Movement Disorders (revue)

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A Tale of Two Factors: What determines rate of progression in Huntington Disease? A Longitudinal MRI study

Identifieur interne : 000290 ( Pmc/Checkpoint ); précédent : 000289; suivant : 000291

A Tale of Two Factors: What determines rate of progression in Huntington Disease? A Longitudinal MRI study

Auteurs : H. Diana Rosas ; Martin Reuter [États-Unis] ; Gheorghe Doros [États-Unis] ; Stephanie Y. Lee ; Tyler Triggs ; Keith Malarick ; Bruce Fischl [États-Unis] ; David H. Salat ; Steven M. Hersch

Source :

RBID : PMC:3155608

Abstract

Background

Over the past several years, increased attention has been devoted to understanding regionally selective brain changes that occur in Huntington’s disease and their relationships to phenotypic variability. Clinical progression is also heterogeneous, and while the CAG repeat length influences age of onset, its role, if any, in progression has been less clear. We evaluated progression in HD using a novel longitudinal MRI analysis; our hypothesis was that the rate of brain atrophy is influenced by the age of onset of HD.

Methods

We scanned 22 patients with HD at approximately one-year intervals; individuals were divided into one of three groups, determined by the relative age of onset.

Results

We found significant differences in the rates of atrophy of cortex, white matter and subcortical structures; patients who developed symptoms earlier demonstrated the most rapid rates of atrophy as compared to those who developed symptoms during middle-age or more advanced age. Rates of cortical atrophy were topologically variable, with the most rapid changes occurring in sensori-motor, posterior frontal and portions of parietal cortex. There were no significant differences in the rates of atrophy in basal ganglia structures. While both CAG repeat length and age influenced the rate of change in some regions, there was no significant correlation in many regions.

Conclusion

Rates of regional brain atrophy are influenced the age of onset of HD symptoms and are only partially explained by the CAG repeat length. These findings suggest that other genetic, epigenetic and environmental factors play important roles in neurodegeneration in HD.


Url:
DOI: 10.1002/mds.23762
PubMed: 21611979
PubMed Central: 3155608


Affiliations:


