bioRxiv ScienceSearch

bioRxiv · 10.1101/385898

A prospective, observational study on conversion of Clinically Isolated Syndrome to Multiple Sclerosis during 4-year period (MS NEO study) in Taiwan

Abstract

ImportanceCIS to MS conversion rates vary depending on population cohorts, initial manifestations, and durations of follow-up.\n\nObjectiveTo investigate conversion rate of patients from CIS to MS and the prognostic significance of demographic and clinical variables in Taiwanese population.\n\nDesignNationwide, prospective, multi-centric, observational study from November 2008 to November 2014 with 4 years follow-up.\n\nSettingMulti-centre setting at 5 institutions in Taiwan.\n\nParticipants152 patients having single clinical event potentially suggestive of MS in last 2 years were enrolled as consecutive sample. 33 patients were lost to follow-up and 16 patients did not complete the study.103 patients completed the study.\n\nIntervention(s) (for clinical trials) or Exposure(s) (for observational studies)Natural progression from first episode of CIS to MS or NMO was observed.\n\nMain Outcome(s) and Measure(s)Variables analysed were proportion of patients converting to MS or NMO after first episode of CIS, duration between first episode of neurological event and diagnosis of MS, status of anti-AQP4 IgG and length of longest contiguous spinal cord lesion in MS patients. Association between baseline characteristics and progression to MS from CIS was analyzed using multiple logistic regression. Multivariate time dependent effect of baseline characteristics on progression to MS was plotted.\n\nResults14.5% patients with CIS converted to MS after 1.1 {+/-} 1.0 years with greater predisposition (18.8%) in those having syndromes referable to the cerebral hemispheres. Conversion rate from ON to MS was 9.7%. 90.9% patients had benign disease course. 46.7% patients had abnormal MRIs at baseline, with 0.6{+/-}0.5 contrast enhanced lesions. Below normal BMI and MRI lesion load ([≥] 4 lesions) were identified as risk indicators for the development of MS. Only 4.5% were positive for anti-AQP4 antibody in MS patients and amongst them, 80% were NMO patients as diagnosed by modern criteria.\n\nConclusions and Relevance Below normal BMI and number of demyelinating lesions ([≥]4) are significant predictors of conversion from CIS to MS. A low conversion rate to MS in Taiwanese CIS patients and majority of them having a benign course and minimal disability suggest the roles of geographic, genetic and ethnic factors.\n\nTrial RegistrationNon-trial observational study.

Source connections

Explore related subjects

Keep this discovery

BibTeXRIS

Ro, L.-S., Yang, C.-C., Lyu, R.-K., Lin, K.-P., Tsai, T.-C., Lu, S.-R., Huang, L.-C., Tsai, C.-P., Chang, K.-H.. 2018-08-06. A prospective, observational study on conversion of Clinically Isolated Syndrome to Multiple Sclerosis during 4-year period (MS NEO study) in Taiwan. https://doi.org/10.1101/385898

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience