Efficacy and Safety of Lenabasum, a Cannabinoid Type 2 Receptor Agonist, in a Phase 3 Randomized Trial in Diffuse Cutaneous Systemic Sclerosis

Objective This phase 3 study was undertaken to investigate the efficacy and safety of lenabasum, a cannabinoid type 2 receptor agonist, in patients with diffuse cutaneous systemic sclerosis (dcSSc). Methods A multinational double-blind study was conducted in 365 dcSSc patients who were randomized and dosed 1:1:1 with lenabasum 20 mg, lenabasum 5 mg, or placebo, each twice daily and added to background treatments, including immunosuppressive therapies (IST). Results The primary end point, the American College of Rheumatology combined response index in dcSSc (CRISS) at week 52 for lenabasum 20 mg twice a day versus placebo, was not met, with CRISS score of 0.888 versus 0.887 (P = 0.4972, using mixed models repeated measures [MMRM]). The change in the modified Rodnan skin thickness score (MRSS) at week 52 for lenabasum 20 mg twice a day versus placebo was −6.7 versus −8.1 (P = 0.1183, using MMRM). Prespecified analyses showed higher CRISS scores, greater improvement in MRSS, and lower decline in forced vital capacity in patients on background mycophenolate and those who were taking IST for ≤1 year. No deaths or excess in serious or severe adverse events related to lenabasum were observed. Conclusion A benefit of lenabasum in dcSSc was not demonstrated. Most patients were treated with background IST, and treatment with mycophenolate mofetil in particular was associated with better outcomes. These findings support the use of IST in the treatment of dcSSc and highlight the challenge of demonstrating a treatment effect when investigational treatment is added to standard of care IST. These findings have relevance to trial design in SSc, as well as to clinical care

Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique\u2014Subtype and Stage Inference (SuStaIn)\u2014able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer\u2019s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 7 10 124 ) or temporal stage (p = 3.96 7 10 125 ). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine

Immunochip analysis identifies multiple susceptibility loci for systemic sclerosis

Full-text article is free to read on the publisher website.\ud \ud In this study, 1,833 systemic sclerosis (SSc) cases and 3,466 controls were genotyped with the Immunochip array. Classical alleles, amino acid residues, and SNPs across the human leukocyte antigen (HLA) region were imputed and tested. These analyses resulted in a model composed of six polymorphic amino acid positions and seven SNPs that explained the observed significant associations in the region. In addition, a replication step comprising 4,017 SSc cases and 5,935 controls was carried out for several selected non-HLA variants, reaching a total of 5,850 cases and 9,401 controls of European ancestry. Following this strategy, we identified and validated three SSc risk loci, including DNASE1L3 at 3p14, the SCHIP1-IL12A locus at 3q25, and ATG5 at 6q21, as well as a suggested association of the TREH-DDX6 locus at 11q23. The associations of several previously reported SSc risk loci were validated and further refined, and the observed peak of association in PXK was related to DNASE1L3. Our study has increased the number of known genetic associations with SSc, provided further insight into the pleiotropic effects of shared autoimmune risk factors, and highlighted the power of dense mapping for detecting previously overlooked susceptibility loci

Immunochip Analysis Identifies Multiple Susceptibility Loci for Systemic Sclerosis

Pathophysiology and treatment of rheumatic disease