Literature DB >> 33393981

Identifying the Distinct Cognitive Phenotypes in Multiple Sclerosis.

Ermelinda De Meo1,2,3, Emilio Portaccio4,5, Antonio Giorgio6, Luis Ruano7,8, Benedetta Goretti3, Claudia Niccolai5, Francesco Patti9, Clara Grazia Chisari9, Paolo Gallo10, Paola Grossi11, Angelo Ghezzi12, Marco Roscio12, Flavia Mattioli13, Chiara Stampatori13, Marta Simone14, Rosa Gemma Viterbo14, Raffaello Bonacchi1,2,15, Maria A Rocca1,15, Nicola De Stefano6, Massimo Filippi1,2,15,16, Maria Pia Amato3,5.   

Abstract

Importance: Cognitive impairment is a common and disabling feature of multiple sclerosis (MS), but a precise characterization of cognitive phenotypes in patients with MS is lacking.
Objectives: To identify cognitive phenotypes in a clinical cohort of patients with MS and to characterize their clinical and magnetic resonance imaging (MRI) features. Design, Setting, and Participants: This multicenter cross-sectional study consecutively screened clinically stable patients with MS and healthy control individuals at 8 MS centers in Italy from January 1, 2010, to October 31, 2019. Patients with MS and healthy control individuals who were not using psychoactive drugs and had no history of other neurological or medical disorders, learning disability, severe head trauma, and alcohol or drug abuse were enrolled. Main Outcomes and Measures: Participants underwent a neurological examination and a cognitive evaluation with the Rao Brief Repeatable Battery and Stroop Color and Word Test. A subgroup of participants also underwent a brain MRI examination. Latent profile analysis was used on cognitive test z scores to identify cognitive phenotypes. Linear regression and mixed-effects models were used to define clinical and MRI features of each phenotype.
Results: A total of 1212 patients with MS (mean [SD] age, 41.1 [11.1] years; 784 women [64.7%]) and 196 healthy control individuals (mean [SD] age, 40.4 [8.6] years; 130 women [66.3%]) were analyzed in this study. Five cognitive phenotypes were identified: preserved cognition (n = 235 patients [19.4%]), mild-verbal memory/semantic fluency (n = 362 patients [29.9%]), mild-multidomain (n = 236 patients [19.5%]), severe-executive/attention (n = 167 patients [13.8%]), and severe-multidomain (n = 212 patients [17.5%]) involvement. Patients with preserved cognition and mild-verbal memory/semantic fluency were younger (mean [SD] age, 36.5 [9.8] years and 38.2 [11.1] years) and had shorter disease duration (mean [SD] 8.0 [7.3] years and 8.3 [7.6] years) compared with patients with mild-multidomain (mean [SD] age, 42.6 [11.2] years; mean [SD] disease duration, 12.8 [9.6] years; P < .001), severe-executive/attention (mean [SD] age, 42.9 [11.7] years; mean [SD] disease duration, 12.2 [9.5] years; P < .001), and severe-multidomain (mean [SD] age, 44.0 [11.0] years; mean [SD] disease duration, 13.3 [10.2] years; P < .001) phenotypes. Severe cognitive phenotypes prevailed in patients with progressive MS. At MRI evaluation, compared with those with preserved cognition, patients with mild-verbal memory/semantic fluency exhibited decreased mean (SE) hippocampal volume (5.42 [0.68] mL vs 5.13 [0.68] mL; P = .04), patients with the mild-multidomain phenotype had decreased mean (SE) cortical gray matter volume (687.69 [35.40] mL vs 662.59 [35.48] mL; P = .02), patients with severe-executive/attention had higher mean (SE) T2-hyperintense lesion volume (51.33 [31.15] mL vs 99.69 [34.07] mL; P = .04), and patients with the severe-multidomain phenotype had extensive brain damage, with decreased volume in all the brain structures explored, except for nucleus pallidus, amygdala and caudate nucleus. Conclusions and Relevance: This study found that by defining homogeneous and clinically meaningful phenotypes, the limitations of the traditional dichotomous classification in MS can be overcome. These phenotypes can represent a more meaningful measure of the cognitive status of patients with MS and can help define clinical disability, support clinicians in treatment choices, and tailor cognitive rehabilitation strategies.

