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Imaging the Long-Term Effects of Drug Exposure in Utero - Emory ...

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Albert E<strong>in</strong>ste<strong>in</strong> College<br />

<strong>of</strong> Medic<strong>in</strong>e<br />

May 16, 2011<br />

Claire D. Coles, Ph.D.<br />

Departments <strong>of</strong> Psychiatry and Behavioral Sciences and Pediatrics<br />

<strong>Emory</strong> University School <strong>of</strong> Medic<strong>in</strong>e, Atlanta, GA


• Departments <strong>of</strong> Psychiatry<br />

and Behavioral Sciences<br />

and Pediatrics, <strong>Emory</strong><br />

University School <strong>of</strong><br />

Medic<strong>in</strong>e<br />

• Fetal Alcohol and <strong>Drug</strong><br />

<strong>Exposure</strong> Center, at <strong>the</strong><br />

Marcus Autism Center <strong>of</strong><br />

Children’s Health Care <strong>of</strong><br />

Atlanta


• Biomedical <strong>Imag<strong>in</strong>g</strong><br />

Technology Center, Wallace H.<br />

Coulter Center<br />

<strong>Emory</strong> University & Georgia Institute <strong>of</strong><br />

Technology<br />

• Xiaop<strong>in</strong>g P. Hu, Ph.D.<br />

(Director)<br />

• Zhihao Li, Ph.D.<br />

• <strong>Long</strong>chaun Li, Ph.D.<br />

• Xiangchuan Chen, PhD.<br />

• Priya Santhanam, PhD<br />

• Gopikrishna Deshpande, PhD<br />

(Auburn University)<br />

• Maternal Substance Use and<br />

Child Development Laboratory<br />

<strong>Emory</strong> University School <strong>of</strong> Medic<strong>in</strong>e<br />

• Mary Ellen Lynch, Ph.D.<br />

• Julie A. Kable, Ph.D.<br />

• Department <strong>of</strong> Neurology<br />

• Felicia Goldste<strong>in</strong>, PhD.<br />

• Department <strong>of</strong> Psychology<br />

• Stephan Hamann, Ph.D.


Some <strong>of</strong> <strong>the</strong> Research discussed today was supported by:<br />

National Institute on Alcoholism and Alcohol Abuse, R01<br />

AA014373<br />

National Institute on <strong>Drug</strong> Abuse, R01-DA 07362<br />

Georgia Department <strong>of</strong> Human Resources


%<br />

30<br />

25<br />

20<br />

15<br />

10<br />

5<br />

0<br />

Marijuana Coca<strong>in</strong>e O<strong>the</strong>r Alcohol Cigarettes<br />

Ebrahim, SH, & Gfroerer, J (2003) Obstetrics and Gynecology, 101, p374-378


State-Specific Weighted Prevalence Estimates <strong>of</strong> Alcohol Use<br />

(Percentage <strong>of</strong> Any Use/B<strong>in</strong>ge Dr<strong>in</strong>k<strong>in</strong>g)<br />

