Objectives The utilization of viral vectors to deliver genes of interest directly to meniscus cells and promote long-term modulation of gene expression may prove useful to enhance meniscus repair and regeneration. The objective of this study was to optimize and compare the potential of lentivirus (LV) and adeno-associated virus (AAV) to deliver transgenes to meniscus cells in both intact meniscus tissue and isolated primary cells in monolayer. Design Porcine meniscus tissue explants and primary meniscus cells in monolayer were transduced with LV or self-complementary AAV2 (scAAV2) encoding green fluorescent protein (GFP). Following transduction, explants were enzymatically digested to isolate meniscus cells, and monolayer cells were trypsinized. Isolated cells were analyzed by flow cytometry to determine percent transduction. Results LV and scAAV2 showed a high transduction efficiency in monolayer meniscus cells. scAAV2 was most effective at transducing cells within intact meniscus tissue but the efficiency was less than 20%. Outer zone meniscus cells were more readily transduced by both LV and scAAV2 than the inner zone cells. Higher virus titers and higher cell density resulted in improved transduction efficiency. Polybrene was necessary for the highest transduction efficiency with LV, but it reduced scAAV2 transduction. Conclusions Both LV and scAAV2 efficiently transduce primary meniscus cells but only scAAV2 can modestly transduce cells embedded in meniscus tissue. This work lays the foundation for viral gene transfer to be utilized to deliver bioactive transgenes or gene editing machinery, which can induce long-term and tunable expression of therapeutic proteins from tissue-engineered constructs for meniscus repair and regeneration.
Abstract Monoclonal gammopathy of undetermined significance (MGUS) is the most common plasma cell dyscrasia, present in ~3% of the population over 50yo. MGUS carries a 1% per year risk of malignant transformation for the rest of the affected individual’s life; long-term followup is recommended for all patients with MGUS. Different risk stratification models exist to evaluate potential for progression to malignancy. The Mayo risk model, published in 2005, uses the presence of 3 risk factors (abnormal free light chain (FLC) kappa/lambda ratio (KLr), M-spike ≥1.5 g/dL, non-IgG isotype) to confer a 3% per year risk of progression instead of the average 1%. For many years, the only FDA-approved measurement of FLC was the FreeLite assay (Binding Site), which uses polyclonal sheep antibodies. Recently, other FLC assays have become available in the US, including the Sebia FLC ELISA, which employs rabbit polyclonal antibodies. The assays have similar reference intervals (RI), however differences in analytical performance between the FreeLite and Sebia were previously reported. The objective of this study was to determine the performance of the Sebia FLC assay in the Mayo risk stratification model of MGUS patients for progression in comparison to FreeLite. Cryopreserved serum samples from a cohort of 923 MGUS patients with available long-term clinical followup (median follow-up time: 7.7years, range: 0.0 to 46.9) was used to measure FLC using Sebia ELISA on a DS2 automated platform (Dynex) and FreeLite on a Siemens BNII nephelometer. Passing-Bablok (P-B) regression and Spearman correlation were used to compare the KLr between assays. Cox proportional hazards models for progression to multiple myeloma or a related plasma cell malignancy were used to estimate the prognostic effect and ability to discriminate low and high risk of abnormal KLr for each assay. Analyses were carried out in R software. Correlation between Sebia and FreeLite KLr had a Spearman r = 0.796; P-B fit: Sebia KLr = 0.825*(FreeLite KLr) – 0.048, 95% CI of slope: 0.810-0.839). With FreeLite, 32.9% of patients had a KLr outside RI for the method. For Sebia, 48.0% of patients had a KLr outside the method specific RI. Despite the individual samples analytical disagreement, both assays showed similar clinical performance for risk stratification: Sebia abnormal KLr was associated with a hazard ratio (HR) of 2.77 (95%CI: 1.79-4.28 c-statistic=0.6505) for progression, while FreeLite abnormal KLr was associated with a HR of 3.31 (95%CI: 2.20-5.00, c-statistic=0.6529), and the difference in c-statistics was not statistically significant (p=0.93). The risk assessment is performed only once per patient, at the initial diagnosis of MGUS. The similarity in clinical performance between FreeLite and Sebia assays support the use of either method as a predictor for risk of progression for MGUS patients.
