Deep gray matter volume loss drives disability worsening in multiple sclerosis

Eshaghi, Arman; Prados, Ferrán; Brownlee, Wallace; Altmann, Daniel R.; Tur, Carmen; Cardoso, M. Jorge; Angelis, Floriana De; Pavert, Steven H van de; Cawley, Niamh; Stefano, Nicola De; Stromillo, ML; Battaglini, Marco; Ruggieri, Serena; Gasperini, Claudio; Filippi, Massimo; Rocca, Maria A.; Rovira, Àlex; Sastre‐Garriga, Jaume; Vrenken, Hugo; Leurs, Cyra E.; Killestein, Joep; Pirpamer, Lukas; Enzinger, Christian; Ourselin, Sébastien; Wheeler-Kingshott, C; Chard, Declan; Thompson, Alan J.; Alexander, Daniel C.; Barkhof, Frederik; Ciccarelli, Olga

doi:10.1002/ana.25145

Cited by 308 publications

(319 citation statements)

References 68 publications

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“…Previous works have detected atrophy in deep gray matter regions of patients with MS, including the thalamus, caudate, putamen, and brain stem. These structures have a wide range of functions, including sensory and motor processing, which become restricted in MS due to the accumulating inflammatory and neurodegenerative processes (Deppe et al, 2016;Eshaghi et al, 2018;Steenwijk et al, 2016). We could show that the pons was the structure driving the atrophy effects in the brain stem.…”

Section: Gray Matter Atrophymentioning

confidence: 84%

“…These structures have a wide range of functions, including sensory and motor processing, which become restricted in MS due to the accumulating inflammatory and neurodegenerative processes (Deppe et al, 2016;Eshaghi et al, 2018;Steenwijk et al, 2016). These structures have a wide range of functions, including sensory and motor processing, which become restricted in MS due to the accumulating inflammatory and neurodegenerative processes (Deppe et al, 2016;Eshaghi et al, 2018;Steenwijk et al, 2016).…”

Section: Gray Matter Atrophymentioning

confidence: 99%

“…By means of magnetic resonance imaging (MRI), a decrease of cortical thickness has been observed in the posterior cortices, temporal lobe, and precentral gyrus with progressing MS (Eshaghi et al, 2018;Steenwijk et al, 2016). Subcortical volume mainly decreased in deep gray matter structures including thalamus, caudate, and brain stem, as well as cerebellar regions (Deppe et al, 2016;Eshaghi et al, 2018) in early stages of MS. Atrophy of deep gray matter nuclei is strongly related to cognitive impairment in MS (Damjanovic et al, 2017). In particular, thalamic atrophy is predictive of cognitive decline (Papathanasiou et al, 2015;Štecková et al, 2014) and correlates with physical disability (Deppe et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

“…Advanced imaging techniques allow investigation of both the integrity of white and gray matter in order to evaluate disease progression (Fleischer et al, 2017;Fleischer, Radetz, et al, 2019;Muthuraman et al, 2016). By means of magnetic resonance imaging (MRI), a decrease of cortical thickness has been observed in the posterior cortices, temporal lobe, and precentral gyrus with progressing MS (Eshaghi et al, 2018;Steenwijk et al, 2016). Subcortical volume mainly decreased in deep gray matter structures including thalamus, caudate, and brain stem, as well as cerebellar regions (Deppe et al, 2016;Eshaghi et al, 2018) in early stages of MS. Atrophy of deep gray matter nuclei is strongly related to cognitive impairment in MS (Damjanovic et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

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Gray matter integrity predicts white matter network reorganization in multiple sclerosis

Radetz

Koirala

Krämer

et al. 2019

Human Brain Mapping

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Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease leadingto gray matter atrophy and brain network reconfiguration as a response to increasing tissue damage. We evaluated whether white matter network reconfiguration appears subsequently to gray matter damage, or whether the gray matter degenerates following alterations in white matter networks. MRI data from 83 patients with clinically isolated syndrome and early relapsing-remitting MS were acquired at two time points with a follow-up after 1 year. White matter network integrity was assessed based on probabilistic tractography performed on diffusion-weighted data using graph theoretical analyses.We evaluated gray matter integrity by computing cortical thickness and deep gray matter volume in 94 regions at both time points. The thickness of middle temporal cortex and the volume of deep gray matter regions including thalamus, caudate, putamen, and brain stem showed significant atrophy between baseline and follow-up. White matter network dynamics, as defined by modularity and distance measure changes over time, were predicted by deep gray matter volume of the atrophying anatomical structures. Initial white matter network properties, on the other hand, did not predict atrophy. Furthermore, gray matter integrity at baseline significantly predicted physical disability at 1-year follow-up. In a sub-analysis, deep gray matter volume was significantly related to cognitive performance at baseline. Hence, we postulate that atrophy of deep gray matter structures drives the adaptation of white matter networks. Moreover, deep gray matter volumes are highly predictive for disability progression and cognitive performance.