Entities:  

Mesh:

Year:  2021        PMID: 33393981      PMCID: PMC7783596          DOI: 10.1001/jamaneurol.2020.4920

Source DB:  PubMed          Journal:  JAMA Neurol        ISSN: 2168-6149            Impact factor:   18.302


  11 in total

1.  The role of cerebellar damage in explaining disability and cognition in multiple sclerosis phenotypes: a multiparametric MRI study.

Authors:  Raffaello Bonacchi; Alessandro Meani; Elisabetta Pagani; Olga Marchesi; Massimo Filippi; Maria A Rocca
Journal:  J Neurol       Date:  2022-03-01       Impact factor: 4.849

2.  Characterizing fatigue phenotypes with other symptoms and clinically relevant outcomes among people with multiple sclerosis.

Authors:  Matthew Plow; Douglas D Gunzler; Julia H C Chang
Journal:  Qual Life Res       Date:  2022-08-18       Impact factor: 3.440

3.  Diagnosis of coexistent neurodegenerative dementias in multiple sclerosis.

Authors:  Diana P Londoño; Kogulavadanan Arumaithurai; Eleni Constantopoulos; Michael R Basso; R Ross Reichard; Eoin P Flanagan; B Mark Keegan
Journal:  Brain Commun       Date:  2022-06-22

4.  Integrated Cognitive Rehabilitation Home-Based Protocol to Improve Cognitive Functions in Multiple Sclerosis Patients: A Randomized Controlled Study.

Authors:  Minoo Sharbafshaaer; Francesca Trojsi; Simona Bonavita; Amirreza Azimi
Journal:  J Clin Med       Date:  2022-06-20       Impact factor: 4.964

5.  Improved prediction of early cognitive impairment in multiple sclerosis combining blood and imaging biomarkers.

Authors:  Tobias Brummer; Muthuraman Muthuraman; Falk Steffen; Timo Uphaus; Lena Minch; Maren Person; Frauke Zipp; Sergiu Groppa; Stefan Bittner; Vinzenz Fleischer
Journal:  Brain Commun       Date:  2022-07-08

Review 6.  Cognitive Decline in Older People with Multiple Sclerosis-A Narrative Review of the Literature.

Authors:  Hsueh-Sheng Chiang; Alka Khera; Barbara E Stopschinski; Olaf Stuve; John Hart; Brendan Kelley; Trung Nguyen
Journal:  Geriatrics (Basel)       Date:  2022-06-05

7.  Neuropsychological evaluation and rehabilitation in multiple sclerosis (NEuRoMS): protocol for a mixed-methods, multicentre feasibility randomised controlled trial.

Authors:  Gogem Topcu; Laura Smith; Jacqueline R Mhizha-Murira; Nia Goulden; Zoë Hoare; Avril Drummond; Deborah Fitzsimmons; Nikos Evangelou; Klaus Schmierer; Emma C Tallantyre; Paul Leighton; Kimberley Allen-Philbey; Andrea Stennett; Paul Bradley; Clare Bale; James Turton; Roshan das Nair
Journal:  Pilot Feasibility Stud       Date:  2022-06-11

Review 8.  Machine Learning Use for Prognostic Purposes in Multiple Sclerosis.

Authors:  Ruggiero Seccia; Silvia Romano; Marco Salvetti; Andrea Crisanti; Laura Palagi; Francesca Grassi
Journal:  Life (Basel)       Date:  2021-02-05

9.  Identifying and revealing different brain neural activities of cognitive subtypes in early course schizophrenia.

Authors:  Tiannan Shao; Weiyan Wang; Gangrui Hei; Ye Yang; Yujun Long; Xiaoyi Wang; Jingmei Xiao; Yuyan Huang; Xueqin Song; Xijia Xu; Shuzhan Gao; Jing Huang; Ying Wang; Jingping Zhao; Renrong Wu
Journal:  Front Mol Neurosci       Date:  2022-10-03       Impact factor: 6.261

Review 10.  Structural and Functional Connectivity Substrates of Cognitive Impairment in Multiple Sclerosis.

Authors:  Jian Zhang; Rosa Cortese; Nicola De Stefano; Antonio Giorgio
Journal:  Front Neurol       Date:  2021-07-08       Impact factor: 4.003

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