ORIGINAL PAPER

Structural brain changes in prenatalmethamphetamine-exposed children

Annerine Roos & Gaby Jones & Fleur M. Howells &

Dan J. Stein & Kirsten A. Donald

Received: 15 October 2013 /Accepted: 28 January 2014 /Published online: 20 February 2014# Springer Science+Business Media New York 2014

Abstract The global use of methamphetamine (MA) hasincreased substantially in recent years, but the effect of MAon brain structure in prenatally exposed children isunderstudied. Here we aimed to investigate potential changesin brain volumes and cortical thickness of children with pre-natal MA-exposure compared to unexposed controls. Eigh-teen 6-year old children with MA-exposure during pregnancyand 18 healthy controls matched for age, gender and socio-economic background underwent structural imaging. Brainvolumes and cortical thickness were assessed using Freesurferand compared using ANOVA. Left putamen volume wassignificantly increased, and reduced cortical thickness wasobserved in the left hemisphere of the inferior parietal,parsopercularis and precuneus areas of MA-exposed childrencompared to controls. Compared to control males, prenatalMA-exposed males had greater volumes in striatal and asso-ciated areas, whereas MA-exposed females predominantlyhad greater cortical thickness compared to control females.In utero exposure to MA results in changes in the striatum ofthe developing child. In addition, changes within the striatal,frontal, and parietal areas are in part gender dependent.

Keywords Methamphetamine . Brain structure . Prenatal .

Dopamine

Introduction

The global use of methamphetamine (MA) has increasedsubstantially in recent years, including in pregnant women.In the United States an increase of 8 % in 1994 to 24 % in2006 was reported in pregnant women (Terplan et al. 2009).Another study conducted in South Africa found that during2006, of 58 % of daily MA users, women mainly of mixedrace made up a quarter (24 %–29 %), and more than 90 % offemale subjects were women of childbearing age(Pluddemann et al. 2008). In a recent South African study(of a local mixed race population in the Western Cape), 238out of 356 non-pregnant women in their 20’s (66%) usedMA,whereas 24 out of 26 pregnant women (92%) usedMA (Joneset al. 2011). It is thus likely that a significant number ofwomen will use MA during pregnancy, with resultant risksfor both mother and child.

MA has specific effects on neurotransmitter systems, in-creasing the release and blocking the reuptake of dopamine indopamine-rich striatal areas of the brain. Animal studies haveshown that in MA-exposed pregnant rodents, MA crosses theplacenta and has global effects on the developing fetus and inparticular the central nervous system (Wouldes et al. 2004).Pregnant mice exposed to MA, showed a two to three timesincrease in MA levels of the fetal striatum after MA wassubcutaneously injected into the female (Heller et al. 2001;Won et al. 2001). In humans, MA also crosses the placenta aswell as the blood–brain barrier to exert effects on the fetalbrain (Won et al. 2001). The blood–brain barrier of the humanfetus is more permeable than that of children and adults, andthe fetus is unable to efficiently metabolise and detoxify drugs(Rozman and Klaassen 1996). This may potentiate damaging

A. Roos (*) :G. Jones :D. J. SteinMRCUnit on Anxiety & Stress Disorders, Department of Psychiatry,Stellenbosch University, P.O. Box 19063, Tygerberg, 7505 CapeTown, South Africae-mail: aroos@sun.ac.za

F. M. HowellsDepartment of Psychiatry and Mental Health, University of CapeTown, Cape Town, South Africa

K. A. DonaldDivision of Developmental Paediatrics, University of Cape Town,Cape Town, South Africa

Metab Brain Dis (2014) 29:341–349DOI 10.1007/s11011-014-9500-0

effects of MA to the human brain, particularly in the striatum,during fetal development.

