a longitudinal study of brain development in autism
DESCRIPTION
A longitudinal study of brain development in autism. Heather Cody Hazlett, PhD Neurodevelopmental Disorders Research Center & UNC-CH Dept of Psychiatry NA-MIC AHM Salt Lake City, UTJan 11, 2007. Overview. Summary of structural imaging studies of autism - PowerPoint PPT PresentationTRANSCRIPT
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A longitudinal study of A longitudinal study of brain development brain development
in autismin autism
Heather Cody Hazlett, PhDHeather Cody Hazlett, PhD
Neurodevelopmental Disorders Research CenterNeurodevelopmental Disorders Research Center& UNC-CH Dept of Psychiatry& UNC-CH Dept of Psychiatry
NA-MIC AHM Salt Lake City, UTNA-MIC AHM Salt Lake City, UT Jan 11, 2007Jan 11, 2007
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OverviewOverview
Summary of structural imaging studies of Summary of structural imaging studies of autismautism
Findings from our longitudinal autism Findings from our longitudinal autism studystudy
Challenges & benefits to imaging across Challenges & benefits to imaging across developmentdevelopment
Future projects & goals for NA-MICFuture projects & goals for NA-MIC
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Structural Imaging in AutismStructural Imaging in Autism
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MRI Studies of Brain Volume in AutismMRI Studies of Brain Volume in Autism
StudyStudy Brain FindingBrain Finding Subject AgeSubject Age
Piven et al. (1992) Piven et al. (1992) mid-sagittal area mid-sagittal area 18 - 53 yrs 18 - 53 yrs
Piven et al (1995) Piven et al (1995) total brain volumetotal brain volume 14 – 29 yrs14 – 29 yrs
Courchesne et al (2001)Courchesne et al (2001) cerebral. gray and whitecerebral. gray and white 2 – 4 yrs only2 – 4 yrs only
Sparks et al (2002)Sparks et al (2002) total cerebral total cerebral 3 - 4 yrs3 - 4 yrs
Aylward et al (2002)Aylward et al (2002) TBV (HFA) TBV (HFA) under 12 yrsunder 12 yrs
Lotspeich et al (2004)Lotspeich et al (2004) cerebral gray (N=52) cerebral gray (N=52) 7 – 18 yr7 – 18 yr
Herbert et al (2004)Herbert et al (2004) cerebral whitecerebral white 5 – 11 yrs5 – 11 yrs
Hazlett at al (2005)Hazlett at al (2005) gray matter volumegray matter volume 14 - 29 yrs14 - 29 yrs
Palmen et al (2005)Palmen et al (2005) TBV, cerebral gray (N=21)TBV, cerebral gray (N=21) 7 – 15 yrs7 – 15 yrs
Limitations: no developmental studies, heterogeneity of samples
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When compared to typically When compared to typically developing individuals….developing individuals….
