: This study demonstrates a significant difference in the gene expression levels of MMP-13, with OA patients having a higher level of MMP-13 expression. In addition, a hypomethylated CpG site in the promoter region of MMP-13 was found in OA patients versus controls, implicating this CpG site as one potential regulatory site for MMP-13 gene expression. The finding was confounded by age, indicating that methylation at this site could be a potential intermediate factor in advancing OA. We hypothesize that increasing methylation with advancing age in MMP-13 may serve as a protective mechanism to prevent collagen degradation. A validation study is needed to confirm the findings.

Purpose: Our previous study found that osteoarthritis (OA) consisted of metabolically distinct subgroups and one of the subgroups tended to have a high prevalence of metabolic diseases (BMJ Open 2014). The purpose of the current study was to identify novel markers for concurrence of OA and metabolic diseases by using a metabolomics approach. Methods: Synovial fluid and plasma samples were collected from patients undergoing total knee joint replacements due to primary OA. Plasma samples of healthy controls were also collected. Medical information on hypertension, dyslipidemia, high-BMI and diabetes were obtained by self-administered questionnaires and confirmed by their medical records. Metabolic profiling was performed on all the collected samples using UPLC-MS coupled with mixed standards assay kits to identify novel markers for OA and concurrence of OA and metabolic diseases. Results: 64 OA patients and 45 healthy people were included in the study. Mean age were 65.6 ± 7.0 and 48.6± 6.3 years, respectively, and the mean BMI were 33.9 ± 7.3 and 30.1±6.7 kg/m2, respectively. 168 metabolite concentrations, including 40 acylcarnitines (including free carnitine), 20 amino acids, 9 biogenic amines, 87 glycerophospholipids, 11 sphingolipids and 1 hexose (>90% glucose), were quantified separately in synovial fluid and plasma samples. OPLS-DA analysis showed that diabetes OA patients could be clearly separated from non-diabetes OA patients based on synovial metabolite concentrations. Similar pattern was seen when plasma metabolite concentrations were used. 13 differential metabolites were identified between diabetes and non-diabetes OA patients from synovial analysis, of which 11 metabolites were the same as the differential metabolites identified in plasma analysis. The comparisons of these 11 metabolite plasma concentrations between diabetes OA, non-diabetes OA, and healthy controls found that 5 metabolic markers, citrulline, arginine, leucine, PC ae C34:3 and PC ae C36:3, were statistically and significantly different between these three groups with a linear trend (all p <0.003). Leucine has been associated with knee OA in our previous study (ARD 2010). In addition, 3 metabolite concentrations, proline, alanine and acetyornithine, were statistically different between diabetes OA patients and healthy controls (p < 0.0001). Conclusions: We confirmed our previous findings and further identified 7 novel metabolic markers for OA and concurrence of OA and diabetes mellitus, suggesting OA may have different pathogenesis when concurring with diabetes mellitus.

Objective.To investigate the relationship between plasma and synovial fluid (SF) metabolite concentrations in patients with osteoarthritis (OA).Methods.Blood plasma and SF samples were collected from patients with primary knee OA undergoing total knee arthroplasty. Metabolic profiling was performed by electrospray ionization tandem mass spectrometry using the AbsoluteIDQ kit. The profiling yielded 168 metabolite concentrations. Correlation analysis between SF and plasma metabolite concentrations was done on absolute concentrations as well as metabolite concentration ratios using Spearman’s rank correlation (ρ) method.Results.A total of 69 patients with knee OA were included, 30 men and 39 women, with an average age of 66 ± 8 years. For the absolute metabolite concentrations, the average ρ was 0.23 ± 0.13. Only 8 out of 168 metabolite concentrations had a ρ ≥ 0.45, with a p value ≤ 2.98 × 10−4, statistically significant after correcting multiple testing with the Bonferroni method. For the metabolite ratios (n = 28,056), the average ρ was 0.29 ± 0.20. There were 4018 metabolite ratios with a ρ ≥ 0.52 and a p value ≤ 1.78 × 10−6, significant after correcting multiple testing. Sex-separate analyses found no difference in ρ between men and women. Similarly, there was no difference in ρ between people younger and older than 65 years.Conclusion.Correlation between blood plasma and SF metabolite concentrations are modest. Metabolite ratios, which are considered proxies for enzymatic reaction rates and have higher correlations, should be considered when using blood plasma as a surrogate of SF in OA biomarker identification.