MA also appears to have specific effects on growth andneurodevelopment. A prospective study conducted in the USfound that prenatal MA-exposed infants were more likely tobe smaller for gestational age than were controls, even afteradjusting for demographic and clinical information and sub-stance use (Nguyen et al. 2010). These authors also demon-strated that MA-exposure in utero was associated with centralnervous system stress, in addition to poor tone, decreasedarousal, and poor quality of movement in neonates. Limitedevidence in children suggests that there may be a number ofneuroanatomical sequelae of prenatal exposure to MA. Asmall number of studies including that of Chang et al.(2004) and Sowell et al. (2010) who studied children in theage range of 3–16 years found volumetric changes mainly indopamine-rich striatal areas, including frontal and parietalareas. Colby et al. (2012) also found alterations in whitematter microstructure within these areas in prenatal MA- andalcohol-exposed children aged 10. However, there is presentlyno data on the effects of in utero MA-exposure on corticalthickness.

The aim of this study was to investigate potential changesin brain volumes and cortical thickness of children with pre-natal MA-exposure compared to unexposed controls. Ourhypotheses are that there will be changes in brain volumesand cortical thickness particularly of striatal and associatedfrontal and parietal areas.

Methods

Subjects

Children residing in the Cape Metropole were included in thestudy. Children with known prenatal MA-exposure and unex-posed children were matched for age, sex, socioeconomicprofile, birth circumstances, gestation and schooling. Childrenwere excluded from the study if there were; fetal anomalies;history of epilepsy, diabetes, or head injury; or premature birth(less than 36 weeks). Although the aim of this study was toinclude only prenatal MA-exposed children, in a small minor-ity the mother used alcohol (n=3). These mothers/caregiversstated that no other drugs (e.g. cocaine, heroin) were usedbesides MA during pregnancy. None of the mothers of thecontrols used alcohol or illicit drugs.

A detailed demographic, socio-economic and medical his-tory of the child was taken during the brain imaging session (atthe time of birth and current), as well as of the mother andfamily (including the use of other recreational drugs andalcohol). Anthropometrics were also determined including

weight, length and head circumference of the child. The childwas prepared for imaging in a mock scanner emulating theMRI scanner in terms of form and sequence noise. The childchose an animated movie that they viewed during the scan.

Parental/legal guardian and child consent were givenbefore inclusion into the study. The attending caregiverwas informed that participation was voluntary and thatthey were allowed to withdraw from the study at anytime without any consequences to them, either social ormedical. The study was approved by the Health Re-search Committee of Stellenbosch University and Uni-versity of Cape Town and was conducted according tothe ethical guidelines of the international Declaration ofHelsinki 2008.

Brain imaging and data analyses

Brain images were acquired on a Siemens Allegra 3 T MRIscanner. A high resolution motion-navigated T1 multiechoMPRAGE structural scan (Van der Kouwe et al. 2008) wasacquired with the following parameters: repetition time of2,530 ms; 4 echo times of 1.5 ms, 3.2 ms, 4.8 ms and6.5 ms; flip angle of 7°; matrix size of 224×224×144; fieldof view of 224 mm; voxel size of 1.3×1.0×1.0 mm andacquisition time of 5 min 20 s. The sequence used anechoplanar imaging volumetric navigator to track and correctsubject motion in real time. A stabilising head cushion wasused during imaging (Howells; Stabilising kit, UK).

Freesurfer 5.1.0 was implemented on a localsupercomputing cluster at the Centre for High PerformanceComputing (CHPC, Cape Town). Freesurfer provides cerebralcortex and white matter models to reconstruct DICOM imagesin order to determine volumes and cortical thickness. Brainregions are segmented into different tissue classes by applyingMarkov random field theory to acquire volumetric informa-tion (Desikan et al. 2006; Fischl et al. 2004). The cerebralcortex is divided into different regions as defined by gyral andsulcal structure to perform thickness measurements. Corticalthickness is determined as the closest distance from the gray orwhite matter boundary to the gray or cerebrospinal fluidboundary at each vertex on the image (Fischl and Dale2009). Volumetric and cortical thickness data were extractedand compared by group using individual factorial ANOVAs inStatistica 11. Upon preliminary investigation of data, variabledifferences in volumes were found between boys and girls infronto-striatal regions, while girls had greater cortical thick-ness across lobes (Table 1). Subsequently, group and genderwere included as categorical factors. Fisher’s least significantdifference (or LSD) tests were performed post hoc to differ-entiate significant interaction effects.