increased brain weight in autismincreased brain weight in autismmacrocephaly in 20%macrocephaly in 20%increased brain volume on MRIincreased brain volume on MRIenlarged tissue volumes (both WM & GM)enlarged tissue volumes (both WM & GM)age effects presentage effects present
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Longitudinal MRI study of brain Longitudinal MRI study of brain development in autismdevelopment in autism
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Longitudinal MRI study of brain Longitudinal MRI study of brain development in autismdevelopment in autism
AIMS
• To characterize patterns of brain development longitudinally in autism cases versus controls (TYP, DD)
• To examine cross-sectional & longitudinal relationships between selected brain regions and behavioral characteristics associated with autism
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NN % male years (SD)% male years (SD) IQ-SS (SD) IQ-SS (SD)**
AutismAutism 5151 88% 88% 2.7 (0.3)2.7 (0.3) 54.2 (9.4) 54.2 (9.4)
ControlsControls 2525
DDDD 1111 55% 55% 2.7 (0.4)2.7 (0.4) 59.7 (9.4) 59.7 (9.4)
TYPTYP 1414 64% 64% 2.4 (0.4) 2.4 (0.4) 107.5 (18.7) 107.5 (18.7)
* IQ-SS = Mullen composite Standard Score* IQ-SS = Mullen composite Standard Score
UNC Longitudinal MRI Study of AutismUNC Longitudinal MRI Study of Autism
Hazlett et al Arch Gen Psych 2005
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UNC Longitudinal MRI Study of AutismUNC Longitudinal MRI Study of Autism
autismautism controls controls
mean (SE)mean (SE) mean (SE)mean (SE) % diff % diff p p
TBV TBV 1264.6 (13.4) 1208.1 (16.2) 4.7 0.008 1264.6 (13.4) 1208.1 (16.2) 4.7 0.008
cerebrumcerebrum 941.5 (10.5) 890.5 (12.3) 5.7 941.5 (10.5) 890.5 (12.3) 5.7 0.0020.002
cerebellum cerebellum 114.1 (1.5)114.1 (1.5) 114.4 (2.2)114.4 (2.2) 0.3 0.3 0.9 0.9
Adjusted for Gender and AgeAdjusted for Gender and Age
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autismautism controls controls
mean (SE)mean (SE) mean (SE)mean (SE) % diff % diff p p
TBV TBV 1264.6 (13.4) 1208.1 (16.2) 4.7 1264.6 (13.4) 1208.1 (16.2) 4.7 0.008 0.008
cerebrumcerebrum 941.5 (10.5) 890.5 (12.3) 5.7 0.002941.5 (10.5) 890.5 (12.3) 5.7 0.002
graygray 676.7 (7.7) 676.7 (7.7) 644.2 (8.8)644.2 (8.8) 5.0 5.0 0.005 0.005
whitewhite 264.7 (3.1)264.7 (3.1) 246.2 (3.7)246.2 (3.7) 7.5 7.5 0.0001 0.0001
cerebellum 114.1 (1.5) 114.4 (2.2)cerebellum 114.1 (1.5) 114.4 (2.2) 0.3 0.3 0.9 0.9
UNC Longitudinal MRI Study of AutismUNC Longitudinal MRI Study of Autism
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% increase Autism vs. Combined Controls
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
7.0%
8.0%
9.0%
10.0%
% i
nc
reas
e
Parietal-Occipital Lobe Temporal Lobe Frontal Lobe
Gray Tissue
White Tissue
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autismautism typical typical mean (SE)mean (SE) mean (SE)mean (SE) % diff% diff p p
cerebrumcerebrum 941.5 (10.5) 941.5 (10.5) 903.1 (17.4)903.1 (17.4) 4.2 4.2 0.06 0.06
graygray 676.7 (7.7)676.7 (7.7) 652.7 (12.2)652.7 (12.2) 3.7 0.1 3.7 0.1
whitewhite 264.7 (3.1) 264.7 (3.1) 250.4 (5.4)250.4 (5.4) 5.7 5.7 0.02 0.02
autismautism dev delayeddev delayed
mean (SE)mean (SE) mean (SE)mean (SE) % diff p% diff p
cerebrumcerebrum 941.5 (10.5) 941.5 (10.5) 874.4 (17.2)874.4 (17.2) 7.7 7.7 0.0008 0.0008
graygray 676.7 (7.7)676.7 (7.7) 633.5 (12.4)633.5 (12.4) 6.8 6.8 0.003 0.003
whitewhite 264.7 (3.1) 264.7 (3.1) 240.9 (5.1)240.9 (5.1) 9.9 9.9 0.0001 0.0001
UNC Longitudinal MRI Study of AutismUNC Longitudinal MRI Study of Autism
