EDITORIAL
Characterizing cognitive impairment in multiple sclerosis: an essential step towards prediction and prevention
See paper by V. Planche et al. on page 282.
Cognitive impairment is now recognized as a cardinal symptom of multiple sclerosis (MS), a neurological disease with no cure that affects young adults striving to build careers, start families and juggle the multiple responsibilities of a life in its prime. Cognitive difficulties emerge early in the disease course, thereby hindering successful attainment of these normative goals. MS disease presents differently from one patient to the next, with variability in sensorimotor symptoms and patterns of disease activity. This heterogeneity extends to cognition: current estimates of cognitive impairment are 50%–70% [1], and the association of cognitive status to disease burden measured with magnetic resonance imaging (MRI) (atrophy, lesion load) is relatively weak/incomplete. That is, cognitive status differs amongst MS patients with comparable disease burden (e.g. T2 lesion volume). As such, cognition in MS represents another example of the ‘clinico-radiological paradox’ invoked when we fail to find a close correspondence of radiological disease markers to clinical symptoms. Planche et al. [2] sought to help account for interpatient variability in cognitive outcomes by examining differences in the quality of cognitive impairment across MS disease subtypes. They controlled for disease duration and included only ‘late’ relapsing remitting MS patients (those who had been diagnosed >10 years), thereby investigating differences in cognition that may be phenotype-specific rather than related to such confounding factors as age and disease duration. This is an important step, although larger sample studies are needed to support their findings. This work also suggests that the prevalence of cognitive impairment in MS may be even higher than previously recognized. By employing a populationbased sample, Planche et al. found cognitive impairment in 77% of their full sample, suggesting that research samples may not accurately reflect prevalence of impairment in the broader MS community. The work of Planche et al. identifies disease subtype as a potential source of differential cognitive decline across MS patients, which may ultimately assist us in identifying patients at greatest risk for cognitive decline. Targeting these highest risk patients for early
© 2015 EAN
intervention cognitive treatments maximizes our chance of successful outcomes. A strength of this study is that the authors aimed to describe cognitive impairment across phenotypes, an important direction for research. However, it must be acknowledged that phenotype is only a proxy for the essential differences in the brains of MS patients that account for variability in cognitive status essential differences that remain to be identified. Having structural and functional brain markers that are highly related to and predictive of cognitive decline in MS will provide us with targets for treatment, as well as permit development of novel outcome variables for clinical trials. Deloire et al. [3] identified variables from structural MRI that are predictive of cognitive decline in MS, and we have recently identified hippocampal volume as a potential modifiable neuroanatomical basis for reserve against memory decline in MS [4]. Whilst cross-sectional work reveals functional MRI (fMRI) to be associated with cognitive function in persons with MS (e.g. resting-state functional connectivity within specific networks [5]), future work is needed to test the predictive value of novel fMRI variables for cognitive outcomes. Having structural and functional MRI targets for early intervention trials would be highly useful, as our only means of accurately measuring the success of a treatment for cognition at present is to wait years to observe whether a treatment has staved or stopped cognitive decline. We propose that developing MRI and fMRI outcome variables for clinical trials of cognitive treatments in MS should be a research priority, as having reliable, validated, standardizable MRI and fMRI markers of increased reserve against future cognitive decline would provide the field with a much-needed starting point for developing effective early intervention treatments for cognition. Finally, as we strive to better understand the clinico-pathologic disconnect amongst disease phenotype, disease burden and cognitive status, we must consider key factors that contribute to individual patients’ abilities to withstand cognitive decline. In this study, Planche et al. found a protective effect of education on cognition in their sample, an effect that
225
EUROPEAN JOURNAL OF NEUROLOGY
doi:10.1111/ene.12736
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EDITORIAL
was shown even after adjustment was made with education-based norms. Lifetime intellectual enrichment, IQ and education are all sources of cognitive reserve, which allows persons with MS to maintain intact cognition despite increasing disease burden (for a review see [6]). The theory of cognitive reserve promotes factors within our control (e.g. choosing to spend our time engaging in intellectually stimulating pursuits) as contributing to brain health and the ability to maintain function in the face of aging and/or disease. Accounting for the powerful impact of cognitive reserve will improve our models to predict and characterize cognitive impairment in MS. Moreover, as we work to develop effective treatments for cognitive impairment in MS, the cognitive reserve literature provides promising directions for utilizing intellectual enrichment as an effective means of building reserve [7].
