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BackgroundIn the phase III ASCLEPIOS I and II trials, participants with relapsing multiple sclerosis receiving ofatumumab had significantly better clinical and magnetic resonance imaging (MRI) outcomes than those receiving teriflunomide.ObjectivesTo assess the efficacy and safety of ofatumumab versus teriflunomide in recently diagnosed, treatment-naive (RDTN) participants from ASCLEPIOS.MethodsParticipants were randomized to receive ofatumumab (20 mg subcutaneously every 4 weeks) or teriflunomide (14 mg orally once daily) for up to 30 months. Endpoints analysed post hoc in the protocol-defined RDTN population included annualized relapse rate (ARR), confirmed disability worsening (CDW), progression independent of relapse activity (PIRA) and adverse events.ResultsData were analysed from 615 RDTN participants (ofatumumab: n = 314; teriflunomide: n = 301). Compared with teriflunomide, ofatumumab reduced ARR by 50% (rate ratio (95% confidence interval (CI)): 0.50 (0.33, 0.74); p

BackgroundOfatumumab is approved for the treatment of relapsing multiple sclerosis (RMS). Ongoing safety reporting is crucial to understand its long-term benefit-risk profile.ObjectiveReport the safety and tolerability of ofatumumab in RMS after extended treatment up to 3.5 years.MethodsPatients completing ASCLEPIOS I/II (phase 3), APLIOS, or APOLITOS (phase 2) trials could enter ALITHIOS, a phase 3b, open-label, long-term safety study. We analyzed cumulative data of continuous ofatumumab treatment and of patients newly switched from teriflunomide.ResultsThe safety population had 1969 patients: 1292 continuously treated with ofatumumab (median time-at-risk 35.5 months, 3253 patient-years) and 677 newly switched (median time-at-risk 18.3 months, 986 patient-years). A total of 1650 patients (83.8%) had ⩾1 adverse events and 191 (9.7%) had ⩾1 serious adverse events. No opportunistic infections or progressive multifocal leukoencephalopathy events were identified; the risk of malignancies was low. Mean serum immunoglobulin (Ig) G levels remained stable. Mean IgM levels decreased but remained above the lower limit of normal in most. Serious infection incidence was low; decreased Ig levels were not associated with serious infections.ConclusionIn patients with up to 3.5 years' exposure, ofatumumab was well tolerated, with no new safety risks identified. These findings, with its established effectiveness, support a favorable benefit-risk profile of ofatumumab in RMS.

ObjectiveThis study aims to confirm the prognostic value of baseline serum neurofilament light chain (sNfL) for on-study disease activity and worsening in patients with relapsing MS (RMS).BackgroundPrevious post-hoc studies suggested that sNfL could be a prognostic biomarker in RMS. In the phase 3 ASCLEPIOS I/II trials in which ofatumumab demonstrated better efficacy outcomes than teriflunomide, treatment with ofatumumab also led to significantly reduced sNfL levels compared to teriflunomide treatment.Design/methodsIn this study, we report protocol-planned analyses from the pooled ASCLEPIOS I/II trials (N=1882). Per protocol, patients were stratified by median baseline sNfL levels (9.3 pg/ml) into high (>median) and low (≤median) categories to prognosticate: annualized rate of new/enlarging T2 (neT2) lesions in year 1 and 2, annualized relapse rate, annual percentage change in whole brain (WB) and regional brain volume [thalamus, white matter (WM), cortical gray matter (cGM)], and disability outcomes. Similar analyses were performed for the recently diagnosed (within 3 years), treatment-naive patients (no prior disease-modifying therapy) subgroup.ResultsHigh versus low sNfL at baseline was prognostic of increased on-study T2 lesion formation at year 1 (relative increase: ofatumumab +158%; teriflunomide +69%, both p

Metabolic diseases are a worldwide problem but the underlying genetic factors and their relevance to metabolic disease remain incompletely understood. Genome-wide research is needed to characterize so-far unannotated mammalian metabolic genes. Here, we generate and analyze metabolic phenotypic data of 2016 knockout mouse strains under the aegis of the International Mouse Phenotyping Consortium (IMPC) and find 974 gene knockouts with strong metabolic phenotypes. 429 of those had no previous link to metabolism and 51 genes remain functionally completely unannotated. We compared human orthologues of these uncharacterized genes in five GWAS consortia and indeed 23 candidate genes are associated with metabolic disease. We further identify common regulatory elements in promoters of candidate genes. As each regulatory element is composed of several transcription factor binding sites, our data reveal an extensive metabolic phenotype-associated network of co-regulated genes. Our systematic mouse phenotype analysis thus paves the way for full functional annotation of the genome.