Among Women Aged 18 – 44 Years — BRFSS, 2008<br />

CA<br />

Guam<br />

28.6<br />

7.1<br />

OR<br />

WA<br />

43.3<br />

12.8<br />

53.1<br />

14.8<br />

53.0<br />

12.9<br />

AK<br />

51.7<br />

18.0<br />

46.1<br />

12.0<br />

NV<br />

MT<br />

ID<br />

45.0<br />

12.9<br />

UT<br />

20.4<br />

6.5<br />

51.6<br />

15.5<br />

AZ<br />

WY<br />

54.4<br />

19.3<br />

NM<br />

49.1<br />

15.0<br />

CO<br />

56.6<br />

14.7<br />

42.6<br />

10.0<br />

44.7<br />

15.5<br />

TX<br />

HI<br />

ND<br />

SD<br />

NE<br />

54.0<br />

23.0<br />

57.0<br />

19.4<br />

53.2<br />

18.9<br />

KS<br />

49.2<br />

12.8<br />

OK<br />

40.9<br />

11.3<br />

43.6<br />

11.6<br />

MN<br />

56.9<br />

19.3<br />

IA<br />

58.2<br />

22.9<br />

49.2<br />

16.0<br />

MO<br />

WI<br />

39.8<br />

11.1<br />

68.4<br />

23.9<br />

AR<br />

55.4<br />

19.4<br />

35.3<br />

45.6<br />

8.9<br />

10.7<br />

LA<br />

41.7<br />

6.1<br />

IL<br />

MS<br />

51.1<br />

MI<br />

NY 12.8<br />

58.8<br />

18.7<br />

PA<br />

52.5<br />

OH<br />

47.6<br />

54.5<br />

18.9<br />

16.3<br />

12.3<br />

WV<br />

28.8<br />

IN<br />

49.5<br />

38.0<br />

6.9<br />

14.7<br />

9.9<br />

VA<br />

KY<br />

40.4<br />

31.7<br />

NC<br />

TN<br />

11.8<br />

8.0<br />

SC<br />

40.8<br />

AL GA<br />

11.4<br />

38.1<br />

47.1<br />

9.5<br />

12.5<br />

U.S. Virg<strong>in</strong> Islands<br />

25.2<br />

7.7<br />

Puerto Rico<br />

FL<br />

64.0<br />

17.9<br />

NJ<br />

VT<br />

ME<br />

58.7<br />

18.2<br />

61.2<br />

NH 12.5<br />

63.1<br />

MA<br />

19.5<br />

CT 58.0<br />

63.9<br />

18.1<br />

RI<br />

52.3<br />

16.0<br />

14.9<br />

55.2<br />

DE<br />

53.8<br />

17.1<br />

MD<br />

14.9<br />

Wash<strong>in</strong>gton, D.C. 62.1<br />

21.9<br />

Any Use<br />

47.7<br />

10.9<br />

B<strong>in</strong>ge<br />

TM


Alcohol is a TERATOGEN:


FAS<br />

• Prenatal<br />

Alcohol<br />

<strong>Exposure</strong><br />

• Face<br />

• Growth<br />

• Bra<strong>in</strong>


• General Cognitive/Learn<strong>in</strong>g Skills (IQ)<br />

• Executive Function<strong>in</strong>g Skills<br />

• Attentional regulation<br />

• Memory,Plann<strong>in</strong>g and organization<br />

• Motor skills<br />

• Visual/spatial skills<br />

• Academic Achievement<br />

• Adaptive Behavior<br />

• Social Behavior<br />

• Mental Health/Behavioral Disorders


• Adult Follow-up <strong>of</strong> Prenatally Identified Cohort-M<br />

age 22.5 Years<br />

• Predom<strong>in</strong>antly African-American, Born 1980 to<br />

1986<br />

• Documented exposure to EtOH and o<strong>the</strong>r drugs<br />

• High levels <strong>of</strong> exposure (M=10+ AAoz/wk= 20+<br />

dr<strong>in</strong>ks)<br />

• <strong>Long</strong>itud<strong>in</strong>al vs Cl<strong>in</strong>ical sample; not biased by<br />