342 Metab Brain Dis (2014) 29:341–349

Results

Subjects

A sample of 48 children aged six years was recruited to thestudy. The final sample included data from 36 children; therewere 18 prenatal MA-exposed children (10 male, 8 female)and 18 unexposed controls (8 male, 10 female). Although weaimed to have information by trimester regarding the timeperiod and amount of MA use, we were unable to acquire thisinformation. This is likely because there is fear and shameamong these people associated with disclosure, especially ofillicit drugs, and accuracy of reporting on drug usage is oftenunreliable. Children (n=12) were excluded from the initialsample for the following reasons: 1) wewere unable to acquireuseful scans from six MA-exposed and three unexposed chil-dren; 2) one unexposed child was excluded and referred forclinical evaluation after imaging, due to explicit low cognitiveability and probable fetal alcohol syndrome, and 3) two struc-tural scans could not be used due to motion artefacts.

The children were of mixed race, and of low socio-economic status according to profiles on income, employmentand housing. The majority of children were either in their

preparatory year (~40 %) or first year of formal schooling(~50 %). There were no significant differences in any demo-graphic or anthropometric data between the MA-exposed andunexposed groups. See Table 2.

Mothers of MA-exposed children had significantly lowereducational levels compared tomothers of unexposed controls[t(1,31)=2.10, p=0.044]. The unemployment rate of MA-users was high (76 %) compared to non-users (44 %), whereincome was comparably low in MA-users.

Volumes and cortical thickness

Group effects

There was significantly increased left putamen volume inMA-exposed children compared to controls [F(1,32)=6.38,p=0.017] (Fig. 1). There was also significantly reduced lefthemisphere cortical thickness of the inferior parietal[F(1,32)=6.05, p=0.020], parsopercularis [F(1,32)=6.72,p=0.014] and precuneus areas [F(1,32)=6.96, p=0.013] ofMA-exposed children compared to controls (Fig. 2).

Table 1 Significantly greater volumes and cortical thickness by gender.These differences are consistent with previous findings on brain devel-opment including frontal, striatal, parietal and temporal regions (Lenrootand Giedd 2006; Sowell et al. 2002, 2007). Notably, there are greater

caudate volume and thicker cortices in right parietal and temporal regionsin females (Durston et al. 2001; Giedd et al. 1996; Sowell et al. 2007).Means are presented in mm

Male Female F pmean (SD) mean (SD)

Volumes

Male > female

L Thalamus 0.0054 (0.0003) 0.0051 (0.0003) 5.43 0.026

Female > male

L Caudate 0.0029 (0.0003) 0.0032 (0.0003) 10.83 0.002

R Caudate 0.0030 (0.0004) 0.0033 (0.0009) 6.57 0.015

R Accumbens 0.0006 (0.0001) 0.0007 (0.0001) 9.74 0.004

Cortical thickness

Female > male

R Fusiform gyrus 2.9910 (0.1546) 3.0916 (0.1019) 4.69 0.038

R Isthmus cingulate 2.6624 (0.2034) 2.8583 (0.1579) 9.32 0.005

R Lateral orbitofrontal cortex 3.1082 (0.3188) 3.2971 (0.1295) 4.77 0.036

R Parahippocampal 2.5594 (0.3288) 2.8401 (0.2573) 7.24 0.011

R Precuneus 2.8371 (0.1447) 2.9678 (0.1379) 7.74 0.009

L Superior frontal 3.2450 (0.2159) 3.4455 (0.1497) 9.43 0.004

R Superior frontal 3.1857 (0.2581) 3.3961 (0.1756) 7.58 0.010

L Transverse temporal 2.5042 (0.2922) 2.7508 (0.2190) 8.19 0.007

R Transverse temporal 2.6645 (0.2036) 2.8213 (0.1960) 6.46 0.016

L Precentral 2.6404 (0.1362) 2.7499 (0.1399) 5.41 0.027

L left hemisphere, R right hemisphere

Metab Brain Dis (2014) 29:341–349 343

Gender effects

There were significant group and gender interactions in vol-umes and cortical thickness, mainly of striatal areas (Table 3,Fig. 3). MA-exposed males had significantly greater volumescompared to control males, of the left globus pallidus, and leftand right ventral diencephalon. MA-exposed males also hadincreased right ventral diencephalon volume compared toMA-exposed females; the opposite was observed in control

males compared to control females. Furthermore, there wassignificantly reduced mid-posterior corpus callosum volumein MA-exposed females compared to control females. Finally,cortical thickness was significantly increased in the banks ofthe superior central sulcus and cuneus of MA-exposed fe-males compared to control females.