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Substructures of interestSubstructures of interest
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Relationship between Brain Relationship between Brain Volume and Autistic FeaturesVolume and Autistic Features
Social Communication
AtypicalBehaviors
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Substructures of interestSubstructures of interest
Basal gangliaBasal ganglia– CaudateCaudate– PutamenPutamen– Globus Globus
palliduspallidus
AmygdalaAmygdala
HippocampusHippocampus
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Caudate Enlargement in AutismCaudate Enlargement in Autism
ageage t t p pStudy 1Study 1autismautism 3535 12-2912-29 2.452.45 .01.01controlscontrols3636 12-2912-29
Study 2Study 2autismautism 1515 m = 27.7m = 27.7 3.193.19 .003.003controlscontrols1515 m = 30.3m = 30.3
(Sears, Vest, Bailey, Ransom, Piven (Sears, Vest, Bailey, Ransom, Piven
1999)1999)
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Clinical Correlates of Caudate VolumeClinical Correlates of Caudate Volume
ADI DomainADI Domain Spearman r Spearman r pp
socialsocial 0.19 0.19 ns ns
communicationcommunication 0.05 0.05 ns ns
ritualistic/repetitiveritualistic/repetitive -0.36 -0.36 0.020.02
(Sears, Vest, Bailey, Ransom, Piven 1999)(Sears, Vest, Bailey, Ransom, Piven 1999)
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Hollander et al. Biological Psychiatry 2005
Clinical Correlates of Caudate VolumeClinical Correlates of Caudate Volume
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DescriptivesDescriptives
%% YearsYears Cognitive* Cognitive* Adaptive**Adaptive**GroupGroup NN MaleMale M (SD)M (SD) M (SD) M (SD) M (SD)M (SD)
autismautism 5252 87%87% 2.7 (0.3)2.7 (0.3) 54.1 (9.3) 54.1 (9.3) 60.8 (5.9)60.8 (5.9)
controlscontrols 3333 70%70% 2.6 (0.5)2.6 (0.5) 87.4 (28.6) 87.4 (28.6) 850.4 (21.1)850.4 (21.1)
developmental delaydevelopmental delay 1212 67%67% 2.8 (0.4)2.8 (0.4) 55.5 (6.7) 55.5 (6.7) 65.8 (14.0)65.8 (14.0) typically developingtypically developing 2121 71%71% 2.4 (0.5)2.4 (0.5) 106.6 (16.8) 106.6 (16.8) 98.3 (13.4)98.3 (13.4)
* Cognitive estimate from Mullen Composite Standard Score* Cognitive estimate from Mullen Composite Standard Score** Adaptive behavior estimate from Vineland Adaptive Behavior Composite** Adaptive behavior estimate from Vineland Adaptive Behavior Composite
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Basal Ganglia Volumes in 2 Year Olds with AutismBasal Ganglia Volumes in 2 Year Olds with Autism(adjusted for TBV)(adjusted for TBV)
Aut v Total Controls Aut v TYP Aut v DD
diff (SE) p % diff (SE) p % diff (SE) p %
Caudate
.50 (.29) .094 7% 0.8 (.31) .013 12% .20 (.43) .65 3%
Globus Pallidus
.16 (.29) .09 6% .17 (.10) .094 6% .16 (.12) .20 6%
Putamen
-.16 (.20) .410 - 2% -.19 (.22) .380 -2% -.14 (.25) .594 -2%
Note - all comparisons also adjusted for age and gender
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Clinical Correlates of Basal Ganglia Volume in 2 year olds Clinical Correlates of Basal Ganglia Volume in 2 year olds with Autismwith Autism
Caudate Globus Pallidus Putamen
B (SE) p* B (SE) p B (SE) p
ADI Item
Minor Change -.35 (.230) .034 -.115 (.071) .055 -.439 (.135) .001
Rituals - - -
Body Mvt .413 (.150) .004 .126 (.049) .007 .140 .140 .163
* one-sided t-test
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MRI Studies of Amygdala Volume in AutismMRI Studies of Amygdala Volume in Autism