V. M. Leavitta and J. F. Sumowskib a
Department of Neurology, Columbia University Medical Center,
New York, NY; and bNeuropsychology and Neuroscience, Kessler Foundation, West Orange, NJ, USA
(e-mail: [email protected])
References 1. Benedict RH, Cookfair D, Gavett R, et al. Validity of the minimal assessment of cognitive function in multiple sclerosis (MACFIMS). J Int Neuropsychol Soc 2006; 12: 549–558. 2. Planche V, Gibelin M, Cregut D, Pereira B, Clavelou P. Cognitive impairment in a population-based study of patients with multiple sclerosis: differences between late relapsing–remitting, secondary progressive and primary progressive multiple sclerosis. Eur J Neurol 2016; 23: 282–289. 3. Deloire MS, Ruet A, Hamel D, Bonnet M, Dousset V, Brochet B. MRI predictors of cognitive outcome in early multiple sclerosis. Neurology 2011; 76: 1161–1167. 4. Sumowski JF, Rocca MA, Leavitt VM, et al. Searching for the neural basis of reserve against memory decline: intellectual enrichment linked to larger hippocampal volume in multiple sclerosis. Eur J Neurol 2016; 23: 39– 44. 5. Leavitt VM, Paxton J, Sumowski JF. Default network connectivity is linked to memory status in multiple sclerosis. J Int Neuropsychol Soc 2014; 20: 937–944. 6. Sumowski JF, Leavitt VM. Cognitive reserve in multiple sclerosis. Mult Scler 2013; 19: 1122–1127. 7. Sumowski JF, Rocca MA, Leavitt VM, et al. Brain reserve and cognitive reserve in multiple sclerosis: what you’ve got and how you use it. Neurology 2013; 80: 2186–2193.
© 2015 EAN
Characterizing cognitive impairment in multiple sclerosis: an essential step towards prediction and prevention
See paper by V. Planche et al. on page 282.
Cognitive impairment is now recognized as a cardinal symptom of multiple sclerosis (MS), a neurological disease with no cure that affects young adults striving to build careers, start families and juggle the multiple responsibilities of a life in its prime. Cognitive difficulties emerge early in the disease course, thereby hindering successful attainment of these normative goals. MS disease presents differently from one patient to the next, with variability in sensorimotor symptoms and patterns of disease activity. This heterogeneity extends to cognition: current estimates of cognitive impairment are 50%–70% [1], and the association of cognitive status to disease burden measured with magnetic resonance imaging (MRI) (atrophy, lesion load) is relatively weak/incomplete. That is, cognitive status differs amongst MS patients with comparable disease burden (e.g. T2 lesion volume). As such, cognition in MS represents another example of the ‘clinico-radiological paradox’ invoked when we fail to find a close correspondence of radiological disease markers to clinical symptoms. Planche et al. [2] sought to help account for interpatient variability in cognitive outcomes by examining differences in the quality of cognitive impairment across MS disease subtypes. They controlled for disease duration and included only ‘late’ relapsing remitting MS patients (those who had been diagnosed >10 years), thereby investigating differences in cognition that may be phenotype-specific rather than related to such confounding factors as age and disease duration. This is an important step, although larger sample studies are needed to support their findings. This work also suggests that the prevalence of cognitive impairment in MS may be even higher than previously recognized. By employing a populationbased sample, Planche et al. found cognitive impairment in 77% of their full sample, suggesting that research samples may not accurately reflect prevalence of impairment in the broader MS community. The work of Planche et al. identifies disease subtype as a potential source of differential cognitive decline across MS patients, which may ultimately assist us in identifying patients at greatest risk for cognitive decline. Targeting these highest risk patients for early
© 2015 EAN