Discussion

The findings of this study revealed significant structuralchanges mainly of striatal, parietal and temporal areas in 6-year old MA-exposed children compared to controls in 1)volumes, 2) cortical thickness and 3) group by gender inter-actions of volumes and cortical thickness.

Changes in striatal volume in MA-exposed subjects havepreviously been shown by animal research (Siegel et al. 2010)as well as by a limited number of studies involving prenatalMA-exposed children (Chang et al. 2004; Berman et al. 2008;Sowell et al. 2010). MA elevates dopamine levels in the fetalrodent brain particularly in the striatum, and the cortex afterprenatal exposure (Heller et al. 2001; Won et al. 2001). Theseauthors report that this increase is within the range of levelsfound for post-mortem brains of premature twin human in-fants who were prenatally exposed to MA (Bost et al. 1989).Chang et al. (2004) found decreased volumes of the putamenin addition to volume reductions of the globus pallidus andcaudate of prenatal MA-exposed children compared to con-trols. Furthermore, a recent study investigating white matterstructure in children found early alterations in correspondingfrontal and parietal areas in prenatal MA-exposed children (3to 4 year olds) compared to controls (Cloak et al. 2009).Another study found alterations in fronto-putamen connectiv-ity during a working memory task in prenatal MA-exposedchildren compared to controls (Roussotte et al. 2012). Alteredstriatal brain volume and changes in the dopaminergic system

Table 2 Demographic and anthropometric information of prenatal MA-exposed and control children

MA Controls

Child

Age (mean, SD) 6.45 (0.42) 6.51 (0.33)

Sex (male/female) 10/8 8/10

Weight (kg, SD) 18.81 (2.44) 20.68 (5.89)

Length (cm, SD) 92.15 (7.73) 89.38 (9.03)

Head circumference (cm, SD) 51.75 (1.72) 51.99 (2.41)

Mother

Education (years) 8.88 (1.32) 10.25 (2.32)

Employed (no/yes) 13/4 8/10

Income (n, %)

<R10 000 11 (61) 7 (39)

R10 000-R20 000 2 (11) 2 (11)

R20 000-R40 000 1 (6) 2 (11)

R40 000-R60 000 – 2 (11)

Marital status (n, %)

Single 15 (83) 10 (56)

Married – 6 (33)

Living with partner – 1 (6)

Divorced 2 (12) –

Widowed – 1 (6)

R South African Rand

Fig. 1 Significantly increasedputamen volume in prenatalMA-exposed children comparedto unexposed controls. Verticalbars denote 0.95 confidenceintervals. P putamen

344 Metab Brain Dis (2014) 29:341–349

has been linked with impaired learning in prenatal MA-exposed children (Thompson et al. 2009). MA-exposed chil-dren thus seem predisposed to have altered organisation andpruning of neural networks in those regions and subsequentcognitive difficulties (Cloak et al. 2009; Roussotte et al.2012).