Sparks (2002)Sparks (2002) 45 ASD45 ASD incinc vs. TYP and DD controls vs. TYP and DD controls
(3-4 yr olds)(3-4 yr olds)
Schumann (2004)Schumann (2004) 61 ASD61 ASD increased in 7-12 year olds, increased in 7-12 year olds,
not increased 12-17 year oldsnot increased 12-17 year olds
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Amygdala/Hippocampus Amygdala/Hippocampus Volume in 2 Year Olds with AutismVolume in 2 Year Olds with Autism
Aut v Total Controls Aut v TYP Aut v DD
diff (SE) p % diff (SE) p % diff (SE) p %
amygdala
.35 (.12) .004 10% .55 (.11) <.001 16% .16 (.17) .336 3%
hippocampus
.03 (.11) .78 1% -.03 (.14) .841 0% .09 (.15) .55 2%
*Note – all comparisons also adjusted for age and gender
(adjusted for TBV)(adjusted for TBV)
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FXS-autism vs autism-nonFXSFXS-autism vs autism-nonFXS
Volume Differences
-15%
-10%
-5%
0%
5%
10%
15%
20%
25%
30%
35%
40%
Caudate Amygdala
% d
iffe
ren
ce
All FX vs Controls
Aut FX vs Controls
Aut vs Controls
***
******
***
*
* p<.05** p<.01*** p <.001
FXS (N=35); Controls (N=38); FXS + autism (N=12); Autism - nonFXS (44)
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Imaging DevelopmentImaging Development
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Challenges to Developmental Challenges to Developmental StudiesStudies
Difficult for very young children and/or Difficult for very young children and/or lower functioning children to remain stilllower functioning children to remain still
May need to remain motionless for long May need to remain motionless for long periods of timeperiods of time
Sleep studies vary in success ratesSleep studies vary in success rates
Subjects may require training and practice Subjects may require training and practice – this adds to expense– this adds to expense
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total cerebral To total cerebral white matter
frontal gray parietal gray
temporal gray occipital gray
Longitudinal Studies:
Brain Development During Childhood and Adolescence
Age in years
Peak 12 y12 yrs 12 yrs
16 yrs20 yrs
4
more sensitive for detecting growth patterns, even in the presence of large inter-individual variation and non-linear growth
Longitudinal Methods
time 1 time 2
Giedd et al., Nature Neuroscience, 1999
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Gray matter maturationGray matter maturation
Gogtay, Giedd et al PNAS 2004. N = 13 (7 male, 6 female) typical subjects
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Time Course of Critical Events in the Time Course of Critical Events in the Determination of Human Brain MorphometryDetermination of Human Brain Morphometry
Pu
ber
ty
Bir
th
18 years1 year20 weeks
Rel
ativ
e V
olu
me/
Den
sity
10 years
Neurogenesis
Synaptogenesis
Dendritic and Axonal Development/Remodeling
Myelination
Synaptic Elimination
Synapses
White MatterWhite Matter
Gray Matter
Migration
Neurodevelopmental processes, cortical synapse density, and their relationship to gray and white matter volumes on MRI. Giedd et al. 1999, Sowell et al. 1999.
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Neonatal Brain MRINeonatal Brain MRI
T2T2T1T1
non-myelinated
white matter
early myelinated white matter
gray matter
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Corpus CallosumCorpus Callosum
Neonate (2 wks) Adult
Corpus callosum: FA along Commissural bundles
Infant (1 year)
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Infancy to ChildhoodInfancy to Childhood
Hermove et al., NeuroImage 2005.
