A plain language summary of what clinical studies can tell us about the safety of evobrutinib – a potential treatment for multiple sclerosis

Immunology; Rheumatology; Systemic lupus erythematosusInmunología; Reumatología; Lupus eritematoso sistémicoImmunologia; Reumatologia; Lupus eritematós sistèmicWhat is this summary about?: This summary explains the findings from a recent investigation that combined the results of over 1000 people from three clinical studies to understand the safety of evobrutinib. Evobrutinib is an oral medication (taken by mouth), being researched as a potential treatment for multiple sclerosis (MS). This medication was also investigated in rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). Over 1000 people have taken evobrutinib as part of three separate phase 2 clinical studies. These studies looked at how much of the drug should be taken, how safe the drug is, and how well it might work for treating a certain medical condition. What were the results?: Evobrutinib was well-tolerated by participants in all three studies. The number of side effects reported by participants taking the medication was very similar to those reported by participants taking the placebo (a 'dummy' treatment without a real drug). The most common side effects in clinical studies were urinary tract infections, headache, swelling of the nose and throat, diarrhoea and blood markers of potential liver damage (these returned to normal once the treatment was stopped). What do the results mean?: The safety data from all three clinical studies are encouraging and can be used to inform further research into using evobrutinib in MS.X Montalban has received speaking honoraria and travel expenses for participation in scientific meetings, has been a steering committee member of clinical trials or participated in advisory boards of clinical trials in the past years with Abbvie, Actelion, Alexion, Biogen, Bristol-Myers Squibb/Celgene, EMD Serono, Genzyme, Hoffmann-La Roche, Immunic, Janssen Pharmaceuticals, Medday, Merck, Mylan, Nervgen, Novartis, Sandoz, Sanofi-Genzyme, Teva Pharmaceutical, TG Therapeutics, Excemed, MSIF and NMSS. D Wallace has received consultant fees from Amgen, Celgene, Eli Lilly, EMD Serono Research & Development Institute, Inc., Billerica, MA, USA (an affiliate of Merck KGaA), Janssen and Merck. MC Genovese is an employee of and has financial interests in Gilead. D Tomic is an employee of Ares Trading SA, Eysins, Switzerland, an affiliate of Merck KGaA, and received stock or an ownership interest from Novartis. D Parsons-Rich was an employee of EMD Serono Research & Development Institute, Inc., Billerica, MA, USA, an affiliate of Merck KGaA, at the time of the study, and is currently an employee of and has received stock from Pfizer. C Le Bolay and H Guehring are employees of Merck Healthcare KGaA, Darmstadt, Germany. A Kao is an employee of and received stock or an ownership interest from EMD Serono Inc., Billerica, MA, USA, a healthcare business of Merck KGaA. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: this work was supported by Merck (CrossRef Funder ID: 10.13039/100009945). This summary was prepared by Lumanity on behalf of, and funded by, Merck KGaA, Darmstadt, Germany

Characterisation of the safety profile of evobrutinib in over 1000 patients from phase II clinical trials in multiple sclerosis, rheumatoid arthritis and systemic lupus erythematosus: an integrated safety analysis

Immunology; Multiple sclerosis; RheumatologyInmunología; Esclerosis múltiple; ReumatologíaImmunologia; Esclerosi múltiple; ReumatologiaObjective Analyse the integrated safety profile of evobrutinib, a Bruton’s tyrosine kinase inhibitor (BTKi), using pooled data from multiple sclerosis (MS), rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) trials. Methods Phase II, randomised, double-blind, placebo-controlled trial data were analysed (N=1083; MS: n=213, 48 weeks (W); RA: n=390, 12W; SLE: n=480, 52W). The analysis included all patients who received ≥1 dose of evobrutinib (25 mg or 75 mg once daily, or 50 mg or 75 mgtwice daily) or placebo. Descriptive statistics and exposure-adjusted incidence rates (EAIR) were used to report treatment-emergent adverse events (TEAEs). Results Data from 1083 patients were pooled: evobrutinib, n=861; placebo, n=271 (sum >1083 due to MS trial design: n=49 received both placebo (W0–24) and evobrutinib 25 mg (W25–48)); median follow-up time (pt-years): evobrutinib, 0.501; placebo, 0.463. Across indications, the proportion of patients with TEAEs and the EAIR were similar for evobrutinib and placebo (66.2% (247.6 events/100 pt-years) vs 62.4% (261.4 events/100 pt-years)). By indication, the EAIR (events/100 pt-years) of TEAEs for evobrutinib versus placebo were: MS: 119.7 vs 148.3; RA: 331.8 vs 306.8; SLE: 343.0 vs 302.1. Two fatal events occurred (in SLE). The serious infections EAIR was 2.7 and 2.1 events/100 pt-years for evobrutinib and placebo. For previously reported BTKi-class effects, the EAIR of transient elevated alanine aminotransferase/aspartate aminotransferase TEAEs (events/100 pt-years) with evobrutinib versus placebo was 4.8 vs 2.8/3.5 vs 0.7, respectively. IgG levels were similar in evobrutinib/placebo-treated patients. Conclusions This is the first BTKi-integrated safety analysis that includes patients with MS. Overall, evobrutinib treatment (all doses) was generally well tolerated across indications.The trial was sponsored by Merck Healthcare KGaA (CrossRef Funder ID: 10.13039/100009945)

