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Genetic risk for multiple sclerosis (MS) is thought to involve both common and rare risk alleles. Recent GWAS and subsequent meta-analysis have established the critical role of the HLA locus and identified new common variants associated to MS. These variants have small odds ratios (ORs) and explain only a fraction of the genetic risk. To expose potentially rare, high-impact alleles, we conducted a GWAS of 68 distantly related cases and 136 controls from a high-risk internal isolate of Finland with increased prevalence and familial occurrence of MS. The top 27 loci with p < 10(-4) were tested in 711 cases and 1029 controls from Finland, and the top two findings were validated in 3859 cases and 9110 controls from more heterogeneous populations. SNP (rs744166) within the STAT3 gene was associated to MS (p = 2.75 x 10(-10), OR 0.87, confidence interval 0.83-0.91). The protective haplotype for MS in STAT3 is a risk allele for Crohn disease, implying that STAT3 represents a shared risk locus for at least two autoimmune diseases. This study also demonstrates the potential of special isolated populations in search for variants contributing to complex traits.
Multiple sclerosis (MS) is the most common cause of chronic neurologic disability beginning in early to middle adult life. Results from recent genome-wide association studies (GWAS) have substantially lengthened the list of disease loci and provide convincing evidence supporting a multifactorial and polygenic model of inheritance. Nevertheless, the knowledge of MS genetics remains incomplete, with many risk alleles still to be revealed.
Previous studies have established regional gray matter (GM) volume loss in multiple sclerosis (MS) but the relationship between development of white matter (WM) lesions and changes of regional GM volumes is unclear. The present study addresses this issue by means of voxel-based morphometry (VBM). T1-weighted three-dimensional magnetic resonance imaging (MRI) data from MS patients followed up for 12 months were analyzed using VBM. An analysis of covariance model assessed with cluster size inference (all corrected for multiple comparisons, p<0.01) was used to compare GM volumes between baseline and follow-up while controlling for age, gender, and disease duration. Lesion burden, i.e. volumes of T1 hypointense and T2 hyperintense lesions and the number of new T2 lesions at year one, was also determined. Comparing all MS patients (n=211) longitudinally, GM volume remained unchanged during one year-follow-up. Focusing on patients with relapsing remitting MS (RRMS) (n=151), significant cortical GM volume reductions between baseline and follow-up scans were found in the anterior and posterior cingulate, the temporal cortex, and cerebellum. Within the RRMS group, those patients with increasing T2 and T1 lesion burden (n=45) showed additional GM volume loss during follow-up in the frontal and parietal cortex, and precuneus. In contrast, patients lacking an increase in WM lesion burden (n=44) did not show any significant GM changes. The present study suggests that the progression of regional GM volume reductions is associated with WM lesion progression and occurs predominantly in fronto-temporal cortical areas.
Interferon-beta (IFNβ) regulates the expression of a complex set of pro- as well as anti-inflammatory genes. In cohorts of MS patients unstratified for therapeutic response to IFNβ, normal vaccine-specific immune responses have been observed. Data capturing antigen-specific immune responses in cohorts of subjects defined by response to IFNβ-therapy are not available.
Amiselimod (MT-1303) is a selective sphingosine 1-phosphate 1 (S1P1 ) receptor modulator which is currently being developed for the treatment of various autoimmune diseases. Unlike some other S1P receptor modulators, amiselimod seemed to show a favourable cardiac safety profile in preclinical, phase I and II studies. The aim of the current study was to characterize the cardiac effects of amiselimod by directly comparing it with fingolimod and placebo.
Nouns and verbs can dissociate following brain damage, at both lexical retrieval and morphosyntactic processing levels. In order to document the range and the neural underpinnings of behavioral dissociations, twelve aphasics with disproportionate difficulty naming objects or actions were asked to apply phonologically identical morphosyntactic transformations to nouns and verbs. Two subjects with poor object naming and 2/10 with poor action naming made no morphosyntactic errors at all. Six of 10 subjects with poor action naming showed disproportionate or no morphosyntactic difficulties for verbs. Morphological errors on nouns and verbs correlated at the group level, but in individual cases a selective impairment of verb morphology was observed. Poor object and action naming with spared morphosyntax were associated with non-overlapping lesions (inferior occipitotemporal and fronto-temporal, respectively). Poor verb morphosyntax was observed with frontal-temporal lesions affecting white matter tracts deep to the insula, possibly disrupting the interaction of nodes in a fronto-temporal network.