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Data Data
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Data Data
Structural MRI Structural MRI
Diffusion TensorDiffusion Tensor
Behavioral, cognitive, developmentalBehavioral, cognitive, developmental
Processed longitudinal dataProcessed longitudinal data
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Data Data
Structural MRIStructural MRI
TI:TI: coronal 3D SPGR IRprep, 0.78 x 0.78 x 1.5 mm, coronal 3D SPGR IRprep, 0.78 x 0.78 x 1.5 mm, 124 124 slices, 5 TE/12 TR, 20 FOV, 1 NEX, 256x192slices, 5 TE/12 TR, 20 FOV, 1 NEX, 256x192
PD/T2: coronal FSE, 0.78 x 0.78 x 3.0 mm, 128 slices, PD/T2: coronal FSE, 0.78 x 0.78 x 3.0 mm, 128 slices, 20 FOV, 17 TE/7200 TR, 1 NEX, 256x16020 FOV, 17 TE/7200 TR, 1 NEX, 256x160
DTI DTI
axial oblique 2D spin echo EPI, 0.93 x 0.97 x 3.8 axial oblique 2D spin echo EPI, 0.93 x 0.97 x 3.8 mm, 30 slices, 24 FOV, 12 dirmm, 30 slices, 24 FOV, 12 dir
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Data Data
Processed datasets* Processed datasets*
Time1 (2 yr old) Time2 (4 yr old)EMS/lobes CN AMYG EMS/lobes CN AMYG
Autism 49 51 47 29 31 31 (+2 CS)DD 12 9 10 6 5 6Typical 25 22 21 11 12 10FX 45 47 47 11 11 10
*As of Nov06
Also have segmented data for:
Put/GP, Hipp, CC area, Ventricles, Ant Cing
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Image ProcessingImage Processing
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Tissue segmentation –2 yr oldTissue segmentation –2 yr old
EMS hard segmentations
EMS segmentations overlaid on MRI
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Automatic parcellation by template warpingAutomatic parcellation by template warping
Manually-derived parcellation “warped” to new subjects
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Challenges to Image ProcessingChallenges to Image Processing
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Registration of images to a common atlasRegistration of images to a common atlas
Inhomogeneities – bias correctionInhomogeneities – bias correction
Tissue contrast – myelinationTissue contrast – myelination
Brain shape changes across developmentBrain shape changes across development
Challenges to Image ProcessingChallenges to Image Processing
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Future DirectionsFuture Directions
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Future DirectionsFuture Directions
Examination of longitudinal data
e.g., 2-4 years old, follow-ups at 6-8
Development & application of novel image processing methods
e.g., shape, cortical thickness
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Change from 2 to 4 yearsChange from 2 to 4 years
These frames show the evolution from 2 year old to 4 year old using high dimensional fluid warping (Joshi)
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Surface growth maps Surface growth maps
age 2 4
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NA-MIC CollaborationNA-MIC CollaborationGoals/Projects for NAMIC collaborators:
1) Pipelines for growth-rate analysis
2) Longitudinal analysis of cortical thickness, cortical folding patterns, etc.
3) Automating DTI processing, creating more regionally defined DTI analysis (?)
4) Development of new segmentation protocols (e.g., dorsolateral prefrontal cortex)
5) Quantify shape changes over time to allow for analysis with behavioral data
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NA-MIC CollaborationNA-MIC Collaboration
Our site can offer NAMIC collaborators:
1) Pediatric dataset of sMRI & DTI
2) Longitudinal data
3) Segmented datasets (e.g., substructures, ROIs) to be used as validation tools
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ContributorsContributorsJoe Piven, MDGuido Gerig, PhD
Sarang Joshi, PhDMichele Poe, PhD Chad Chappell, MAJudy Morrow, PhDNancy Garrett, BS, OTA
Robin Morris, BARachel Smith, BAMike Graves, MChESarah Peterson, BAMatthieu Jomier, MSCarissa Cascio, PhDMatt Mosconi, PhDMatt Mosconi, PhD
Martin Styner, PhDAllison Ross, MD James MacFall, PhD
Alan Song, PhDValerie Jewells, MD James Provenzale, MD Greg McCarthy, Ph.D.John Gilmore, MDAllen Reiss, MD
UNC Fragile X CenterNDRC Research Registry
Funded by the National Institutes of Health
Many thanks to the families that have generously participated !