Methotrexate Polyglutamation in a Myasthenia Gravis Clinical Trial

Introduction. Methotrexate (MTX) is an immunosuppressive and anti-inflammatory drug used to treat rheumatoid arthritis (RA) and other autoimmune conditions. MTX is transported into cells, where glutamate moieties are added and is retained as methotrexate polyglutamates (MTXPGs). In the RA literature, it has been reported that the degree of polyglutamation correlates with the anti-inflammatory effect of MTX in RA. There are no prior studies evaluating the relationship between MTXPGs and myasthenia gravis (MG) outcome measures. The objective of this study was to assess the correlation between methotrexate (MTX) polyglutamates (MTXPGs) with Myasthenia Gravis (MG) outcome measures. Methods.xAn analysis was done of blood drawn from patients enrolled in the 12-month randomized, placebo-controlled study of MTX in MG study. Red blood cell MTXPGs were measured via ultraperformance liquid chromatography and tandem mass spectrometry. MTXPG was correlated to MG outcome measures using Spearman Correlation Coefficient. A two-group t-test was used to determine the difference in MTXPG based on clinical outcome responder definitions. Results. Twenty-one polyglutamate samples were analyzed of subjects on MTX while eight samples were analyzed from subjects on placebo. Pentaglutamate had the strongest correlation with the MG-ADL (0.99), while tetraglutamate had the strongest correlation with the QMG (0.54). Triglutamate had the strongest correlation with MGC (0.76). Conclusion. There were variable correlations between MTXPG1-5 and MG outcomes (rho range: 0.08 to 0.99). There are strong correlations between MTXPG and the MG-ADL, QMG, and MGC. Long chain methotrexate polyglutamates correlate better with MG outcomes

A Bayesian comparative effectiveness trial in action: developing a platform for multisite study adaptive randomization

A grant from the One-University Open Access Fund at the University of Kansas was used to defray the author's publication fees in this Open Access journal. The Open Access Fund, administered by librarians from the KU, KU Law, and KUMC libraries, is made possible by contributions from the offices of KU Provost, KU Vice Chancellor for Research & Graduate Studies, and KUMC Vice Chancellor for Research. For more information about the Open Access Fund, please see http://library.kumc.edu/authors-fund.xml.Background In the last few decades, the number of trials using Bayesian methods has grown rapidly. Publications prior to 1990 included only three clinical trials that used Bayesian methods, but that number quickly jumped to 19 in the 1990s and to 99 from 2000 to 2012. While this literature provides many examples of Bayesian Adaptive Designs (BAD), none of the papers that are available walks the reader through the detailed process of conducting a BAD. This paper fills that gap by describing the BAD process used for one comparative effectiveness trial (Patient Assisted Intervention for Neuropathy: Comparison of Treatment in Real Life Situations) that can be generalized for use by others. A BAD was chosen with efficiency in mind. Response-adaptive randomization allows the potential for substantially smaller sample sizes, and can provide faster conclusions about which treatment or treatments are most effective. An Internet-based electronic data capture tool, which features a randomization module, facilitated data capture across study sites and an in-house computation software program was developed to implement the response-adaptive randomization. Results A process for adapting randomization with minimal interruption to study sites was developed. A new randomization table can be generated quickly and can be seamlessly integrated in the data capture tool with minimal interruption to study sites. Conclusion This manuscript is the first to detail the technical process used to evaluate a multisite comparative effectiveness trial using adaptive randomization. An important opportunity for the application of Bayesian trials is in comparative effectiveness trials. The specific case study presented in this paper can be used as a model for conducting future clinical trials using a combination of statistical software and a web-based application. Trial registration ClinicalTrials.gov Identifier: NCT02260388, registered on 6 October 201

Database Evaluation for Muscle and Nerve Diseases - DEMAND: An academic neuromuscular coding system

Background: A database which documents the diagnosis of neuromuscular patients is useful for determining the types of patients referred to academic centers and for identifying participants for clinical trials and other studies. The ICD-9 or ICD-10 numeric systems are insufficiently detailed for this purpose. Objective: To develop a database for neuromuscular diagnoses Methods: We developed a detailed diagnostic coding system for neuromuscular diseases called DEMAND: Database Evaluation for Muscle and Nerve Diseases that has been adopted by neuromuscular clinics at University of Texas Health Science Center San Antonio (UTHSCSA), Ohio State University (OSU), University of Kansas Medical Center (KUMC), and University of Texas Southwestern (UTSW). At the initial visit, patients are assigned a diagnostic code which can be revised later if appropriate. Fields include patient’s name, date of birth, and diagnostic code. The neuromuscular database consisted of 457 codes. Each code has a prefix (MUS or PNS) followed by a three-digit number. Depending on whether muscle or nerve is primarily involved, there are eight broad groups: motor neuron disease (MUS codes 100-139); neuromuscular junction disorders (MUS 200-217); acquired and hereditary myopathies (MUS 300-600s); acquired and hereditary polyneuropathies (PNS 100-400); mononeuropathies (PNS 500s); plexopathies (PNS 600s); radiculopathies (PNS 700s); and mononeuritis multiplex (PNS 800s). Results: During a period of 10 years, 17,163 of patients were entered (1,752 at UTHSCSA, 1,840 at OSU, 3,699 at KUMC, 9,872 at UTSW). The number of patients in several broad categories are: 3,080 motor neuron disease; 1,575 neuromuscular junction disease; 1,851 muscular dystrophies; 633 inflammatory myopathies; 1,090 hereditary neuropathies; 1,001 immune-mediated polyneuropathies; 620 metabolic/toxic polyneuropathies; 535 mononeuropathies; 296 plexopathies; and 769 radiculopathies. Conclusion: A detailed diagnostic neuromuscular database can be utilized at multiple academic centers. The database should be simple without too many fields to complete, to ensure compliance during busy clinic operations. This database has been very useful in identifying groups of patients for retrospective, observational studies and for prospective treatment studies including trials for Amyotrophic Lateral Sclerosis (ALS), Muscular Dystrophies (MD), Myasthenia Gravis (MG), and retrospective studies of Primary Lateral Sclerosis (PLS), chronic inflammatory demyelinating neuropathy (CIDP), etc