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Le document en format XML

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<title>Background</title>
<p id="P1">Over the past several years, increased attention has been devoted to understanding regionally selective brain changes that occur in Huntington’s disease and their relationships to phenotypic variability. Clinical progression is also heterogeneous, and while the CAG repeat length influences age of onset, its role, if any, in progression has been less clear. We evaluated progression in HD using a novel longitudinal MRI analysis; our hypothesis was that the rate of brain atrophy is influenced by the age of onset of HD.</p>
</sec>
<sec sec-type="methods" id="S2">
<title>Methods</title>
<p id="P2">We scanned 22 patients with HD at approximately one-year intervals; individuals were divided into one of three groups, determined by the relative age of onset.</p>
</sec>
<sec id="S3">
<title>Results</title>
<p id="P3">We found significant differences in the rates of atrophy of cortex, white matter and subcortical structures; patients who developed symptoms earlier demonstrated the most rapid rates of atrophy as compared to those who developed symptoms during middle-age or more advanced age. Rates of cortical atrophy were topologically variable, with the most rapid changes occurring in sensori-motor, posterior frontal and portions of parietal cortex. There were no significant differences in the rates of atrophy in basal ganglia structures. While both CAG repeat length and age influenced the rate of change in some regions, there was no significant correlation in many regions.</p>
</sec>
<sec id="S4">
<title>Conclusion</title>
<p id="P4">Rates of regional brain atrophy are influenced the age of onset of HD symptoms and are only partially explained by the CAG repeat length. These findings suggest that other genetic, epigenetic and environmental factors play important roles in neurodegeneration in HD.</p>
</sec>
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<name>
<surname>Rosas</surname>
<given-names>H. Diana</given-names>
</name>
<degrees>MD</degrees>
<xref ref-type="aff" rid="A1">1</xref>
<xref ref-type="aff" rid="A2">2</xref>
<xref ref-type="aff" rid="A3">3</xref>
<xref ref-type="aff" rid="A4">4</xref>
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<given-names>Martin</given-names>
</name>
<degrees>PhD</degrees>
<xref ref-type="aff" rid="A1">1</xref>
<xref ref-type="aff" rid="A2">2</xref>
<xref ref-type="aff" rid="A4">4</xref>
<xref ref-type="aff" rid="A5">5</xref>
<xref ref-type="aff" rid="A6">6</xref>
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<surname>Doros</surname>
<given-names>Gheorghe</given-names>
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<degrees>PhD</degrees>
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<name>
<surname>Lee</surname>
<given-names>Stephanie Y.</given-names>
</name>
<degrees>BS</degrees>
<xref ref-type="aff" rid="A1">1</xref>
<xref ref-type="aff" rid="A2">2</xref>
<xref ref-type="aff" rid="A3">3</xref>
<xref ref-type="aff" rid="A4">4</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Triggs</surname>
<given-names>Tyler</given-names>
</name>
<degrees>BS</degrees>
<xref ref-type="aff" rid="A1">1</xref>
<xref ref-type="aff" rid="A2">2</xref>
<xref ref-type="aff" rid="A3">3</xref>
<xref ref-type="aff" rid="A4">4</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Malarick</surname>
<given-names>Keith</given-names>
</name>
<degrees>BS</degrees>
<xref ref-type="aff" rid="A1">1</xref>
<xref ref-type="aff" rid="A2">2</xref>
<xref ref-type="aff" rid="A3">3</xref>
<xref ref-type="aff" rid="A4">4</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Fischl</surname>
<given-names>Bruce</given-names>
</name>
<degrees>PhD</degrees>
<xref ref-type="aff" rid="A4">4</xref>
<xref ref-type="aff" rid="A5">5</xref>
<xref ref-type="aff" rid="A6">6</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Salat</surname>
<given-names>David H.</given-names>
</name>
<degrees>PhD</degrees>
<xref ref-type="aff" rid="A2">2</xref>
<xref ref-type="aff" rid="A4">4</xref>
<xref ref-type="aff" rid="A5">5</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Hersch</surname>
<given-names>Steven M.</given-names>
</name>
<degrees>MD PhD</degrees>
<xref ref-type="aff" rid="A1">1</xref>
<xref ref-type="aff" rid="A3">3</xref>
</contrib>
</contrib-group>
<aff id="A1">
<label>1</label>
Department of Neurology, Massachusetts General Hospital and Harvard Medical School</aff>
<aff id="A2">
<label>2</label>
Center for Neuro-imaging of Aging and Neurodegenerative Diseases, Massachusetts General Hospital and Harvard Medical School</aff>
<aff id="A3">
<label>3</label>
MassGeneral Institute for Neurodegeneration, Massachusetts General Hospital and Harvard Medical School</aff>
<aff id="A4">
<label>4</label>
Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School</aff>
<aff id="A5">
<label>5</label>
Department of Radiology, Massachusetts General Hospital and Harvard Medical School</aff>
<aff id="A6">
<label>6</label>
MIT Computer Science and AI Lab, Division of Health Sciences and Technology, Cambridge, MA</aff>
<aff id="A7">
<label>7</label>
Department of Biostatistics, Boston University, Boston, MA</aff>
<author-notes>
<corresp id="cor1">
<bold>Address correspondence and reprint requests to:</bold>
H. Diana Rosas, M.D., Center for Neuro-imaging of Aging and Neurodegenerative Diseases, Massachusetts General Hospital 149 13th Street, Room 2275, Charlestown, MA 02129,
<email>rosas@helix.mgh.harvard.edu</email>