Univariate analyses have identified gray matter (GM) alterations in different groups of MS patients. While these methods detect differences on the basis of the single voxel or cluster, multivariate methods like support vector machines (SVM) identify the complex neuroanatomical patterns of GM differences. Using multivariate linear SVM analysis and leave-one-out cross-validation, we aimed at identifying neuroanatomical GM patterns relevant for individual classification of MS patients. We used SVM to separate GM segmentations of T1-weighted three-dimensional magnetic resonance (MR) imaging scans within different age- and sex-matched groups of MS patients with either early (n=17) or late MS (n=17) (contrast I), low (n=20) or high (n=20) white matter lesion load (contrast II), and benign MS (BMS, n=13) or non-benign MS (NBMS, n=13) (contrast III) scanned on a single 1.5 T MR scanner. GM patterns most relevant for individual separation of MS patients comprised cortical areas of all the cerebral lobes as well as deep GM structures, including the thalamus and caudate. The patterns detected were sufficiently informative to separate individuals of the respective groups with high sensitivity and specificity in 85% (contrast I), 83% (contrast II) and 77% (contrast III) of cases. The study demonstrates that neuroanatomical spatial patterns of GM segmentations contain information sufficient for correct classification of MS patients at the single case level, thus making multivariate SVM analysis a promising clinical application.
Background: Brainstem-mediated functions are impaired in neurodegenerative diseases and aging. Atrophy can be visualized by MRI. This study investigates extrinsic sources of brainstem volume variability, intrinsic sources of anatomical variability, and the influence of age and sex on the brainstem volumes in healthy subjects. We aimed to develop efficient normalization strategies to reduce the effects of intrinsic anatomic variability on brainstem volumetry. Methods: Brainstem segmentation was performed from MPRAGE data using our deep-learning-based brainstem segmentation algorithm MD-GRU. The extrinsic variability of brainstem volume assessments across scanners and protocols was investigated in two groups comprising 11 (median age 33.3 years, 7 women) and 22 healthy subjects (median age 27.6 years, 50% women) scanned twice and compared using Dice scores. Intrinsic anatomical inter-individual variability and age and sex effects on brainstem volumes were assessed in segmentations of 110 healthy subjects (median age 30.9 years, range 18-72 years, 53.6% women) acquired on 1.5T (45%) and 3T (55%) scanners. The association between brainstem volumes and predefined anatomical covariates was studied using Pearson correlations. Anatomical variables with associations of |r| > 0.30 as well as the variables age and sex were used to construct normalization models using backward selection. The effect of the resulting normalization models was assessed by % relative standard deviation reduction and by comparing the inter-individual variability of the normalized brainstem volumes to the non-normalized values using paired t- tests with Bonferroni correction. Results: The extrinsic variability of brainstem volumetry across different field strengths and imaging protocols was low (Dice scores > 0.94). Mean inter-individual variability/SD of total brainstem volumes was 9.8%/7.36. A normalization based on either total intracranial volume (TICV), TICV and age, or v-scale significantly reduced the inter-individual variability of total brainstem volumes compared to non-normalized volumes and similarly reduced the relative standard deviation by about 35%. Conclusion: The extrinsic variability of the novel brainstem segmentation method MD-GRU across different scanners and imaging protocols is very low. Anatomic inter-individual variability of brainstem volumes is substantial. This study presents efficient normalization models for variability reduction in brainstem volumetry in healthy subjects.
The choroid plexus has been shown to play a crucial role in CNS inflammation. Previous studies found larger choroid plexus in multiple sclerosis (MS) compared with healthy controls. However, it is not clear whether the choroid plexus is similarly involved in MS and in neuromyelitis optica spectrum disorder (NMOSD). Thus, the aim of this study was to compare the choroid plexus volume in MS and NMOSD.
Quantitative MRI (qMRI) has greatly improved the sensitivity and specificity of microstructural brain pathology in multiple sclerosis (MS) when compared to conventional MRI (cMRI). More than cMRI, qMRI also provides means to assess pathology within the normal-appearing and lesion tissue. In this work, we further developed a method providing personalized quantitative T1 (qT1) abnormality maps in individual MS patients by modeling the age dependence of qT1 alterations. In addition, we assessed the relationship between qT1 abnormality maps and patients' disability, in order to evaluate the potential value of this measurement in clinical practice.
Rett syndrome (RTT) is defined as a rare disease caused by mutations of the methyl-CpG binding protein 2 (MECP2). It is one of the most common causes of genetic mental retardation in girls, characterized by normal early psychomotor development, followed by severe neurologic regression. Hitherto, RTT lacks a specific biomarker, but altered lipid homeostasis has been found in RTT model mice as well as in RTT patients. We performed LC-MS/MS lipidomics analysis to investigate the cerebrospinal fluid (CSF) and plasma composition of patients with RTT for biochemical variations compared to healthy controls. In all seven RTT patients, we found decreased CSF cholesterol levels compared to age-matched controls (n = 13), whereas plasma cholesterol levels were within the normal range in all 13 RTT patients compared to 18 controls. Levels of phospholipid (PL) and sphingomyelin (SM) species were decreased in CSF of RTT patients, whereas the lipidomics profile of plasma samples was unaltered in RTT patients compared to healthy controls. This study shows that the CSF lipidomics profile is altered in RTT, which is the basis for future (functional) studies to validate selected lipid species as CSF biomarkers for RTT.
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