Understanding brain function through small vessel disease: What zebras can teach us about horses Sudha Seshadri and Frank-Erik de Leeuw Neurology 2014;82;1940-1941 Published Online before print May 2, 2014 DOI 10.1212/WNL.0000000000000484 This information is current as of May 2, 2014
The online version of this article, along with updated information and services, is located on the World Wide Web at: http://www.neurology.org/content/82/22/1940.full.html
Neurology ® is the official journal of the American Academy of Neurology. Published continuously since 1951, it is now a weekly with 48 issues per year. Copyright © 2014 American Academy of Neurology. All rights reserved. Print ISSN: 0028-3878. Online ISSN: 1526-632X.
EDITORIAL
Understanding brain function through small vessel disease What zebras can teach us about horses
Sudha Seshadri, MD Frank-Erik de Leeuw, MD, PhD
Correspondence to Dr. Seshadri: [email protected] Neurology® 2014;82:1940–1941
When you hear hoofbeats in the night, think of horses, not zebras!
So goes the adage attributed to Dr. Theodore Woodward of the University of Maryland. But perhaps considering the habits of zebras could teach us about their more common equine cousins. Traditionally, our knowledge about the correlation of normal structure and function in the brain has relied, to a large extent, on studying the disruption wrought by disease processes on normal function, whether this disrupted structure was detected at autopsy or more recently by CT and MRI. This led to the common dictum that neurology was learned “stroke by stroke” (lesion-symptom mapping). In the last 5 years, higher-resolution MRI scanners (3T and 7T machines) and innovative scanning protocols and analytic methods have exponentially expanded our ability to “see” subtle details of brain structure in living persons.1 In parallel, genetic studies have shown that mildly damaging genetic variants located within genes associated with severe monogenic disorders (“the diagnostic zebras”) may explain a larger proportion of common disease (“the horses”) than had been previously suspected. One example is NOTCH3, the gene underlying cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), variants within which are associated with greater white matter lesion load in healthy adults in the community.2 Vascular cognitive impairment (VCI) is a distressingly common condition that remains difficult to precisely diagnose and define, partly because of poor lesion– symptom correlation. Conventional MRI markers of small vessel disease (SVD), white matter hyperintensities/lesions and lacunar infarcts, are the most common structural surrogates of VCI in population samples, but the correlation is far from perfect, with a wide range of cognitive function observed in persons with apparently identical burdens of white matter lesions.3 Thus, the question looms: can parallels be drawn between common and rare types of VCI and can the use of novel image analysis tools improve our understanding of VCI?
In this issue of Neurology®, Duering et al.4 examined whether a previously noted association in patients with CADASIL, of white matter injury within frontalsubcortical circuits with lower processing speed,5 was replicable in a community-based sample of older adults. They analyzed brain MRI data on 584 dementia- and stroke-free participants in the Austrian Stroke Prevention Study using 2 novel image analysis techniques, voxel-based lesion-symptom mapping (determining which voxels were most likely to have white matter lesions in persons with poorer cognition), and Bayesian network analysis of lesion volumes within major white matter tracts (determining which tracts were most likely to have white matter lesions in these persons). They observed that deficits in processing speed, measured by performance on the Trail Making Test B and reaction time tasks, were related to SVD in 2 specific areas, the frontal interhemispheric (forceps minor) and (anterior) thalamic projection fiber tracts, but not to the total volume of white matter lesions. What are the implications of this study? It partly explains the poor correlation observed in prior structural– functional (lesion–symptom) studies of SVD as a consequence of an inadequate resolution of images. It also suggests that extrapolating from observations in CADASIL and other monogenic variants of SVD can provide novel insights into sporadic VCI. However, whereas this study emphasizes the importance of specific frontal–subcortical circuits in determining processing speed, it does not resolve whether this association is due to primary white matter microstructural injury, injury to the adjacent cortex, or disturbance of functional connectivity networks. Further, variation in the integrity of these tracts explained only 1.8% of the variance in processing speed observed. Brain parenchymal volume did not predict processing speed, but studying other aspects of brain structure, such as MRI infarcts, fractional anisotropy on diffusion tensor imaging (which detects microstructural white matter injury), and amyloid burden (extent of concomitant degenerative pathology), might have increased the proportion of variance
See page 1946 From the Department of Neurology at Boston University School of Medicine (S.S.); the Framingham Heart Study (S.S.), Framingham, MA; and the Department of Neurology (F.-E.d.L.), Donders Institute of Brain Behaviour & Cognition, Center for Neuroscience, Radboud University Medical Center Nijmegen, the Netherlands. Go to Neurology.org for full disclosures. Funding information and disclosures deemed relevant by the authors, if any, are provided at the end of the editorial. 1940