intervention cognitive treatments maximizes our chance of successful outcomes. A strength of this study is that the authors aimed to describe cognitive impairment across phenotypes, an important direction for research. However, it must be acknowledged that phenotype is only a proxy for the essential differences in the brains of MS patients that account for variability in cognitive status essential differences that remain to be identified. Having structural and functional brain markers that are highly related to and predictive of cognitive decline in MS will provide us with targets for treatment, as well as permit development of novel outcome variables for clinical trials. Deloire et al. [3] identified variables from structural MRI that are predictive of cognitive decline in MS, and we have recently identified hippocampal volume as a potential modifiable neuroanatomical basis for reserve against memory decline in MS [4]. Whilst cross-sectional work reveals functional MRI (fMRI) to be associated with cognitive function in persons with MS (e.g. resting-state functional connectivity within specific networks [5]), future work is needed to test the predictive value of novel fMRI variables for cognitive outcomes. Having structural and functional MRI targets for early intervention trials would be highly useful, as our only means of accurately measuring the success of a treatment for cognition at present is to wait years to observe whether a treatment has staved or stopped cognitive decline. We propose that developing MRI and fMRI outcome variables for clinical trials of cognitive treatments in MS should be a research priority, as having reliable, validated, standardizable MRI and fMRI markers of increased reserve against future cognitive decline would provide the field with a much-needed starting point for developing effective early intervention treatments for cognition. Finally, as we strive to better understand the clinico-pathologic disconnect amongst disease phenotype, disease burden and cognitive status, we must consider key factors that contribute to individual patients’ abilities to withstand cognitive decline. In this study, Planche et al. found a protective effect of education on cognition in their sample, an effect that
225
EUROPEAN JOURNAL OF NEUROLOGY
doi:10.1111/ene.12736
226
EDITORIAL
was shown even after adjustment was made with education-based norms. Lifetime intellectual enrichment, IQ and education are all sources of cognitive reserve, which allows persons with MS to maintain intact cognition despite increasing disease burden (for a review see [6]). The theory of cognitive reserve promotes factors within our control (e.g. choosing to spend our time engaging in intellectually stimulating pursuits) as contributing to brain health and the ability to maintain function in the face of aging and/or disease. Accounting for the powerful impact of cognitive reserve will improve our models to predict and characterize cognitive impairment in MS. Moreover, as we work to develop effective treatments for cognitive impairment in MS, the cognitive reserve literature provides promising directions for utilizing intellectual enrichment as an effective means of building reserve [7].
V. M. Leavitta and J. F. Sumowskib a
Department of Neurology, Columbia University Medical Center,
New York, NY; and bNeuropsychology and Neuroscience, Kessler Foundation, West Orange, NJ, USA
(e-mail: [email protected])
References 1. Benedict RH, Cookfair D, Gavett R, et al. Validity of the minimal assessment of cognitive function in multiple sclerosis (MACFIMS). J Int Neuropsychol Soc 2006; 12: 549–558. 2. Planche V, Gibelin M, Cregut D, Pereira B, Clavelou P. Cognitive impairment in a population-based study of patients with multiple sclerosis: differences between late relapsing–remitting, secondary progressive and primary progressive multiple sclerosis. Eur J Neurol 2016; 23: 282–289. 3. Deloire MS, Ruet A, Hamel D, Bonnet M, Dousset V, Brochet B. MRI predictors of cognitive outcome in early multiple sclerosis. Neurology 2011; 76: 1161–1167. 4. Sumowski JF, Rocca MA, Leavitt VM, et al. Searching for the neural basis of reserve against memory decline: intellectual enrichment linked to larger hippocampal volume in multiple sclerosis. Eur J Neurol 2016; 23: 39– 44. 5. Leavitt VM, Paxton J, Sumowski JF. Default network connectivity is linked to memory status in multiple sclerosis. J Int Neuropsychol Soc 2014; 20: 937–944. 6. Sumowski JF, Leavitt VM. Cognitive reserve in multiple sclerosis. Mult Scler 2013; 19: 1122–1127. 7. Sumowski JF, Rocca MA, Leavitt VM, et al. Brain reserve and cognitive reserve in multiple sclerosis: what you’ve got and how you use it. Neurology 2013; 80: 2186–2193.
© 2015 EAN
![[Pathogenesis of cognitive impairment in multiple sclerosis].](/assets/img/hold.png)
