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

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

Structural Imaging in AutismStructural Imaging in Autism

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

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

Longitudinal MRI study of brain Longitudinal MRI study of brain development in autismdevelopment in autism

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

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

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

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

% 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

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

Substructures of interestSubstructures of interest

Relationship between Brain Relationship between Brain Volume and Autistic FeaturesVolume and Autistic Features

Social Communication

AtypicalBehaviors

Substructures of interestSubstructures of interest

Basal gangliaBasal ganglia– CaudateCaudate– PutamenPutamen– Globus Globus

palliduspallidus

AmygdalaAmygdala

HippocampusHippocampus

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)

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)

Hollander et al. Biological Psychiatry 2005

Clinical Correlates of Caudate VolumeClinical Correlates of Caudate Volume

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

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

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

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

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)

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)

Imaging DevelopmentImaging Development

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

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

Gray matter maturationGray matter maturation

Gogtay, Giedd et al PNAS 2004. N = 13 (7 male, 6 female) typical subjects

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.

Neonatal Brain MRINeonatal Brain MRI

T2T2T1T1

non-myelinated

white matter

early myelinated white matter

gray matter

Corpus CallosumCorpus Callosum

Neonate (2 wks) Adult

Corpus callosum: FA along Commissural bundles

Infant (1 year)

Infancy to ChildhoodInfancy to Childhood

Hermove et al., NeuroImage 2005.

Data Data

Data Data

Structural MRI Structural MRI

Diffusion TensorDiffusion Tensor

Behavioral, cognitive, developmentalBehavioral, cognitive, developmental

Processed longitudinal dataProcessed longitudinal data

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

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

Image ProcessingImage Processing

Tissue segmentation –2 yr oldTissue segmentation –2 yr old

EMS hard segmentations

EMS segmentations overlaid on MRI

Automatic parcellation by template warpingAutomatic parcellation by template warping

Manually-derived parcellation “warped” to new subjects

Challenges to Image ProcessingChallenges to Image Processing

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

Future DirectionsFuture Directions

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

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)

Surface growth maps Surface growth maps

age 2 4

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

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

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 !