© 2014 American Academy of Neurology
explained.6 In addition, hypertension and diabetes had effects on processing speed independent of their deleterious effects on the studied fiber tracts, and various demographic (age, sex, education) and lifestyle factors (sleep, physical activity, smoking, diet) can likely also affect processing speed through pathways that might not alter brain structure on MRI. Some strengths of this study are the large populationbased sample; the congruent findings from the 2 different methods used, which increases our confidence in the findings; and the use of 1.5T and 3T MRI scans, comparable in quality to those routinely obtained in clinical settings. One limitation was that the observed association was largely restricted to performance on a single cognitive test, the Trail Making Test B, and was not seen with 2 other tests of executive function examined; hence, the impact of injuries in these 2 locations on the performance of daily activities remains to be studied. Another limitation is the cross-sectional study design. However, longitudinal studies on community-dwelling adults that explore the clinical consequences of SVD by combining novel imaging techniques such as diffusion tensor imaging and fMRI with repeated clinical assessments are currently under way,7 and these studies, in conjunction with the adoption of more uniform descriptions of SVD on imaging,8 have the potential to greatly expand our understanding of VCI. AUTHOR CONTRIBUTIONS Sudha Seshadri: drafting/revising the manuscript, study concept or design. Frank-Erik de Leeuw: drafting/revising the manuscript.
STUDY FUNDING Supported by grants from the National Institute on Aging (R01 AG08122), the National Institute of Neurological Disorders and Stroke
(R01 NS17950), and a VIDI innovational grant from Dutch Organization for Scientific Research (grant 016.126.351).
DISCLOSURE The authors report no disclosures relevant to the manuscript. Go to Neurology.org for full disclosures.
REFERENCES 1. Nielsen AS, Kinkel RP, Madigan N, Tinelli E, Benner T, Mainero C. Contribution of cortical lesion subtypes at 7T MRI to physical and cognitive performance in MS. Neurology 2013;81:641–649. 2. Schmidt H, Zeginigg M, Wiltgen M, et al. Genetic variants of the NOTCH3 gene in the elderly and magnetic resonance imaging correlates of age-related cerebral small vessel disease. Brain 2011;134:3384–3397. 3. Debette S, Markus HS. The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis. BMJ 2010; 341:c3666. 4. Duering M, Gesierich B, Seiler S, et al. Strategic white matter tracts for processing speed deficits in age-related small vessel disease. Neurology 2014;82:1946–1950. 5. Duering M, Zieren N, Herve D, et al. Strategic role of frontal white matter tracts in vascular cognitive impairment: a voxel-based lesion-symptom mapping study in CADASIL. Brain 2011;134:2366–2375. 6. Viswanathan A, Godin O, Jouvent E, et al. Impact of MRI markers in subcortical vascular dementia: a multi-modal analysis in CADASIL. Neurobiol Aging 2010;31:1629–1636. 7. van der Holst HM, Tuladhar AM, van Norden AG, et al. Microstructural integrity of the cingulum is related to verbal memory performance in elderly with cerebral small vessel disease: the RUN DMC study. Neuroimage 2013; 65:416–423. 8. Wardlaw JM, Smith EE, Biessels GJ, et al. Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration. Lancet Neurol 2013;12:822–838.
Neurology 82
June 3, 2014
1941
Understanding brain function through small vessel disease: What zebras can teach us about horses Sudha Seshadri and Frank-Erik de Leeuw Neurology 2014;82;1940-1941 Published Online before print May 2, 2014 DOI 10.1212/WNL.0000000000000484 This information is current as of May 2, 2014 Updated Information & Services
including high resolution figures, can be found at: http://www.neurology.org/content/82/22/1940.full.html
References
This article cites 8 articles, 5 of which you can access for free at: http://www.neurology.org/content/82/22/1940.full.html##ref-list1
Subspecialty Collections
This article, along with others on similar topics, appears in the following collection(s): All Cerebrovascular disease/Stroke http://www.neurology.org//cgi/collection/all_cerebrovascular_dis ease_stroke All epidemiology http://www.neurology.org//cgi/collection/all_epidemiology Executive function http://www.neurology.org//cgi/collection/executive_function MRI http://www.neurology.org//cgi/collection/mri Vascular dementia http://www.neurology.org//cgi/collection/vascular_dementia
Permissions & Licensing
Information about reproducing this article in parts (figures,tables) or in its entirety can be found online at: http://www.neurology.org/misc/about.xhtml#permissions
Reprints
Information about ordering reprints can be found online: http://www.neurology.org/misc/addir.xhtml#reprintsus
The online version of this article, along with updated information and services, is located on the World Wide Web at: http://www.neurology.org/content/82/22/1940.full.html
Neurology ® is the official journal of the American Academy of Neurology. Published continuously since 1951, it is now a weekly with 48 issues per year. Copyright © 2014 American Academy of Neurology. All rights reserved. Print ISSN: 0028-3878. Online ISSN: 1526-632X.
