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      Clinical Characteristics and Disability Progression of Early- and Late-Onset Multiple Sclerosis Compared to Adult-Onset Multiple Sclerosis

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          Abstract

          Background: Compared to the adult onset of multiple sclerosis (AOMS), both early-onset (EOMS) and late-onset (LOMS) are much less frequent, but are often under- or misdiagnosed. The aims of the present study were: 1. To compare demographic and clinical features of individuals with EOMS, AOMS and LOMS, and 2. To identify predictors for disability progression from relapsing remitting MS (RRMS) to secondary progressive MS (SPMS). Method: Data were taken from the Isfahan Hakim MS database. Cases were classified as EOMS (MS onset 18 years), LOMS (MS onset >50 years) and AOMS (MS >18 and 50 years). Patients’ demographic and clinical (initial symptoms; course of disease; disease patterns from MRI; disease progress) information were gathered and assessed. Kaplan–Meier and Cox proportional hazard regressions were conducted to determine differences between the three groups in the time lapse in conversion from relapsing remitting MS to secondary progressive MS. Results: A total of 2627 MS cases were assessed; of these 127 were EOMS, 84 LOMS and 2416 AOMS. The mean age of those with EOMS was 14.5 years; key symptoms were visual impairments, brain stem dysfunction, sensory disturbances and motor dysfunctions. On average, 24.6 years after disease onset, 14.2% with relapsing remitting MS (RRMS) were diagnosed with secondary progressive MS (SPMS). The key predictor variable was a higher Expanded Disability Status Scale (EDSS) score at disease onset. Compared to individuals with AOMS and LOMS, those with EOMS more often had one or two relapses in the first two years, and more often gadolinium-enhancing brain lesions. For individuals with AOMS, mean age was 29.4 years; key symptoms were sensory disturbances, motor dysfunctions and visual impairments. On average, 20.5 years after disease onset, 15.6% with RRMS progressed to SPMS. The key predictors at disease onset were: a higher EDSS score, younger age, a shorter inter-attack interval and spinal lesions. Compared to individuals with EOMS and LOMS, individuals with AOMS more often had either no or three and more relapses in the first two years. For individuals with LOMS, mean age was 53.8 years; key symptoms were motor dysfunctions, sensory disturbances and visual impairments. On average, 14 years after disease onset, 25.3% with RRMS switched to an SPMS. The key predictors at disease onset were: occurrence of spinal lesions and spinal gadolinium-enhancement. Compared to individuals with EOMS and AOMS, individuals with LOMS more often had no relapses in the first two years, and higher EDSS scores at disease onset and at follow-up. Conclusion: Among a large sample of MS sufferers, cases with early onset and late onset are observable. Individuals with early, adult and late onset MS each display distinct features which should be taken in consideration in their treatment.

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          Gene regulation and DNA damage in the ageing human brain.

          The ageing of the human brain is a cause of cognitive decline in the elderly and the major risk factor for Alzheimer's disease. The time in life when brain ageing begins is undefined. Here we show that transcriptional profiling of the human frontal cortex from individuals ranging from 26 to 106 years of age defines a set of genes with reduced expression after age 40. These genes play central roles in synaptic plasticity, vesicular transport and mitochondrial function. This is followed by induction of stress response, antioxidant and DNA repair genes. DNA damage is markedly increased in the promoters of genes with reduced expression in the aged cortex. Moreover, these gene promoters are selectively damaged by oxidative stress in cultured human neurons, and show reduced base-excision DNA repair. Thus, DNA damage may reduce the expression of selectively vulnerable genes involved in learning, memory and neuronal survival, initiating a programme of brain ageing that starts early in adult life.
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            The relation between inflammation and neurodegeneration in multiple sclerosis brains

            Some recent studies suggest that in progressive multiple sclerosis, neurodegeneration may occur independently from inflammation. The aim of our study was to analyse the interdependence of inflammation, neurodegeneration and disease progression in various multiple sclerosis stages in relation to lesional activity and clinical course, with a particular focus on progressive multiple sclerosis. The study is based on detailed quantification of different inflammatory cells in relation to axonal injury in 67 multiple sclerosis autopsies from different disease stages and 28 controls without neurological disease or brain lesions. We found that pronounced inflammation in the brain is not only present in acute and relapsing multiple sclerosis but also in the secondary and primary progressive disease. T- and B-cell infiltrates correlated with the activity of demyelinating lesions, while plasma cell infiltrates were most pronounced in patients with secondary progressive multiple sclerosis (SPMS) and primary progressive multiple sclerosis (PPMS) and even persisted, when T- and B-cell infiltrates declined to levels seen in age matched controls. A highly significant association between inflammation and axonal injury was seen in the global multiple sclerosis population as well as in progressive multiple sclerosis alone. In older patients (median 76 years) with long-disease duration (median 372 months), inflammatory infiltrates declined to levels similar to those found in age-matched controls and the extent of axonal injury, too, was comparable with that in age-matched controls. Ongoing neurodegeneration in these patients, which exceeded the extent found in normal controls, could be attributed to confounding pathologies such as Alzheimer's or vascular disease. Our study suggests a close association between inflammation and neurodegeneration in all lesions and disease stages of multiple sclerosis. It further indicates that the disease processes of multiple sclerosis may die out in aged patients with long-standing disease.
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              Long‐term evolution of multiple sclerosis disability in the treatment era