behavior problems, etc<br />

• Developmental and social history known


• Controls- Recruited prenatally, same hospital and<br />

SES, no alcohol exposure.<br />

• Dysmorphic -Recruited prenatally, alcohol<br />

exposed, Dysmorphic Checklist score 1 SD above<br />

group mean.<br />

• ARND - Recruited prenatally, alcohol exposed, no<br />

dysmorphia, IQ


Control<br />

ARND<br />

DYSM<br />

(n = 26)<br />

(n = 36)<br />

(n = 30)<br />

% Males 46.2 27.8 46.7<br />

% A-A 1 100 97.2 100<br />

Age (yrs) 22.7 (1.7) 23.1 (1.6) 23.1 (2.2)<br />

Ed (yrs) 12.3 (1.6) 11.7 (1.5) 11.8 (1.3)<br />

Dysm Score<br />

3.62 (3.3) 4.7 (3.8) 9.43 (7.8)*<br />

FSIQ 2 84.0 (8.6) 80.5 (12.1) 76.0 (12.0)*<br />

AA/oz/wk 0 (0) 7.7 (13.1)* 13.5 (13.6)*<br />

1<br />

. African-American; 2 . Full Scale IQ * Indicates a significant difference


• Structure-Identify structural<br />

changes associated with<br />

prenatal alcohol exposure<br />

(PAE)-sMRI<br />

• White matter <strong>in</strong>tegrity-Us<strong>in</strong>g<br />

Diffusion Tensor <strong>Imag<strong>in</strong>g</strong> (DTI),<br />

identify effects <strong>of</strong> PAE on<br />

structural connectivity<br />

• Activation-Us<strong>in</strong>g fMRI, exam<strong>in</strong>e<br />

differences <strong>in</strong> activation <strong>of</strong><br />

candidate ROIs-Math and<br />

Attention Tasks<br />

3T Siemens<br />

Magnetom Trio<br />

Scanner


• PAE is associated with structural changes <strong>in</strong><br />

bra<strong>in</strong><br />

• PAE affects white matter <strong>in</strong>tegrity<br />

• PAE is associated with alterations <strong>in</strong> BOLD<br />

activation <strong>in</strong> areas responsible for Math<br />

performance<br />

• PAE affects bra<strong>in</strong> networks responsible for<br />

structural and functional connectivity


• 96 separate measurements <strong>of</strong> bra<strong>in</strong> volume, rang<strong>in</strong>g<br />

from total Intracranial volume to subcortical structures<br />

(e.g., hippocampus)us<strong>in</strong>g Free surfer<br />

• Exam<strong>in</strong>ed:<br />

▪ Cortical regions<br />

▪ Subcortical<br />

▪ Corpus Callosum<br />

• Compared:<br />

• Alcohol exposure vs Nonexposed Controls<br />

• Alcohol “affected” vs “non-affected” vs Controls


SFr: Superiorfrontal<br />

RMF: Rostralmiddlefrontal<br />

CMF: Caudalmiddlefrontal<br />

PTr: Parstriangularis<br />

POr: Parsorbitalis<br />

LOF: Lateralorbit<strong>of</strong>rontal<br />

PrC: Precentral<br />

PoC: Postcentral<br />

SuM: Supramarg<strong>in</strong>al<br />

SPa: Superiorparietal<br />

STe: Superiortemporal<br />

ITe: Inferiortemporal<br />

LOc: Lateraloccipital,<br />

CAC: Caudalanteriorc<strong>in</strong>gulate<br />

PCu: Precuneus<br />

Cun: Cuneus<br />

PCa: Pericalcar<strong>in</strong>e<br />

L<strong>in</strong>: L<strong>in</strong>gual<br />

Fus: Fusiform<br />

PHi: Parahippocampal<br />

RAC: Rostralanteriorc<strong>in</strong>gulate<br />

IPa: Inferiorparietal<br />

POp: Parsopercularis.<br />

Cortical regions exhibit<strong>in</strong>g PAE effects (N=92)<br />

Chen, et al., (2011) ) Understand<strong>in</strong>g Specific <strong>Effects</strong> <strong>of</strong> Prenatal Alcohol<br />

<strong>Exposure</strong> on Bra<strong>in</strong> Structure <strong>in</strong> Young Adults, Human Bra<strong>in</strong> Mapp<strong>in</strong>g


Cbr: Cerebral Cortex<br />

Cbe: Cerebellum<br />

Cortex<br />

Tha: Thalamus Proper<br />

Hip: Hippocampus<br />

Put: Putamen<br />

Pal: Pallidum<br />

Amy: Amygdala<br />

Cau: Caudate<br />

Acu: Accumbens<br />

Area.<br />

R: Right Hemisphere,<br />

L: Left Hemisphere.<br />

Sub-cortical regions exhibit<strong>in</strong>g PAE effects, (N=92)


<strong>Effects</strong> <strong>of</strong> Prenatal Alcohol <strong>Exposure</strong> on Corpus Callosum Volume<br />

. Segmentation <strong>of</strong> <strong>the</strong> corpus callosum (A), <strong>in</strong> which some<br />

portions (1, 4 and 5) exhibited <strong>the</strong> general PAE effect (B). 1:<br />

Anterior, 2: Mid-Anterior, 3: Central, 4: Mid-Posterior, 5:<br />

Posterior.<br />

•Chen, X., C.D. Coles, M.E. Lynch, X. Hu (2011, <strong>in</strong> Pre ) Understand<strong>in</strong>g Specific <strong>Effects</strong> <strong>of</strong><br />

Prenatal Alcohol <strong>Exposure</strong> on Bra<strong>in</strong> Structure <strong>in</strong> Young Adults, Human Bra<strong>in</strong> Mapp<strong>in</strong>g ss