Targeting Protein Homeostasis in Sporadic Inclusion Body Myositis

Sporadic inclusion body myositis (sIBM) is the commonest severe myopathy in patients over age 50. Previous therapeutic trials have targeted the inflammatory features of sIBM, but all have failed. Since protein dyshomeostasis may also play a role in sIBM, we tested the effects of targeting this feature of the disease. Using rat myoblast cultures, we found that up-regulation of the heat shock response with Arimoclomol reduced key pathological markers of sIBM in vitro. Furthermore, in mutant valosin-containing protein VCP mice, which develop an inclusion body myopathy (IBM), treatment with Arimoclomol ameliorated disease pathology and improved muscle function. We therefore evaluated the safety and tolerability of Arimoclomol in an investigator-lead, randomised, double-blind, placebo-controlled, proof-of-concept patient trial and gathered exploratory efficacy data which showed that Arimoclomol was safe and well tolerated. Although Arimoclomol improved some IBM-like pathology in vitro and in vivo in the mutant VCP mouse, we did not see statistically significant evidence of efficacy in this proof of concept patient trial

A genome-wide association study of myasthenia gravis

IMPORTANCE: Myasthenia gravis is a chronic, autoimmune, neuromuscular disease characterized by fluctuating weakness of voluntary muscle groups. Although genetic factors are known to play a role in this neuroimmunological condition, the genetic etiology underlying myasthenia gravis is not well understood. OBJECTIVE: To identify genetic variants that alter susceptibility to myasthenia gravis, we performed a genome-wide association study. DESIGN, SETTING, AND PARTICIPANTS: DNA was obtained from 1032 white individuals from North America diagnosed as having acetylcholine receptor antibody–positive myasthenia gravis and 1998 race/ethnicity-matched control individuals from January 2010 to January 2011. These samples were genotyped on Illumina OmniExpress single-nucleotide polymorphism arrays. An independent cohort of 423 Italian cases and 467 Italian control individuals were used for replication. MAIN OUTCOMES AND MEASURES: We calculated P values for association between 8114394 genotyped and imputed variants across the genome and risk for developing myasthenia gravis using logistic regression modeling. A threshold P value of 5.0 × 10(−8) was set for genome-wide significance after Bonferroni correction for multiple testing. RESULTS: In the over all case-control cohort, we identified association signals at CTLA4 (rs231770; P = 3.98 × 10(−8); odds ratio, 1.37; 95% CI, 1.25–1.49), HLA-DQA1 (rs9271871; P = 1.08 × 10(−8); odds ratio, 2.31; 95% CI, 2.02 – 2.60), and TNFRSF11A (rs4263037; P = 1.60 × 10(−9); odds ratio, 1.41; 95% CI, 1.29–1.53). These findings replicated for CTLA4 and HLA-DQA1 in an independent cohort of Italian cases and control individuals. Further analysis revealed distinct, but overlapping, disease-associated loci for early- and late-onset forms of myasthenia gravis. In the late-onset cases, we identified 2 association peaks: one was located in TNFRSF11A (rs4263037; P = 1.32 × 10(−12); odds ratio, 1.56; 95% CI, 1.44–1.68) and the other was detected in the major histocompatibility complex on chromosome 6p21 (HLA-DQA1; rs9271871; P = 7.02 × 10(−18); odds ratio, 4.27; 95% CI, 3.92–4.62). Association within the major histocompatibility complex region was also observed in early-onset cases (HLA-DQA1; rs601006; P = 2.52 × 10(−11); odds ratio, 4.0; 95% CI, 3.57–4.43), although the set of single-nucleotide polymorphisms was different from that implicated among late-onset cases. CONCLUSIONS AND RELEVANCE: Our genetic data provide insights into aberrant cellular mechanisms responsible for this prototypical autoimmune disorder. They also suggest that clinical trials of immunomodulatory drugs related to CTLA4 and that are already Food and Drug Administration approved as therapies for other autoimmune diseases could be considered for patients with refractory disease