Orthopaedic research, and biomedical research in general, has made enormous strides to develop treatments for conditions long thought to be inevitable or untreatable; however, there is growing concern about the quality of published research. Considerable efforts have been made to improve overall research quality, integrity, and rigor, including meaningful proposals focused on transparency of reporting, appropriate use of statistics, and reporting of negative results. However, we believe that there is another key component to rigor and reproducibility that is not discussed sufficiently-analytical validation and quality control (QC). In this commentary, we discuss QC and method validation principles and practices that are systematically applied in the clinical laboratory setting to verify and monitor the analytical performance of quantitative assays, and the utility of applying similar practices to biochemical assays in the orthopaedic research setting. This commentary includes (1) recommendations for validation and QC practices, including examples of assay performance limitations uncovered by validation experiments performed in our laboratory, and (2) a description of an ongoing QC program developed to monitor the ongoing performance of commonly used assays in our lab. We hope that this commentary and the examples presented here will be thought-provoking and inspire further discussion and adaptation of analytical validation and QC procedures to advance our shared pursuit of high-quality, rigorous, and reproducible orthopaedic research.
Meniscus injuries are common and while surgical strategies have improved, there is a need for alternative therapeutics to improve long-term outcomes and prevent post-traumatic osteoarthritis. Current research efforts in regenerative therapies and tissue engineering are hindered by a lack of understanding of meniscus cell biology and a poorly defined meniscus cell phenotype. This study utilized bulk RNA-sequencing to identify unique and overlapping transcriptomic profiles in cartilage, inner and outer zone meniscus tissue, and passaged inner and outer zone meniscus cells. The greatest transcriptomic differences were identified when comparing meniscus tissue to passaged monolayer cells (> 4,600 differentially expressed genes (DEGs)) and meniscus tissue to cartilage (> 3,100 DEGs). While zonal differences exist within the meniscus tissue (205 DEGs between inner and outer zone meniscus tissue), meniscus resident cells are more similar to each other than to either cartilage or passaged monolayer meniscus cells. Additionally, we identified and validated LUM, PRRX1, and SNTB1 as potential markers for meniscus tissue and ACTA2, TAGLN, SFRP2, and FSTL1 as novel markers for meniscus cell dedifferentiation. Our data contribute significantly to the current characterization of meniscus cells and provide an important foundation for future work in meniscus cell biology, regenerative medicine, and tissue engineering.
Abstract Background Calculated LDL cholesterol (LDL-C) is a standard component of the lipid panel and an important risk factor in managing atherosclerotic cardiovascular disease (ASCVD). Due to the assumptions in the derivation of the Friedwald formula, fasting (≥8 hours) and triglyceride levels ≤400mg/dL have long been recommended. More recent data have shown that in most cases fasting has minimal effect on results, leading to the endorsement of non-fasting lipid panels for routine evaluation of ASCVD risk in clinical practice guidelines. Furthermore, newer equations (e.g. Sampson-NIH) allow for more accurate estimation of LDL-C even in the presence of hypertriglyceridemia. Mayo Clinic has implemented the Sampson-NIH LDL-C calculation and removed fasting/non-fasting designation from lipid panel orders. We hypothesized that the change to fasting designation would allow more afternoon draws for routine lipid panels and that increased non-fasting collections may increase triglyceride levels, but that the Sampson-NIH equation would prevent bias in LDL-C estimation. In order to test these hypotheses, we analyzed patient data from 1 year prior and 1 year post-implementation. Methods Results of lipid panels performed for one year preceding (n=334,719) and one year after (n=381,804) removal of the fasting/non-fasting designation and implementation of Sampson-NIH equation were collected. Median, 10th, and 90th percentile of draw time, triglyceride, and LDL-C calculated by either Sampson-NIH or Friedwald formulas were compared by quantile regression. Results Draw times shifted post-implementation at the 10th percentile (7:06 vs. 7:10, p<0.0001), median (8:49 vs. 9:08, p<0.0001) and 90th (12:02 vs. 13:46, p<0.0001). No difference in median triglyceride measurement was observed between pre-and post-implementation (110mg/dL), but slight differences were observed in the 10th and 90th percentile values (60 vs 59mg/dL and 224 vs 229mg/dL, p<0.0001). No difference was observed in 10th, 50th, or 90th percentile LDL values when calculated by Sampson-NIH equation (56, 99, 153mg/dL); however, if the Friedwald formula is used, a slight shift is observed in the 10th and 50th percentile LDL values (54 vs. 53, 97 vs. 96; p<0.0001) but not the 90th (150mg/dL). Conclusions Changing to the Sampson/NIH formula for LDL-C and removing fasting vs. non-fasting designation from routine lipid panels had minimal effect on reported triglyceride and LDL-C values, while allowing increased flexibility in draw time and reporting of LDL-C on patients with triglycerides ≥400mg/dL. Patients with TG ≥400mg/dL represented 1.7% of the dataset overall, including 5,387 patients before the change in which LDL-C could not be reported and 6,697 patients in the year post-implementation for whom LDL-C was reported based on the Sampson-NIH formula. Using an equation that is robust in patients with elevated triglyceride levels and removing fasting requirements from routine lipid panels allows greater flexibility and convenience for patients while allowing for more even distribution of phlebotomy workload and reporting of LDL-C results for patients with hypertriglyceridemia without evidence of clinically significant bias in reported results.