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Section: Gray Matter Atrophymentioning

confidence: 84%

Section: Gray Matter Atrophymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Gray matter integrity predicts white matter network reorganization in multiple sclerosis

Radetz

Koirala

Krämer

et al. 2019

Human Brain Mapping

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“…Indeed, it is increasingly recognized that pathology in the gray matter including the cortex is central to the progression of MS (Calabrese et al, 2015;Mahad et al, 2015;Ontaneda et al, 2017). Gray matter pathology correlates with accruing disability, predicts conversion to progressive MS 10 and explains the increasing cognitive deficits that MS patients with advanced disease experience (Damjanovic et al, 2017;Eshaghi et al, 2018;Ontaneda et al, 2017;Scalfari et al, 2018). Despite this profound clinical importance, our understanding of the mechanisms underlying cortical pathology in progressive MS remains poor, in part because modelling gray matter inflammation has been difficult.…”

Section: Introductionmentioning

confidence: 99%

Localized calcium accumulations prime synapses for phagocyte removal in cortical neuroinflammation

Jafari

Schumacher

Snaidero

et al. 2019

Preprint

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Cortical pathology contributes to chronic cognitive impairment of patients suffering from the neuroinflammatory disease multiple sclerosis (MS). How such gray matter inflammation affects neuronal structure and function is not well understood. Here we use functional and structural in vivo imaging in a mouse model of cortical MS to demonstrate that bouts of cortical 5 inflammation disrupt cortical circuit activity coincident with a widespread but transient loss of dendritic spines. Spines destined for removal show a local calcium accumulation and are subsequently removed by invading macrophages and activated microglia. Targeting phagocyte activation with a new antagonist of the colony-stimulating factor 1 receptor prevents cortical synapse loss. Overall, our study identifies synapse loss as a key pathological feature of 10 inflammatory gray matter lesions that is amenable to immunomodulatory therapy. HIGHLIGHTS:• Widespread, but transient loss of synapses in inflammatory lesions and beyond • Reversible impairment of neuronal firing and circuit function in the inflamed cortex • Calcium dyshomeostasis of single spines precedes swift synapse loss 20• Phagocyte-mediated spine pruning as targetable mechanism of synapse loss Jafari, Schumacher, Snaidero et al.2

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Diagnosis of Progressive Multiple Sclerosis From the Imaging Perspective

et al. 2021

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agnetic resonance imaging (MRI) is central in the diagnostic workup of patients with suspected multiple sclerosis (MS) given its high sensitivity to detect disease dissemination in space and over time and its substantial, albeit imperfect, ability to exclude other mimics of MS. From 2001 until 2017, great effort was expended providing successive iterations of the McDonald criteria to define imaging features typical of MS in patients presenting with clinically isolated syndrome (CIS). 1 However, diagnosis of primary progressive (PP) MS remains challenging and is only possible retrospectively based on clinical assessment.Identification of imaging features associated with PPMS and features that predict evolution from relapsing-remitting (RR) MS to secondary progressive (SP) MS is an important unmet need. Given the advent of effective therapies for RRMS that may reduce development of SPMS and limit disability worsening in progressive MS (PMS), 2 the need for such imaging indicators is all the greater.Diagnosis of PMS is limited by difficulties in distinguishing accumulating disability due to inflammatory disease activity from that attributable to degenerative processes associated with SPMS. Moreover, there are no accepted clinical criteria for diagnosing SPMS. 3,4 This need has promoted extensive research in the field of imaging, facilitated by definition of novel MRI sequences, to identify imaging features reflecting pathophysiological mechanisms relevant to the pathobiology of PMS. MethodsIn this review, we report the conclusions of the "Diagnosis of Progressive MS: The Imaging Perspective" workshop held in Milan,

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Deep gray matter volume loss drives disability worsening in multiple sclerosis

Cited by 308 publications

References 68 publications

Gray matter integrity predicts white matter network reorganization in multiple sclerosis

Gray matter integrity predicts white matter network reorganization in multiple sclerosis

Localized calcium accumulations prime synapses for phagocyte removal in cortical neuroinflammation

Diagnosis of Progressive Multiple Sclerosis From the Imaging Perspective

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