              Objective To characterize the accrual of long‐term disability in a cohort of actively treated multiple sclerosis (MS) patients and to assess whether clinical and magnetic resonance imaging (MRI) data used in clinical trials have long‐term prognostic value. Methods This is a prospective study of 517 actively managed MS patients enrolled at a single center. Results More than 91% of patients were retained, with data ascertained up to 10 years after the baseline visit. At this last assessment, neurologic disability as measured by the Expanded Disability Status Scale (EDSS) was stable or improved compared to baseline in 41% of patients. Subjects with no evidence of disease activity (NEDA) by clinical and MRI criteria during the first 2 years had long‐term outcomes that were no different from those of the cohort as a whole. 25‐OH vitamin D serum levels were inversely associated with short‐term MS disease activity; however, these levels had no association with long‐term disability. At a median time of 16.8 years after disease onset, 10.7% (95% confidence interval [CI] = 7.2–14%) of patients reached an EDSS ≥ 6, and 18.1% (95% CI = 13.5–22.5%) evolved from relapsing MS to secondary progressive MS (SPMS). Interpretation Rates of worsening and evolution to SPMS were substantially lower when compared to earlier natural history studies. Notably, the NEDA 2‐year endpoint was not a predictor of long‐term stability. Finally, the data call into question the utility of annual MRI assessments as a treat‐to‐target approach for MS care. Ann Neurol 2016;80:499–510
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                Author and article information

                Journal
                J Clin Med
                J Clin Med
                jcm
                Journal of Clinical Medicine
                MDPI
                2077-0383
                02 May 2020
                May 2020
                : 9
                : 5
                : 1326
                Affiliations
                [1 ]Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan 81746-73461, Iran; omid.mirmosayyeb@ 123456gmail.com (O.M.); barzegar_mahdi73@ 123456yahoo.com (M.B.); N.nehzat96@ 123456gmail.com (N.N.)
                [2 ]Universal Council of Epidemiology (UCE), Universal Scientific Education and Research Network (USERN), Tehran University of Medical Sciences, Tehran 14197-33151, Iran
                [3 ]Department of Neurology, Isfahan University of Medical Sciences, Isfahan 81746-73461, Iran
                [4 ]Center of Depression, Stress and Sleep Disorders, Psychiatric Clinics (UPK), University of Basel, 4002 Basel, Switzerland; serge.brand@ 123456upk.ch (S.B.); dena.sadeghibahmani@ 123456upk.ch (D.S.B.)
                [5 ]Division of Sport Science and Psychosocial Health, Department of Sport, Exercise, and Health, University of Basel, 4032 Basel, Switzerland
                [6 ]Substance Abuse Prevention Research Center, Health Institute, Kermanshah University of Medical Sciences (KUMS), Kermanshah 6719851351, Iran
                [7 ]Sleep Disorders Research Center, Health Institute, Kermanshah University of Medical Sciences (KUMS), Kermanshah 6719851351, Iran
                [8 ]School of Medicine, Tehran University of Medical Sciences (TUMS), Tehran 1416753955, Iran
                [9 ]Department of Biostatistics and Epidemiology, Faculty of Health, North Khorasan University of Medical Sciences, Bojnurd 74877-94149, Iran; a.afshari@ 123456nkums.ac.ir
                [10 ]Faculty of Pharmacy, Ahvaz Jundishapur University of Medical Sciences, Ahvaz 6135715794, Iran
                [11 ]Departments of Physical Therapy, University of Alabama at Birmingham, Birmingham, AL 35209, USA
                Author notes
                [†]

                The authors share the first authorship.

                Author information
                https://orcid.org/0000-0003-2175-2765
                https://orcid.org/0000-0002-1301-5522
                Article
                jcm-09-01326
                10.3390/jcm9051326
                7290335
                32370288
                4da1a105-2948-4138-b178-fd5748e1554a
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 28 March 2020
                : 27 April 2020
                Categories
                Article

                multiple sclerosis,age of onset,early onset,late onset,magnetic resonance imaging,predictors,edss score,relapsing-remitting ms,secondary progressive ms

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