EDITORIAL
Understanding brain function through small vessel disease What zebras can teach us about horses
Sudha Seshadri, MD Frank-Erik de Leeuw, MD, PhD
Correspondence to Dr. Seshadri: [email protected] Neurology® 2014;82:1940–1941
When you hear hoofbeats in the night, think of horses, not zebras!
So goes the adage attributed to Dr. Theodore Woodward of the University of Maryland. But perhaps considering the habits of zebras could teach us about their more common equine cousins. Traditionally, our knowledge about the correlation of normal structure and function in the brain has relied, to a large extent, on studying the disruption wrought by disease processes on normal function, whether this disrupted structure was detected at autopsy or more recently by CT and MRI. This led to the common dictum that neurology was learned “stroke by stroke” (lesion-symptom mapping). In the last 5 years, higher-resolution MRI scanners (3T and 7T machines) and innovative scanning protocols and analytic methods have exponentially expanded our ability to “see” subtle details of brain structure in living persons.1 In parallel, genetic studies have shown that mildly damaging genetic variants located within genes associated with severe monogenic disorders (“the diagnostic zebras”) may explain a larger proportion of common disease (“the horses”) than had been previously suspected. One example is NOTCH3, the gene underlying cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), variants within which are associated with greater white matter lesion load in healthy adults in the community.2 Vascular cognitive impairment (VCI) is a distressingly common condition that remains difficult to precisely diagnose and define, partly because of poor lesion– symptom correlation. Conventional MRI markers of small vessel disease (SVD), white matter hyperintensities/lesions and lacunar infarcts, are the most common structural surrogates of VCI in population samples, but the correlation is far from perfect, with a wide range of cognitive function observed in persons with apparently identical burdens of white matter lesions.3 Thus, the question looms: can parallels be drawn between common and rare types of VCI and can the use of novel image analysis tools improve our understanding of VCI?
In this issue of Neurology®, Duering et al.4 examined whether a previously noted association in patients with CADASIL, of white matter injury within frontalsubcortical circuits with lower processing speed,5 was replicable in a community-based sample of older adults. They analyzed brain MRI data on 584 dementia- and stroke-free participants in the Austrian Stroke Prevention Study using 2 novel image analysis techniques, voxel-based lesion-symptom mapping (determining which voxels were most likely to have white matter lesions in persons with poorer cognition), and Bayesian network analysis of lesion volumes within major white matter tracts (determining which tracts were most likely to have white matter lesions in these persons). They observed that deficits in processing speed, measured by performance on the Trail Making Test B and reaction time tasks, were related to SVD in 2 specific areas, the frontal interhemispheric (forceps minor) and (anterior) thalamic projection fiber tracts, but not to the total volume of white matter lesions. What are the implications of this study? It partly explains the poor correlation observed in prior structural– functional (lesion–symptom) studies of SVD as a consequence of an inadequate resolution of images. It also suggests that extrapolating from observations in CADASIL and other monogenic variants of SVD can provide novel insights into sporadic VCI. However, whereas this study emphasizes the importance of specific frontal–subcortical circuits in determining processing speed, it does not resolve whether this association is due to primary white matter microstructural injury, injury to the adjacent cortex, or disturbance of functional connectivity networks. Further, variation in the integrity of these tracts explained only 1.8% of the variance in processing speed observed. Brain parenchymal volume did not predict processing speed, but studying other aspects of brain structure, such as MRI infarcts, fractional anisotropy on diffusion tensor imaging (which detects microstructural white matter injury), and amyloid burden (extent of concomitant degenerative pathology), might have increased the proportion of variance
See page 1946 From the Department of Neurology at Boston University School of Medicine (S.S.); the Framingham Heart Study (S.S.), Framingham, MA; and the Department of Neurology (F.-E.d.L.), Donders Institute of Brain Behaviour & Cognition, Center for Neuroscience, Radboud University Medical Center Nijmegen, the Netherlands. Go to Neurology.org for full disclosures. Funding information and disclosures deemed relevant by the authors, if any, are provided at the end of the editorial. 1940
© 2014 American Academy of Neurology
explained.6 In addition, hypertension and diabetes had effects on processing speed independent of their deleterious effects on the studied fiber tracts, and various demographic (age, sex, education) and lifestyle factors (sleep, physical activity, smoking, diet) can likely also affect processing speed through pathways that might not alter brain structure on MRI. Some strengths of this study are the large populationbased sample; the congruent findings from the 2 different methods used, which increases our confidence in the findings; and the use of 1.5T and 3T MRI scans, comparable in quality to those routinely obtained in clinical settings. One limitation was that the observed association was largely restricted to performance on a single cognitive test, the Trail Making Test B, and was not seen with 2 other tests of executive function examined; hence, the impact of injuries in these 2 locations on the performance of daily activities remains to be studied. Another limitation is the cross-sectional study design. However, longitudinal studies on community-dwelling adults that explore the clinical consequences of SVD by combining novel imaging techniques such as diffusion tensor imaging and fMRI with repeated clinical assessments are currently under way,7 and these studies, in conjunction with the adoption of more uniform descriptions of SVD on imaging,8 have the potential to greatly expand our understanding of VCI. AUTHOR CONTRIBUTIONS Sudha Seshadri: drafting/revising the manuscript, study concept or design. Frank-Erik de Leeuw: drafting/revising the manuscript.