Background A newly-described syndrome called Aneurysm-Osteoarthritis Syndrome (AOS) was recently reported. AOS presents with early onset osteoarthritis (OA) in multiple joints, together with aneurysms in major arteries, and is caused by rare mutations in SMAD3. Because of the similarity of AOS to idiopathic generalized OA (GOA), we hypothesized that SMAD3 is also associated with GOA and tested the hypothesis in a population-based cohort. Methods Study participants were derived from the Chingford study. Kellgren-Lawrence (KL) grades and the individual features of osteophytes and joint space narrowing (JSN) were scored from radiographs of hands, knees, hips, and lumbar spines. The total KL score, osteophyte score, and JSN score were calculated and used as indicators of the total burden of radiographic OA. Forty-one common SNPs within SMAD3 were genotyped using the Illumina HumanHap610Q array. Linear regression modelling was used to test the association between the total KL score, osteophyte score, and JSN score and each of the 41 SNPs, with adjustment for patient age and BMI. Permutation testing was used to control the false positive rate. Results A total of 609 individuals were included in the analysis. All were Caucasian females with a mean age of 60.9±5.8. We found that rs3825977, with a minor allele (T) frequency of 20%, in the last intron of SMAD3, was significantly associated with total KL score (β = 0.14, Ppermutation = 0.002). This association was stronger for the total JSN score (β = 0.19, Ppermutation = 0.002) than for total osteophyte score (β = 0.11, Ppermutation = 0.02). The T allele is associated with a 1.47-fold increased odds for people with 5 or more joints to be affected by radiographic OA (Ppermutation = 0.046). Conclusion We found that SMAD3 is significantly associated with the total burden of radiographic OA. Further studies are required to reveal the mechanism of the association.

Objective: Over 200 genes have been reported to be associated with osteoarthritis (OA), but most of them have not been replicated in an independent sample. Using the newly collected cohort from a genetically isolated population - the Newfoundland and Labrador population, we attempted to replicate 105 previously reported OAassociated SNPs. Methods: A case-control study design was utilized in this study. Patients undergoing total hip/knee joint replacements due to severe OA were collected as cases. A group of healthy individuals with no evidence of OA was used as control.105 SNPs were genotyped either by Sequenom iPLEX Gold method or Illumina GWAS genotyping platform. The cross-reference was performed on both methods in a subset of samples for genotyping quality control. A logistic regression model was used to test for associations between the SNPs and OA. Results: A total of 126 cases and 348 healthy controls were included in the final analysis. OA Patients were on average 9 years older than healthy controls (p<0.0001), but there was no difference in BMI. We were unable to replicate the previously reported associations. Two SNPs, rs2294995 (COL9A3), and rs1049007 (BMP2) showed an association with p<0.05, but the significance did not survive the Bonferroni multiple testing correction. Conclusion: A lack of replication might be due to study design, complexity of OA, method of OA ascertainment, populations studied, or false positives in the original publications. A study with larger sample is needed to confirm the two possible SNPs with OA.

OBJECTIVES:To identify metabolic markers that can classify patients with osteoarthritis (OA) into subgroups.DESIGN:A case-only study design was utilised.PARTICIPANTS:Patients were recruited from those who underwent total knee or hip replacement surgery due to primary OA between November 2011 and December 2013 in St. Clare's Mercy Hospital and Health Science Centre General Hospital in St. John's, capital of Newfoundland and Labrador (NL), Canada. 38 men and 42 women were included in the study. The mean age was 65.2±8.7 years.OUTCOME MEASURES:Synovial fluid samples were collected at the time of their joint surgeries. Metabolic profiling was performed on the synovial fluid samples by the targeted metabolomics approach, and various analytic methods were utilised to identify metabolic markers for classifying subgroups of patients with OA. Potential confounders such as age, sex, body mass index (BMI) and comorbidities were considered in the analysis.RESULTS:Two distinct patient groups, A and B, were clearly identified in the 80 patients with OA. Patients in group A had a significantly higher concentration on 37 of 39 acylcarnitines, but the free carnitine was significantly lower in their synovial fluids than in those of patients in group B. The latter group was further subdivided into two subgroups, that is, B1 and B2. The corresponding metabolites that contributed to the grouping were 86 metabolites including 75 glycerophospholipids (6 lysophosphatidylcholines, 69 phosphatidylcholines), 9 sphingolipids, 1 biogenic amine and 1 acylcarnitine. The grouping was not associated with any known confounders including age, sex, BMI and comorbidities. The possible biological processes involved in these clusters are carnitine, lipid and collagen metabolism, respectively.CONCLUSIONS:The study demonstrated that OA consists of metabolically distinct subgroups. Identification of these distinct subgroups will help to unravel the pathogenesis and develop targeted therapies for OA.