Learning a Prior on Regulatory Potential from eQTL Data

Genome-wide RNA expression data provide a detailed view of an organism's biological state; hence, a dataset measuring expression variation between genetically diverse individuals (eQTL data) may provide important insights into the genetics of complex traits. However, with data from a relatively small number of individuals, it is difficult to distinguish true causal polymorphisms from the large number of possibilities. The problem is particularly challenging in populations with significant linkage disequilibrium, where traits are often linked to large chromosomal regions containing many genes. Here, we present a novel method, Lirnet, that automatically learns a regulatory potential for each sequence polymorphism, estimating how likely it is to have a significant effect on gene expression. This regulatory potential is defined in terms of “regulatory features”—including the function of the gene and the conservation, type, and position of genetic polymorphisms—that are available for any organism. The extent to which the different features influence the regulatory potential is learned automatically, making Lirnet readily applicable to different datasets, organisms, and feature sets. We apply Lirnet both to the human HapMap eQTL dataset and to a yeast eQTL dataset and provide statistical and biological results demonstrating that Lirnet produces significantly better regulatory programs than other recent approaches. We demonstrate in the yeast data that Lirnet can correctly suggest a specific causal sequence variation within a large, linked chromosomal region. In one example, Lirnet uncovered a novel, experimentally validated connection between Puf3—a sequence-specific RNA binding protein—and P-bodies—cytoplasmic structures that regulate translation and RNA stability—as well as the particular causative polymorphism, a SNP in Mkt1, that induces the variation in the pathway

Genetic Determinants of Lipid Traits in Diverse Populations from the Population Architecture using Genomics and Epidemiology (PAGE) Study

For the past five years, genome-wide association studies (GWAS) have identified hundreds of common variants associated with human diseases and traits, including high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels. Approximately 95 loci associated with lipid levels have been identified primarily among populations of European ancestry. The Population Architecture using Genomics and Epidemiology (PAGE) study was established in 2008 to characterize GWAS–identified variants in diverse population-based studies. We genotyped 49 GWAS–identified SNPs associated with one or more lipid traits in at least two PAGE studies and across six racial/ethnic groups. We performed a meta-analysis testing for SNP associations with fasting HDL-C, LDL-C, and ln(TG) levels in self-identified European American (∼20,000), African American (∼9,000), American Indian (∼6,000), Mexican American/Hispanic (∼2,500), Japanese/East Asian (∼690), and Pacific Islander/Native Hawaiian (∼175) adults, regardless of lipid-lowering medication use. We replicated 55 of 60 (92%) SNP associations tested in European Americans at p<0.05. Despite sufficient power, we were unable to replicate ABCA1 rs4149268 and rs1883025, CETP rs1864163, and TTC39B rs471364 previously associated with HDL-C and MAFB rs6102059 previously associated with LDL-C. Based on significance (p<0.05) and consistent direction of effect, a majority of replicated genotype-phentoype associations for HDL-C, LDL-C, and ln(TG) in European Americans generalized to African Americans (48%, 61%, and 57%), American Indians (45%, 64%, and 77%), and Mexican Americans/Hispanics (57%, 56%, and 86%). Overall, 16 associations generalized across all three populations. For the associations that did not generalize, differences in effect sizes, allele frequencies, and linkage disequilibrium offer clues to the next generation of association studies for these traits