STUDY FUNDING Supported by grants from the National Institute on Aging (R01 AG08122), the National Institute of Neurological Disorders and Stroke
(R01 NS17950), and a VIDI innovational grant from Dutch Organization for Scientific Research (grant 016.126.351).
DISCLOSURE The authors report no disclosures relevant to the manuscript. Go to Neurology.org for full disclosures.
REFERENCES 1. Nielsen AS, Kinkel RP, Madigan N, Tinelli E, Benner T, Mainero C. Contribution of cortical lesion subtypes at 7T MRI to physical and cognitive performance in MS. Neurology 2013;81:641–649. 2. Schmidt H, Zeginigg M, Wiltgen M, et al. Genetic variants of the NOTCH3 gene in the elderly and magnetic resonance imaging correlates of age-related cerebral small vessel disease. Brain 2011;134:3384–3397. 3. Debette S, Markus HS. The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis. BMJ 2010; 341:c3666. 4. Duering M, Gesierich B, Seiler S, et al. Strategic white matter tracts for processing speed deficits in age-related small vessel disease. Neurology 2014;82:1946–1950. 5. Duering M, Zieren N, Herve D, et al. Strategic role of frontal white matter tracts in vascular cognitive impairment: a voxel-based lesion-symptom mapping study in CADASIL. Brain 2011;134:2366–2375. 6. Viswanathan A, Godin O, Jouvent E, et al. Impact of MRI markers in subcortical vascular dementia: a multi-modal analysis in CADASIL. Neurobiol Aging 2010;31:1629–1636. 7. van der Holst HM, Tuladhar AM, van Norden AG, et al. Microstructural integrity of the cingulum is related to verbal memory performance in elderly with cerebral small vessel disease: the RUN DMC study. Neuroimage 2013; 65:416–423. 8. Wardlaw JM, Smith EE, Biessels GJ, et al. Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration. Lancet Neurol 2013;12:822–838.
Neurology 82
June 3, 2014
1941
Understanding brain function through small vessel disease: What zebras can teach us about horses Sudha Seshadri and Frank-Erik de Leeuw Neurology 2014;82;1940-1941 Published Online before print May 2, 2014 DOI 10.1212/WNL.0000000000000484 This information is current as of May 2, 2014 Updated Information & Services
including high resolution figures, can be found at: http://www.neurology.org/content/82/22/1940.full.html
References
This article cites 8 articles, 5 of which you can access for free at: http://www.neurology.org/content/82/22/1940.full.html##ref-list1
Subspecialty Collections
This article, along with others on similar topics, appears in the following collection(s): All Cerebrovascular disease/Stroke http://www.neurology.org//cgi/collection/all_cerebrovascular_dis ease_stroke All epidemiology http://www.neurology.org//cgi/collection/all_epidemiology Executive function http://www.neurology.org//cgi/collection/executive_function MRI http://www.neurology.org//cgi/collection/mri Vascular dementia http://www.neurology.org//cgi/collection/vascular_dementia
Permissions & Licensing
Information about reproducing this article in parts (figures,tables) or in its entirety can be found online at: http://www.neurology.org/misc/about.xhtml#permissions
Reprints
Information about ordering reprints can be found online: http://www.neurology.org/misc/addir.xhtml#reprintsus