Genome-wide association studies (GWAS) have found few common variants that influence fasting measures of insulin sensitivity. We hypothesized that a GWAS of an integrated assessment of fasting and dynamic measures of insulin sensitivity would detect novel common variants. We performed a GWAS of the modified Stumvoll Insulin Sensitivity Index (ISI) within the Meta-Analyses of Glucose and Insulin-Related Traits Consortium. Discovery for genetic association was performed in 16,753 individuals, and replication was attempted for the 23 most significant novel loci in 13,354 independent individuals. Association with ISI was tested in models adjusted for age, sex, and BMI and in a model analyzing the combined influence of the genotype effect adjusted for BMI and the interaction effect between the genotype and BMI on ISI (model 3). In model 3, three variants reached genome-wide significance: rs13422522 (NYAP2; P = 8.87 × 10(-11)), rs12454712 (BCL2; P = 2.7 × 10(-8)), and rs10506418 (FAM19A2; P = 1.9 × 10(-8)). The association at NYAP2 was eliminated by conditioning on the known IRS1 insulin sensitivity locus; the BCL2 and FAM19A2 associations were independent of known cardiometabolic loci. In conclusion, we identified two novel loci and replicated known variants associated with insulin sensitivity. Further studies are needed to clarify the causal variant and function at the BCL2 and FAM19A2 loci.

Background'No evidence of disease activity' (NEDA), defined as absence of magnetic resonance imaging activity (T2 and/or gadolinium-enhanced T1 lesions), relapses and disability progression ('NEDA-3'), is used as a comprehensive measure of treatment response in relapsing multiple sclerosis (RMS), but is weighted towards inflammatory activity. Accelerated brain volume loss (BVL) occurs in RMS and is an objective measure of disease worsening and progression.ObjectiveTo assess the contribution of individual components of NEDA-3 and the impact of adding BVL to NEDA-3 ('NEDA-4') METHODS: We analysed data pooled from two placebo-controlled phase 3 fingolimod trials in RMS and assessed NEDA-4 using different annual BVL mean rate thresholds (0.2%-1.2%).ResultsAt 2 years, 31.0% (217/700) of patients receiving fingolimod 0.5 mg achieved NEDA-3 versus 9.9% (71/715) on placebo (odds ratio (OR) 4.07; p

Background'No evidence of disease activity' (NEDA), defined as absence of magnetic resonance imaging activity (T2 and/or gadolinium-enhanced T1 lesions), relapses and disability progression ('NEDA-3'), is used as a comprehensive measure of treatment response in relapsing multiple sclerosis (RMS), but is weighted towards inflammatory activity. Accelerated brain volume loss (BVL) occurs in RMS and is an objective measure of disease worsening and progression.ObjectiveTo assess the contribution of individual components of NEDA-3 and the impact of adding BVL to NEDA-3 ('NEDA-4') METHODS: We analysed data pooled from two placebo-controlled phase 3 fingolimod trials in RMS and assessed NEDA-4 using different annual BVL mean rate thresholds (0.2%-1.2%).ResultsAt 2 years, 31.0% (217/700) of patients receiving fingolimod 0.5 mg achieved NEDA-3 versus 9.9% (71/715) on placebo (odds ratio (OR) 4.07; p

Patients with established type 2 diabetes display both β-cell dysfunction and insulin resistance. To define fundamental processes leading to the diabetic state, we examined the relationship between type 2 diabetes risk variants at 37 established susceptibility loci, and indices of proinsulin processing, insulin secretion, and insulin sensitivity. We included data from up to 58,614 nondiabetic subjects with basal measures and 17,327 with dynamic measures. We used additive genetic models with adjustment for sex, age, and BMI, followed by fixed-effects, inverse-variance meta-analyses. Cluster analyses grouped risk loci into five major categories based on their relationship to these continuous glycemic phenotypes. The first cluster (PPARG, KLF14, IRS1, GCKR) was characterized by primary effects on insulin sensitivity. The second cluster (MTNR1B, GCK) featured risk alleles associated with reduced insulin secretion and fasting hyperglycemia. ARAP1 constituted a third cluster characterized by defects in insulin processing. A fourth cluster (TCF7L2, SLC30A8, HHEX/IDE, CDKAL1, CDKN2A/2B) was defined by loci influencing insulin processing and secretion without a detectable change in fasting glucose levels. The final group contained 20 risk loci with no clear-cut associations to continuous glycemic traits. By assembling extensive data on continuous glycemic traits, we have exposed the diverse mechanisms whereby type 2 diabetes risk variants impact disease predisposition.

Patients with established type 2 diabetes display both β-cell dysfunction and insulin resistance. To define fundamental processes leading to the diabetic state, we examined the relationship between type 2 diabetes risk variants at 37 established susceptibility loci, and indices of proinsulin processing, insulin secretion, and insulin sensitivity. We included data from up to 58,614 nondiabetic subjects with basal measures and 17,327 with dynamic measures. We used additive genetic models with adjustment for sex, age, and BMI, followed by fixed-effects, inverse-variance meta-analyses. Cluster analyses grouped risk loci into five major categories based on their relationship to these continuous glycemic phenotypes. The first cluster (PPARG, KLF14, IRS1, GCKR) was characterized by primary effects on insulin sensitivity. The second cluster (MTNR1B, GCK) featured risk alleles associated with reduced insulin secretion and fasting hyperglycemia. ARAP1 constituted a third cluster characterized by defects in insulin processing. A fourth cluster (TCF7L2, SLC30A8, HHEX/IDE, CDKAL1, CDKN2A/2B) was defined by loci influencing insulin processing and secretion without a detectable change in fasting glucose levels. The final group contained 20 risk loci with no clear-cut associations to continuous glycemic traits. By assembling extensive data on continuous glycemic traits, we have exposed the diverse mechanisms whereby type 2 diabetes risk variants impact disease predisposition.