Cardiotoxicity of mitoxantrone treatment in a german cohort of 639 multiple sclerosis patients

Background and Purpose: The aim of this study was to elucidate the role of therapy-related cardiotoxicity in multiple sclerosis (MS) patients treated with mitoxantrone and to identify potential predictors for individual risk assessment. Methods: Within a multicenter retrospective cohort design, cardiac side effects attributed to mitoxantrone were analyzed in 639 MS patients at 2 MS centers in Germany. Demographic, disease, treatment, and follow-up data were collected from hospital records. Patients regularly received cardiac monitoring during the treatment phase. Results: None of the patients developed symptomatic congestive heart failure. However, the frequency of patients experiencing cardiac dysfunction of milder forms after mitoxantrone therapy was 4.1% (26 patients) among all patients. Analyses of the risk for cardiotoxicity revealed that cumulative dose exposure was the only statistically relevant risk factor associated with cardiac dysfunction. Conclusions: The number of patients developing subclinical cardiac dysfunction below the maximum recommended cumulative dose is higher than was initially assumed. Interestingly, a subgroup of patients was identified who experienced cardiac dysfunction shortly after initiation of mitoxantrone and who received a low cumulative dose. Therefore, each administration of mitoxantrone should include monitoring of cardiac function to enhance the treatment safety for patients and to allow for early detection of any side effects, especially in potential high-risk subgroups (as determined genetically)

Factors predisposing to humoral autoimmunity against brain-antigens in health and disease Analysis of 49 autoantibodies in over 7000 subjects

Background:Circulating autoantibodies (AB) against brain-antigens, often deemed pathological, receive increasing attention. We assessed predispositions and seroprevalence/characteristics of 49 AB in >7000 individuals.Methods:Exploratory cross-sectional cohort study, investigating deeply phenotyped neuropsychiatric patients and healthy individuals of GRAS Data Collection for presence/characteristics of 49 brain-directed serum-AB. Predispositions were evaluated through GWAS of NMDAR1-AB carriers, analyses of immune check-point genotypes, APOE4 status, neurotrauma. Chi-square, Fisher’s exact tests and logistic regression analyses were used.Results:Study of N=7025 subjects (55.8% male; 41±16 years) revealed N=1133 (16.13%) carriers of any AB against 49 defined brain-antigens. Overall, age dependence of seroprevalence (OR=1.018/year; 95% CI [1.015-1.022]) emerged, but no disease association, neither general nor with neuropsychiatric subgroups. Males had higher AB seroprevalence (OR=1.303; 95% CI [1.144-1.486]). Immunoglobulin class (N for IgM:462; IgA:487; IgG:477) and titers were similar. Abundant were NMDAR1-AB (7.7%). Low seroprevalence (1.25%-0.02%) was seen for most AB (e.g. amphiphysin, KCNA2, ARHGAP26, GFAP, CASPR2, MOG, Homer-3, KCNA1, GLRA1b, GAD65). Non-detectable were others. GWAS of NMDAR1-AB carriers revealed three genome-wide significant SNPs, two intergenic, one in TENM3, previously autoimmune disease-associated. Targeted analysis of immune check-point genotypes (CTLA4, PD1, PD-L1) uncovered effects on humoral anti-brain autoimmunity (OR=1.55; 95% CI [1.058-2.271]) and disease likelihood (OR=1.43; 95% CI [1.032-1.985]). APOE4 carriers (∼19%) had lower seropositivity (OR=0.766; 95% CI [0.625-0.933]). Neurotrauma predisposed to NMDAR1-AB seroprevalence (IgM: OR=1.599; 95% CI [1.022-2.468]).Conclusions:Humoral autoimmunity against brain-antigens, frequent across health and disease, is predicted by age, gender, genetic predisposition, and brain injury. Seroprevalence, immunoglobulin class, or titers do not predict disease

Clinical implications of serum neurofilament in newly diagnosed MS patients: a longitudinal multicentre cohort study