250000<br />

200000<br />

150000<br />

100000<br />

50000<br />

Control<br />

EtOH<br />

DYSM<br />

SpecED<br />

In Cerebral<br />

Cortex,<br />

Dysm


250000<br />

200000<br />

150000<br />

100000<br />

50000<br />

Control<br />

EtOH<br />

DYSM<br />

SpecED<br />

0<br />

Lcerebral Rcerebral Lc'bellum Rc'bellum<br />

p


• White matter <strong>in</strong>tegrity-Us<strong>in</strong>g Diffusion<br />

Tensor <strong>Imag<strong>in</strong>g</strong> (DTI), identify effects <strong>of</strong> PAE<br />

<strong>in</strong> corpus callosum<br />

• Assumption, <strong>the</strong>re are specific effects on<br />

White Matter <strong>in</strong>tegrity <strong>in</strong> bra<strong>in</strong>


• Diffusion Tensor <strong>Imag<strong>in</strong>g</strong> exam<strong>in</strong>es white<br />

matter <strong>in</strong>tegrity and white matter tracts.<br />

• Behavioral data <strong>in</strong> alcohol-affected<br />

<strong>in</strong>dividuals suggests a effect on white<br />

matter <strong>in</strong>tegrity.<br />

• Structural neuroimag<strong>in</strong>g studies <strong>in</strong>dicate<br />

differences <strong>in</strong> white matter, particularly<br />

loss <strong>of</strong> white matter <strong>in</strong> alcohol-affected<br />

<strong>in</strong>dividuals.


• FA-Fractional Anistropy-How strongly directional local<br />

tract structure is. Responsive to conditions that affect<br />

axon development or damage axons reflected <strong>in</strong> low FA<br />

and Hi MD.<br />

• MD-Mean diffusivity. Average Diffusion <strong>in</strong> all 3 directions.<br />

• AD-Axial Diffusivity- Mean magnitude <strong>of</strong> water diffusion<br />

parallel to axon direction with<strong>in</strong> <strong>the</strong> voxel <strong>of</strong> axon tractsmeasures<br />

axonal <strong>in</strong>tegrity<br />

• RD-Radial Diffusivity-Mean magnitude <strong>of</strong> water diffusion<br />

perpendicular to axon tracts-measures demylenization


LI, Coles, Lynch, & Hu, Human Bra<strong>in</strong> Mapp<strong>in</strong>g, 2009


Us<strong>in</strong>g TBSS for DTI analysis, voxel-wise statistics on <strong>the</strong> skeletonized FA data reveal<br />

subregions <strong>of</strong> <strong>the</strong> c<strong>in</strong>gulum with significantly lower FA values <strong>in</strong> both PAE groups<br />

versus control subjects.<br />

Skeletonized FA difference between Control and Non-Dysmorphic PAE groups<br />

(green=skeleton, purple=anatomically def<strong>in</strong>ed ROI, p<strong>in</strong>k=region <strong>of</strong> significant<br />

difference). Similar differences were seen between control and dysmorphic PAE<br />

groups.<br />

Santhanam, et al, 2011, <strong>in</strong> press


TBSS results for bilateral<br />

c<strong>in</strong>gulum. ROI shows<br />

significant differences<br />

between<br />

(a) Control and Non<br />

Dysmorphic PAE groups<br />

(b) Control and Dysmorphic<br />

PAE groups <strong>in</strong> FA.<br />

Green <strong>in</strong>dicates mean FA skeleton<br />

and red <strong>in</strong>dicates regions <strong>of</strong><br />

significant difference between<br />

groups, with thickened red-yellow<br />

for <strong>the</strong> bilateral c<strong>in</strong>gulum ROI.<br />

Axial slices shown are z=107 to<br />

z=112.


Controls Non-Dys PAE Dys PAE<br />

Left hand<br />

response to<br />

Opposite side<br />

stimulation (LO)<br />

*Significant difference between Dys-PAE and Control groups <strong>in</strong> premotor area<br />

Controls Non-Dys PAE Dys PAE<br />

Right hand<br />

response to<br />

Opposite side<br />

stimulation (RO)<br />

*Significant difference between Dys-PAE and Control groups <strong>in</strong><br />

primary motor (arrows) and premotor areas


Group maps <strong>of</strong><br />

task-related activation<br />

Difference maps <strong>of</strong><br />

task-related activation<br />

Control-NonDys<br />

Control<br />

Non-dys<br />

PAE<br />

Dys PAE<br />

+<br />

_<br />

Control-Dys<br />

29


Regions <strong>of</strong> default mode deactivation dur<strong>in</strong>g arithmetic task (us<strong>in</strong>g<br />

letter-match<strong>in</strong>g task as basel<strong>in</strong>e). MPFC and PCC clusters from <strong>the</strong>se<br />

group average activation maps were used for subsequent rest<strong>in</strong>g-state<br />

analysis. Color bar <strong>in</strong>dicates <strong>the</strong>se regions are negatively activated.<br />