</corresp>
</author-notes>
<pub-date pub-type="nihms-submitted">
<day>30</day>
<month>3</month>
<year>2011</year>
</pub-date>
<pub-date pub-type="epub">
<day>24</day>
<month>5</month>
<year>2011</year>
</pub-date>
<pub-date pub-type="ppub">
<day>1</day>
<month>8</month>
<year>2011</year>
</pub-date>
<pub-date pub-type="pmc-release">
<day>1</day>
<month>8</month>
<year>2012</year>
</pub-date>
<volume>26</volume>
<issue>9</issue>
<fpage>1691</fpage>
<lpage>1697</lpage>
<abstract>
<sec id="S1">
<title>Background</title>
<p id="P1">Over the past several years, increased attention has been devoted to understanding regionally selective brain changes that occur in Huntington’s disease and their relationships to phenotypic variability. Clinical progression is also heterogeneous, and while the CAG repeat length influences age of onset, its role, if any, in progression has been less clear. We evaluated progression in HD using a novel longitudinal MRI analysis; our hypothesis was that the rate of brain atrophy is influenced by the age of onset of HD.</p>
</sec>
<sec sec-type="methods" id="S2">
<title>Methods</title>
<p id="P2">We scanned 22 patients with HD at approximately one-year intervals; individuals were divided into one of three groups, determined by the relative age of onset.</p>
</sec>
<sec id="S3">
<title>Results</title>
<p id="P3">We found significant differences in the rates of atrophy of cortex, white matter and subcortical structures; patients who developed symptoms earlier demonstrated the most rapid rates of atrophy as compared to those who developed symptoms during middle-age or more advanced age. Rates of cortical atrophy were topologically variable, with the most rapid changes occurring in sensori-motor, posterior frontal and portions of parietal cortex. There were no significant differences in the rates of atrophy in basal ganglia structures. While both CAG repeat length and age influenced the rate of change in some regions, there was no significant correlation in many regions.</p>
</sec>
<sec id="S4">
<title>Conclusion</title>
<p id="P4">Rates of regional brain atrophy are influenced the age of onset of HD symptoms and are only partially explained by the CAG repeat length. These findings suggest that other genetic, epigenetic and environmental factors play important roles in neurodegeneration in HD.</p>
</sec>
</abstract>
<kwd-group>
<kwd>MRI longitudinal atrophy</kwd>
<kwd>Phenotypic variability</kwd>
<kwd>Huntington’s disease</kwd>
<kwd>neurodegeneration</kwd>
<kwd>longitudinal MRI</kwd>
</kwd-group>
<funding-group>
<award-group>
<funding-source country="United States">National Center for Research Resources : NCRR</funding-source>
<award-id>U24 RR021382-01 || RR</award-id>
</award-group>
<award-group>
<funding-source country="United States">National Institute of Neurological Disorders and Stroke : NINDS</funding-source>
<award-id>R21 NS072652-01 || NS</award-id>
</award-group>
<award-group>
<funding-source country="United States">National Institute of Neurological Disorders and Stroke : NINDS</funding-source>
<award-id>R01 NS052585-01A1 || NS</award-id>
</award-group>
<award-group>
<funding-source country="United States">National Institute of Neurological Disorders and Stroke : NINDS</funding-source>
<award-id>R01 NS042861-01A2 || NS</award-id>
</award-group>
<award-group>
<funding-source country="United States">National Institute of Nursing Research : NINR</funding-source>
<award-id>R01 NR010827-01A1 || NR</award-id>
</award-group>
<award-group>
<funding-source country="United States">National Institute of Biomedical Imaging and Bioengineering : NIBIB</funding-source>
<award-id>R01 EB006758-01A1 || EB</award-id>
</award-group>
<award-group>
<funding-source country="United States">National Center for Research Resources : NCRR</funding-source>
<award-id>P41 RR014075-01A1 || RR</award-id>
</award-group>
<award-group>
<funding-source country="United States">National Institute of Neurological Disorders and Stroke : NINDS</funding-source>
<award-id>P01 NS058793-01A1 || NS</award-id>
</award-group>
</funding-group>
</article-meta>
</front>
</pmc>
<affiliations>
<list>
<country>
<li>États-Unis</li>
</country>
<region>
<li>Massachusetts</li>
</region>
</list>
<tree>
<noCountry>
<name sortKey="Hersch, Steven M" sort="Hersch, Steven M" uniqKey="Hersch S" first="Steven M." last="Hersch">Steven M. Hersch</name>
<name sortKey="Lee, Stephanie Y" sort="Lee, Stephanie Y" uniqKey="Lee S" first="Stephanie Y." last="Lee">Stephanie Y. Lee</name>
<name sortKey="Malarick, Keith" sort="Malarick, Keith" uniqKey="Malarick K" first="Keith" last="Malarick">Keith Malarick</name>
<name sortKey="Rosas, H Diana" sort="Rosas, H Diana" uniqKey="Rosas H" first="H. Diana" last="Rosas">H. Diana Rosas</name>
<name sortKey="Salat, David H" sort="Salat, David H" uniqKey="Salat D" first="David H." last="Salat">David H. Salat</name>
<name sortKey="Triggs, Tyler" sort="Triggs, Tyler" uniqKey="Triggs T" first="Tyler" last="Triggs">Tyler Triggs</name>
</noCountry>
<country name="États-Unis">
<region name="Massachusetts">
<name sortKey="Reuter, Martin" sort="Reuter, Martin" uniqKey="Reuter M" first="Martin" last="Reuter">Martin Reuter</name>
</region>
<name sortKey="Doros, Gheorghe" sort="Doros, Gheorghe" uniqKey="Doros G" first="Gheorghe" last="Doros">Gheorghe Doros</name>
<name sortKey="Fischl, Bruce" sort="Fischl, Bruce" uniqKey="Fischl B" first="Bruce" last="Fischl">Bruce Fischl</name>
</country>
</tree>
</affiliations>
</record>

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