BACKGROUND: We aim to evaluate serum neurofilament light chain (sNfL), indicating neuroaxonal damage, as a biomarker at diagnosis in a large cohort of early multiple sclerosis (MS) patients. METHODS: In a multicentre prospective longitudinal observational cohort, patients with newly diagnosed relapsing-remitting MS (RRMS) or clinically isolated syndrome (CIS) were recruited between August 2010 and November 2015 in 22 centers. Clinical parameters, MRI, and sNfL levels (measured by single molecule array) were assessed at baseline and up to four-year follow-up. FINDINGS: Of 814 patients, 54.7% (445) were diagnosed with RRMS and 45.3% (369) with CIS when applying 2010 McDonald criteria (RRMS[2010] and CIS[2010]). After reclassification of CIS[2010] patients with existing CSF analysis, according to 2017 criteria, sNfL levels were lower in CIS[2017] than RRMS[2017] patients (9.1 pg/ml, IQR 6.2-13.7 pg/ml, n = 45; 10.8 pg/ml, IQR 7.4-20.1 pg/ml, n = 213; p = 0.036). sNfL levels correlated with number of T2 and Gd+ lesions at baseline and future clinical relapses. Patients receiving disease-modifying therapy (DMT) during the first four years had higher baseline sNfL levels than DMT-naïve patients (11.8 pg/ml, IQR 7.5-20.7 pg/ml, n = 726; 9.7 pg/ml, IQR 6.4-15.3 pg/ml, n = 88). Therapy escalation decisions within this period were reflected by longitudinal changes in sNfL levels. INTERPRETATION: Assessment of sNfL increases diagnostic accuracy, is associated with disease course prognosis and may, particularly when measured longitudinally, facilitate therapeutic decisions

Novel multiple sclerosis susceptibility loci implicated in epigenetic regulation

We conducted a genome-wide association study (GWAS) on multiple sclerosis (MS) susceptibility in German cohorts with 4888 cases and 10,395 controls. In addition to associations within the major histocompatibility complex (MHC) region, 15 non-MHC loci reached genome-wide significance. Four of these loci are novel MS susceptibility loci. They map to the genes L3MBTL3, MAZ, ERG, and SHMT1. The lead variant at SHMT1 was replicated in an independent Sardinian cohort. Products of the genes L3MBTL3, MAZ, and ERG play important roles in immune cell regulation. SHMT1 encodes a serine hydroxymethyltransferase catalyzing the transfer of a carbon unit to the folate cycle. This reaction is required for regulation of methylation homeostasis, which is important for establishment and maintenance of epigenetic signatures. Our GWAS approach in a defined population with limited genetic substructure detected associations not found in larger, more heterogeneous cohorts, thus providing new clues regarding MS pathogenesis

DeepWAS: multivariate genotype-phenotype associations by directly integrating regulatory information using deep learning

Genome-wide association studies (GWAS) identify genetic variants associated with traits or diseases. GWAS never directly link variants to regulatory mechanisms. Instead, the functional annotation of variants is typically inferred by post hoc analyses. A specific class of deep learning-based methods allows for the prediction of regulatory effects per variant on several cell type-specific chromatin features. We here describe "DeepWAS", a new approach that integrates these regulatory effect predictions of single variants into a multivariate GWAS setting. Thereby, single variants associated with a trait or disease are directly coupled to their impact on a chromatin feature in a cell type. Up to 61 regulatory SNPs, called dSNPs, were associated with multiple sclerosis (MS, 4,888 cases and 10,395 controls), major depressive disorder (MDD, 1,475 cases and 2,144 controls), and height (5,974 individuals). These variants were mainly non-coding and reached at least nominal significance in classical GWAS. The prediction accuracy was higher for DeepWAS than for classical GWAS models for 91% of the genome-wide significant, MS-specific dSNPs. DSNPs were enriched in public or cohort-matched expression and methylation quantitative trait loci and we demonstrated the potential of DeepWAS to generate testable functional hypotheses based on genotype data alone. DeepWAS is available at https://github.com/cellmapslab/DeepWAS

A digitally-augmented ground space with timed visual cues for facilitating forearm crutches’ mobility