Interpretation of neuroimaging data in the developing brainis complex. Very few studies have looked at the longitudinal

effects of substance exposure on the developing brain. TheCollaborative Initiative on Fetal Alcohol Spectrum Disorders(CIFASD) group (Lebel et al. 2012) has found definite effectsof alcohol exposure on the maturational trajectory of brainstructures reflected in altered volumes over time. While onecannot generalise findings in alcohol exposure to those ofother drugs of abuse, it is likely that prenatal exposure ofany drug of abuse is likely to have effects on these processes

Fig. 2 Significantly reducedcortical thickness in prenatalMA-exposed children comparedto unexposed controls. Meansizes of structures (mm) areindicated under each heading.*p<0.05

Table 3 Group and gender interaction effects. There were greater volumes of striatal areas predominately in MA-exposed males, whereas MA-exposedfemales mainly had greater cortical thickness of specific brain areas

Hemisphere Effect F p

Volumes

Globus pallidus Left ↑ MA male ⊥ C male 4.89 0.034

Ventral diencephalon Left ↑ MA male ⊥ C male 9.27 0.005

Left ↑ MA male ⊥ MA female

Right ↑ MA male ⊥ C male 13.48 0.001

Right ↑ MA male ⊥ MA female

Right ↓ C male ⊥ C female

Thalamus Right ↑ MA male ⊥ MA female 6.13 0.019

Mid-posterior corpus callosum – ↓ MA female ⊥ C female 4.65 0.039

– ↑ C female ⊥ C male

Cortical thickness

Banks of superior central sulcus Left ↑ MA female ⊥ C female 6.28 0.017

Fusiform gyrus Left ↑ MA female ⊥ MA male 4.62 0.039

Cuneus Right ↑ MA female ⊥ C female 4.67 0.039

MA methamphetamine-exposed, C control, ⊥ compared to

Metab Brain Dis (2014) 29:341–349 345

Fig. 3 Significant group and gender interaction effects. Differences involumes were evident in MA exposed males, whereas MA-exposedfemales mainly had increased cortical thickness in striatal, parietal and

temporal areas. a–e denote interaction effects in volumes. f–h denoteinteraction effects in cortical thickness

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(DeVane 1991; Kuhnert 1991). Our findings of (putamen)volume increases as compared to controls may seem contra-dictory to the reported reduction in volume in key areas ofaffected children to date, considering that studies mainlyfound reduced volumes in prenatal MA-exposed children(Chang et al. 2004; Sowell et al. 2010). However, the childrenwere adolescent (mean age of 10 years) whereas our groupwas pre-adolescent. Figure 4 illustrates the importance ofconsidering age and developmental trajectories when structur-al brain changes due to substance use are interpreted. Theorange rectangles indicate where our data fit onto the devel-opmental trajectory as denoted by the Sowell group (2010).From this and because our MA-exposed children also showedalterations in overlapping areas, there is a possibility that thesefindings may represent a similar initial higher volume ofaffected areas (blue lines) compared to unexposed children(black lines) during pre-adolescence. Poor organization andpruning of networks in the developing brain is implicated(Lebel et al. 2012) rather than neuroinflammatory effects thatare seen in adults who use MA (e.g. Sulzer et al. 2005).

Our findings show, that in prenatal MA-exposed 6-year oldchildren, there is altered cortical thickness in the inferiorparietal cortex, parsopercularis and precuneus that corroboratevolumetric changes and probable dysfunction in striatal, pari-etal and temporal areas. First-mentioned areas that are

specifically involved in attention and awareness, perception,motor function, memory and language function (Cavanna andTrimble 2006; Clower et al. 2001; Foundas et al. 1998;Tomaiuolo et al. 1999; Wang et al. 2012) are functionallyinterrelated. A rodent study found that pups of rats withprenatal MA-exposure had impaired sensory-motor functioncompared to control pups (Slamberova et al. 2006). Impairedobject recognition was found later in life in prenatal MA-exposed mice, whereas novel location recognition was im-paired in females (Siegel et al. 2010). In a study that investi-gated cognition in 36 healthy term infants with prenatal ex-posure to amphetamines and/or cocaine and 26 unexposedinfants, deficits were found in attention, visual recognitionmemory, distractibility and activity level (Hansen et al.1993; Struthers and Hansen 1992). Further work is neededto determine whether these early brain changes during earlychildhood predict dysfunction in neurocognition andneurodevelopment later in life.