Meniscus injuries are common and a major cause of long-term joint degeneration and disability. Current treatment options are limited, so novel regenerative therapies or tissue engineering strategies are urgently needed. The development of new therapies is hindered by a lack of knowledge regarding the cellular biology of the meniscus and a lack of well-established methods for studying meniscus cells in vitro. The goals of this study were to (1) establish baseline expression profiles and dedifferentiation patterns of inner and outer zone primary meniscus cells, and (2) evaluate the utility of poly(ethylene glycol) diacrylate (PEGDA) and gelatin methacrylate (GelMA) polymer hydrogels to reverse dedifferentiation trends for long-term meniscus cell culture. Using reverse transcription-quantitative polymerase chain reaction, we measured expression levels of putative meniscus phenotype marker genes in freshly isolated meniscus tissue, tissue explant culture, and monolayer culture of inner and outer zone meniscus cells from porcine knees to establish baseline dedifferentiation characteristics, and then compared these expression levels to PEGDA/GelMA embedded passaged meniscus cells. COL1A1 showed robust upregulation, while CHAD, CILP, and COMP showed downregulation with monolayer culture. Expression levels of COL2A1, ACAN, and SOX9 were surprisingly similar between inner and outer zone tissue and were found to be less sensitive as markers of dedifferentiation. When embedded in PEGDA/GelMA hydrogels, expression levels of meniscus cell phenotype genes were significantly modulated by varying the ratio of polymer components, allowing these materials to be tuned for phenotype restoration, meniscus cell culture, and tissue engineering applications.
Abstract Background New immunoglobulin free light chain (FLC) assays are available. Despite analytical differences, it seems possible to use free light chain ratios (FLCr) generated by different assays and apply similar cut-points for the diagnosis of multiple myeloma. It is still unknown if we can use different assays for risk stratification of patients with monoclonal gammopathy of undetermined significance (MGUS). Methods Patients diagnosed with MGUS (N = 923) had FLC tested using a nephelometric FreeLite (Binding Site) assay on BNII instruments (Siemens) and a Sebia FLC assay (Sebia) on a DS2 ELISA analyzer (Dynex). Patients were followed up for progression to any plasma cell dyscrasia (PCD) for several decades. The Mayo MGUS risk stratification model for progression was assessed with both assays (M-spike >1.5 g/dL; non-IgG isotype and abnormal FLCr), using package insert reference intervals (RI) and a new metric called principal component 2 (PC2). Results There were 94 events of progression to PCD in the cohort during a median of 38 years of follow-up. Freelite and Sebia FLC showed similar hazard ratios in the risk models for elevated FLCr. An alternative clinical decision point lower than the package insert RI was evaluated for the Sebia assay, which improved risk stratification for patients with a low FLCr. The PC2 metric showed similar performance to the FLCr in models, without superior benefit. Conclusions The Sebia ELISA-based FLC assay can be employed in an MGUS risk stratification model with similar performance to the original 2005 risk stratification model using the FreeLite assay.
Meniscus injuries are highly prevalent, and both meniscus injury and subsequent surgery are linked to the development of post-traumatic osteoarthritis (PTOA). Although the pathogenesis of PTOA remains poorly understood, the inflammatory cytokine IL-1 is elevated in synovial fluid following acute knee injuries and causes degradation of meniscus tissue and inhibits meniscus repair. Dynamic mechanical compression of meniscus tissue improves integrative meniscus repair in the presence of IL-1 and dynamic tensile strain modulates the response of meniscus cells to IL-1. Despite the promising observed effects of physiologic mechanical loading on suppressing inflammatory responses of meniscus cells, there is a lack of knowledge on the global effects of loading on meniscus transcriptomic profiles. In this study, we compared two established models of physiologic mechanical stimulation, dynamic compression of tissue explants and cyclic tensile stretch of isolated meniscus cells, to identify conserved responses to mechanical loading. RNA sequencing was performed on loaded and unloaded meniscus tissue or isolated cells from inner and outer zones, with and without IL-1. Overall, results from both models showed significant modulation of inflammation-related pathways with mechanical stimulation. Anti-inflammatory effects of loading were well-conserved between the tissue compression and cell stretch models for inner zone; however, the cell stretch model resulted in a larger number of differentially regulated genes. Our findings on the global transcriptomic profiles of two models of mechanical stimulation lay the groundwork for future mechanistic studies of meniscus mechanotransduction, which may lead to the discovery of novel therapeutic targets for the treatment of meniscus injuries.
