Graph theoretical analysis helps to gain insight into functional reorganisation in MS. Italian researchers developed advanced machine-learning methods to analyse data on resting-state functional connectivity and classify MS patients according to disease phenotype [1]. They obtained fMRI scans from 46 healthy controls and 113 MS patients (62 with relapsing-remitting MS and 51 with progressive MS). By way of dominant set clustering, functional connectivity matrices were grouped into patients with similar network configurations. Disease phenotypes were classified using linear support vector machines.
This approach helped to distinguish relapsing-remitting MS patients from healthy controls with an accuracy rate of 72.5%. A sensitivity analysis revealed the following key features that differentiated relapsing-remitting MS as well as progressive MS patients from healthy controls: increased connectivity within the basal ganglia sub-network and decreased functional connectivity within the temporal sub-network. Decreased functional connectivity within the occipital and parietal sub-networks contributed to differentiate progressive MS patients from healthy controls. Altered thalamic and frontal resting-state functional connectivity occurred in all phenotypes and may be a hallmark of MS. The involvement of occipitotemporal subnetworks in relapsing-remitting MS patients may be secondary to damage of associative sensory regions. The involvement of the parietal regions in progressive MS suggests a spreading of damage to high-order, associative regions, leading to impaired network integration.
In another very recent study, machine learning applied to brain MRI scans from 6,322 MS patients resulted in the definition of 3 MS subtypes: cortex-led, normal-appearing white matter-led, and lesion-led [2]. The lesion-led subtype had the highest risk of confirmed disability progression and the highest relapse rate, but also predicted positive treatment response in clinical trials.
- Rocca MA, et al. Classifying and characterizing multiple sclerosis disease phenotypes with functional connectivity and machine learning. OPR-112, EAN 2021 Virtual Congress, 19–22 June.
- Eshaghi A, et al. Nat Commun. 2021;12(1):2078.
Copyright ©2021 Medicom Medical Publishers
Posted on
Previous Article
« Positive results from ublituximab versus teriflunomide Next Article
Typing behaviour to remotely monitor clinical MS status »
« Positive results from ublituximab versus teriflunomide Next Article
Typing behaviour to remotely monitor clinical MS status »
Table of Contents: EAN 2021
Featured articles
Letter from the Editor
COVID-19
First evidence of brainstem involvement in COVID-19
Cognitive/behavioural alterations persistent after COVID-19
Neural base of persistent hyposmia after COVID-19
Neurological symptoms and complications of COVID-19 affect outcomes
Cerebrovascular Disease
Intracerebral haemorrhage only slightly increases mortality in COVID-19 patients
Stroke with covert brain infarction indicates high vascular risk
Expanding precision medicine to stroke care
Dexamethasone not indicated for chronic subdural haematoma
Cognitive Impairment and Dementia
Severe outcomes of COVID-19 in patients with dementia
Promising diagnostic accuracy of plasma GFAP
Sex modulates effect of cognitive reserve on subjective cognitive decline
Hypersensitivity to uncertainty in subjective cognitive decline
Epilepsy
Minimally invasive device to detect focal seizure activity
‘Mozart effect’ in epilepsy: why Mozart tops Haydn
Migraine and Headache
Factors associated with decreased migraine attack risk
Pregnant migraine patients at higher risk of complications
Occipital nerve stimulation in drug-resistant cluster headache
Rhythmicity in primary headache disorders
Multiple Sclerosis and NMOSD
Typing behaviour to remotely monitor clinical MS status
Alemtuzumab in treatment-naïve patients with aggressive MS
No higher early MS relapse frequency after stopping ponesimod
Good long-term safety and efficacy of inebilizumab in NMOSD
Neuromuscular Disorders
Inability to recognise disgust as first cognitive symptom of ALS
Pathogenic T-cell signature identified in myasthenia gravis
Parkinson’s Disease
Levodopa-carbidopa intestinal gel in patients with advanced PD
New Frontier – Navigated Transcranial Ultrasound
Exploring the possibilities
Related Articles
August 18, 2021
Typing behaviour to remotely monitor clinical MS status
August 18, 2021
Hypersensitivity to uncertainty in subjective cognitive decline
August 18, 2021
Eptinezumab shows acute benefits during migraine attack
© 2024 Medicom Medical Publishers. All rights reserved. Terms and Conditions | Privacy Policy
HEAD OFFICE
Laarderhoogtweg 25
1101 EB Amsterdam
The Netherlands
T: +31 85 4012 560
E: publishers@medicom-publishers.com