The findings on gender appear consistent with preliminaryevidence, in animal studies on associations by gender ofprenatal MA-exposure with altered hormone and neurotrans-mitter levels, as well as structural studies in children. A studyinvestigating neonatal and prepubertal estrogen levels in MA-exposed mice, suggested partial neuroprotective effects ofestrogen against MA in females compared to males (Dluzen

Fig. 4 Brain areas withsignificantly differentdevelopmental trajectories inprenatal substance-exposedchildren compared to unexposedcontrols. The orange rectanglesindicate where our data fit ontothe developmental trajectory. Atthat stage, there is higher volumein selected brain regions insubstance-exposed children(blue lines) compared tounexposed children (black lines).Considering the trajectoriesoverall, there is less change inbrain development over time inexposed compared to unexposedchildren that suggest reducedbrain plasticity (Lebel et al. 2012).The figure was used and adaptedwith permission from ElizabethSowell and Catherine Lebel(University of California at LosAngeles, USA)

Metab Brain Dis (2014) 29:341–349 347

and McDermott 2002), so that the impact of prenatal MA-exposure is arguably less severe in females at certain stages ofdevelopment. A study of 3-month old rats that were exposedto MA as newborns found sex-dependent changes in dopa-mine and norepinephrine levels in the caudate, putamen andnucleus accumbens of fronto-striatal areas (Gomez da Silvaet al. 2004). Notably, we found increased right diencephalonvolume in MA-exposed males compared to MA-exposedfemales, and similar group differences in thalamus volume;where the opposite was observed in control males and controlfemales. The ventral diencephalon is the developmental rootto posterior forebrain structures including the thalamus(Jacobson and Marcus 2008) suggesting very early changesin brain development due to MA-exposure by gender.

We found greater volumes in striatal and associated areas inprenatal MA-exposed males compared to control males,whereas exposed females predominantly had greater corticalthickness compared to control females. Boys typically havegreater brain volumes than girls (Durston et al. 2001), whilecortical thickness in girls is greater independent of brainvolume (Sowell et al. 2007) suggesting augmented gender-dependent striatal changes due to prenatal MA-exposure.There was significantly reduced mid-posterior corpuscallosum volume in MA-exposed females compared to unex-posed females, suggesting less efficient connectivity betweenbrain areas. Neural fibres originating from the motor cortex,that are primary motor and sensory area of the parietal lobe,cross through the posterior mid-body or areas IVand Vof thecorpus callosum (Chao et al. 2009; Hofer and Frahm 2006) tostriatal areas. In turn, our findings on altered cortical thicknessof the superior central sulcus and cuneus suggest that senso-rimotor function, facial processing and visual processing(Haxby et al. 2000; McCarthy et al. 1997; Plomp et al.2010; White et al. 1997) of boys and girls may be differen-tially affected by prenatal MA-exposure. The findings suggestthat there are both atypical enhancements and diminutions insex-dependent neurodevelopment in MA-exposed children.

Our study has a number of limitations. Studies of substanceabuse are almost invariably confounded by issues of selectivedisclosure and polysubstance use. The majority of the MA-exposed children were reportedly only exposed to MA duringpregnancy; however three children were also exposed to al-cohol. As this investigation recruited prenatal MA-exposedchildren 6 years after birth, we had no access to biologicalsamples to indicate drug use during pregnancy, and drug usewas based on self-report. Although poverty and other envi-ronmental factors by itself may have effects on brain devel-opment, cases and controls were closely matched for age andgender, and children were from similar socio-economic back-grounds and were of similar ethnicity.

In utero exposure to MA results in changes in the striatum ofthe developing child. In addition, changes within the striatal,frontal, and parietal areas are in part gender dependent. Future

prospective longitudinal studies are needed to address the pre-cise trajectories of changes in brain volumes and cortical thick-ness over time, and their associated neuropsychological andneurodevelopmental impact.

Acknowledgments Thank you to Ali Alhamud and Jean-Paul Fouchefor their valuable input on brain imaging sequences and analyses, and toSamantha Brooks for grammar editing of the manuscript. Thank you tothe funding agencies that supported this study including the MedicalResearch Council of South Africa, the National Research Foundationand the Harry Crossley Foundation. Thank you also to the Centre forHigh Performance Computing at Rosebank (Cape Town) who made theFreesurfer analyses possible.

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