Figure 1


Rest<strong>in</strong>g-state functional<br />

connectivity (correlation)<br />

group maps (a) with and (b)<br />

without global signal<br />

regression. At threshold<br />

p


FIGURE 3: Difference correlation<br />

maps <strong>of</strong>:<br />

(a) Control-Non Dysmorphic PAE<br />

(b) Control-Dysmorphic PAE<br />

groups seeded at <strong>the</strong> PCC region<br />

and masked at MPFC region<br />

identified <strong>in</strong> Figure 1.<br />

Control groups had more<br />

correlation with <strong>the</strong> MPFC than<br />

ei<strong>the</strong>r exposure group (red-yellow<br />

<strong>in</strong>dicates positive difference).<br />

Threshold used was p


• Task related reactivity <strong>in</strong> DMN affected by<br />

PAE<br />

• Structural Connectivity lower (DTI)<br />

• Functional Connectivity affected (fMRI)<br />

• Implies that structural connectivity deficit<br />

affects functional network <strong>in</strong> system that<br />

modulates attention and cognition


• Genetic differences that characterize women<br />

who use drugs/alcohol dur<strong>in</strong>g pregnancy<br />

• Social factors, like nutrition, post natal<br />

environment, social class, ethnic group…<br />

• Polydrug exposure prenatally and postnatally<br />

• Experimental characteristics-sample<br />

selection, research design, and so forth


• Evidence for persistent, global deficits even<br />

when SES and postnatal environment<br />

accounted for.<br />

• In addition to global deficits, <strong>the</strong>re may be<br />

specific cognitive problems <strong>in</strong> <strong>the</strong> follow<strong>in</strong>g<br />

areas: Motor function<strong>in</strong>g, visual spatial skills,<br />

math, memory.<br />

• MRI (and fMRI) suggest neurological basis for<br />

behavioral f<strong>in</strong>d<strong>in</strong>gs.


• Coles CD; Li Z (2011) Functional neuroimag<strong>in</strong>g <strong>in</strong><br />

<strong>the</strong> exam<strong>in</strong>ation <strong>of</strong> effects <strong>of</strong> prenatal alcohol<br />

exposure.<br />

• Lebel C; Roussotte F; Sowell ER (2011) <strong>Imag<strong>in</strong>g</strong><br />

<strong>the</strong> impact <strong>of</strong> prenatal alcohol expsure on <strong>the</strong><br />

structure <strong>of</strong> <strong>the</strong> develop<strong>in</strong>g human bra<strong>in</strong>.<br />

• Wozniak JR; Muetzel RL (2011) What does<br />

diffusion tensor imag<strong>in</strong>g reveal about <strong>the</strong> bra<strong>in</strong><br />

and cognition <strong>in</strong> fetal alcohol spectrum disorders?


• 20 years <strong>of</strong> research<br />

• Bra<strong>in</strong> Volume -Smaller <strong>in</strong> Diagnosed cases<br />

and prenatal exposure<br />

• With total BV controlled, specific effects<br />

noted <strong>in</strong> corpus callosum, caudate,<br />

hippocampus, cerebellum. O<strong>the</strong>r areas also<br />

noted.<br />

• Both white and grey matter affected but<br />

white more affected.<br />

• Sowell and colleagues-cortical thicken<strong>in</strong>g<br />

• Reductions found more <strong>of</strong>ten <strong>in</strong> frontal,<br />

parietal. O<strong>the</strong>r areas less studied.


• 7 Studies, 2 with adults, 5 with older children<br />

and adolescents.<br />

• Microstructural anomalies found <strong>in</strong> many<br />

regions studied, but particularly, Corpus<br />

Callosum<br />

• Structural and functional deficits appear related<br />

• DTI seems sensitive to teratogenic effects <strong>of</strong><br />

alcohol; however, effects are not specific but<br />

similar to those <strong>in</strong> o<strong>the</strong>r disorders<br />

• Lack <strong>of</strong> developmental norms makes<br />

<strong>in</strong>terpretation difficult.

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