Persuasive technologies for physical rehabilitation have been pro posed in a number of different health interventions such as post-stroke gait rehabilitation. We propose a new persuasive system, called Augmented Crut ches, aimed at helping people to walk with crutches. People with injuries, or with any sort of mobility problem typically use assistive devices such as crut ches, walkers or canes in order to be able to walk more independently. However, walking with crutches is a learning skill that needs continuous repetition and constant attention to detail in order to walk correctly with them and without suffering negative consequences, such as falls or injuries. In close collaboration with therapists, we identify the main issues that patients face when walking with crutches. These vary from person to person, but the most common and hardest challenges are the position and coordination of the crutches. Augmented Crut ches studies human behavior aspects in these situations and augments the ground space around the user with digital visual cues where timing is the most important factor, without the need for a constant therapist providing manual help. This is performed through a mini-projector connected to a smartphone, worn by the user in a portable, lightweight manner. Our system helps people to learn how to walk using crutches with increased self-confidence and motivation. Additionally, our work identifies timing, controllability and awareness as the key design dimensions for the successful creation of persuasive, interactive experiences for learning how to walk with crutches.info:eu-repo/semantics/publishedVersio

Can we predict cognitive decline after initial diagnosis of multiple sclerosis? Results from the German National early MS cohort (KKNMS)

BACKGROUND: Cognitive impairment (CI) affects approximately one-third of the patients with early multiple sclerosis (MS) and clinically isolated syndrome (CIS). Little is known about factors predicting CI and progression after initial diagnosis. METHODS: Neuropsychological screening data from baseline and 1-year follow-up of a prospective multicenter cohort study (NationMS) involving 1123 patients with newly diagnosed MS or CIS were analyzed. Employing linear multilevel models, we investigated whether demographic, clinical and conventional MRI markers at baseline were predictive for CI and longitudinal cognitive changes. RESULTS: At baseline, 22% of patients had CI (impairment in ≥2 cognitive domains) with highest frequencies and severity in processing speed and executive functions. Demographics (fewer years of academic education, higher age, male sex), clinical (EDSS, depressive symptoms) but no conventional MRI characteristics were linked to baseline CI. At follow-up, only 14% of patients showed CI suggesting effects of retesting. Neither baseline characteristics nor initiation of treatment between baseline and follow-up was able to predict cognitive changes within the follow-up period of 1 year. CONCLUSIONS: Identification of risk factors for short-term cognitive change in newly diagnosed MS or CIS is insufficient using only demographic, clinical and conventional MRI data. Change-sensitive, re-test reliable cognitive tests and more sophisticated predictors need to be employed in future clinical trials and cohort studies of early-stage MS to improve prediction

Multimodal Functional Network Connectivity: An EEG-fMRI Fusion in Network Space

EEG and fMRI recordings measure the functional activity of multiple coherent networks distributed in the cerebral cortex. Identifying network interaction from the complementary neuroelectric and hemodynamic signals may help to explain the complex relationships between different brain regions. In this paper, multimodal functional network connectivity (mFNC) is proposed for the fusion of EEG and fMRI in network space. First, functional networks (FNs) are extracted using spatial independent component analysis (ICA) in each modality separately. Then the interactions among FNs in each modality are explored by Granger causality analysis (GCA). Finally, fMRI FNs are matched to EEG FNs in the spatial domain using network-based source imaging (NESOI). Investigations of both synthetic and real data demonstrate that mFNC has the potential to reveal the underlying neural networks of each modality separately and in their combination. With mFNC, comprehensive relationships among FNs might be unveiled for the deep exploration of neural activities and metabolic responses in a specific task or neurological state

A systems biology approach uncovers cell-specific gene regulatory effects of genetic associations in multiple sclerosis

Genome-wide association studies (GWAS) have identified more than 50,000 unique associations with common human traits. While this represents a substantial step forward, establishing the biology underlying these associations has proven extremely difficult. Even determining which cell types and which particular gene(s) are relevant continues to be a challenge. Here, we conduct a cell-specific pathway analysis of the latest GWAS in multiple sclerosis (MS), which had analyzed a total of 47,351 cases and 68,284 healthy controls and found more than 200 non-MHC genome-wide associations. Our analysis identifies pan immune cell as well as cell-specific susceptibility genes in T cells, B cells and monocytes. Finally, genotype-level data from 2,370 patients and 412 controls is used to compute intraindividual and cell-specific susceptibility pathways that offer a biological interpretation of the individual genetic risk to MS. This approach could be adopted in any other complex trait for which genome-wide data is available