New Results

White Matter Alterations in Young Children with Prenatal Alcohol Exposure

Preeti Kar, Jess E. Reynolds, Melody N. Grohs, W. Ben Gibbard, Carly McMorris, Christina Tortorelli, Catherine Lebel
doi: https://doi.org/10.1101/2021.01.05.425489

Abstract

Prenatal alcohol exposure (PAE) can lead to cognitive, behavioural, and social-emotional challenges. Previous neuroimaging research has identified alterations to brain structure in newborns, older children, adolescents, and adults with PAE; however, little is known about brain structure in young children. Extensive brain development takes place during early childhood; therefore, understanding the neurological profiles of young children with PAE is critical for early identification and effective intervention. We studied 54 children (5.21±1.11 years; 27 males) with confirmed PAE compared to 54 age- and sex-matched children without PAE. Children underwent diffusion tensor imaging between 2 and 7 years of age. Mean fractional anisotropy (FA) and mean diffusivity (MD) were obtained for 10 major white matter tracts, along with tract volume, axial and radial diffusivity (AD, RD). A univariate analysis of covariance was conducted to test for group differences (PAE vs. control) controlling for age, sex and tract volume. Our results reveal white matter microstructural differences between young children with PAE and unexposed controls. The PAE group had higher FA and/or lower MD (as well as lower AD and RD) in the genu and the body of the corpus callosum, as well as the bilateral uncinate fasciculus and pyramidal tracts. Our findings align with studies of newborns with PAE finding lower AD, but contrast those in older populations with PAE, which consistently report lower FA and higher MD. These findings may reflect premature development of white matter that may then plateau too early, leading to the lower FA/higher MD observed at older ages.

Introduction

Prenatal alcohol exposure (PAE) affects the developing brain by altering neuronal and glial proliferation and migration, as well as disrupting synaptogenesis, gene transcription, and apoptotic processes (Goodlett et al., 2005; Wilhelm et al., 2016). Fetal alcohol spectrum disorder (FASD) is the neurodevelopmental disorder caused by PAE (Cook et al., 2015), and has an estimated prevalence of 2-5% in North America (May et al., 2014; Popova et al., 2019), considerably higher than most other neurodevelopmental disorders (Flannigan et al., 2018).

Cognitive, behavioural and social-emotional challenges are commonly observed in individuals with PAE and/or FASD, including lower cognitive and academic achievement (Mattson et al., 2019), impairments in expressive and receptive language (Wyper et al., 2011), motor deficits (Lucas et al., 2016), as well as a significantly increased risk of mental health disorders (Pei et al., 2011). Investigating the brain structure underlying these impairments can shed light upon the neurobiological effects of PAE teratogenesis.

Magnetic resonance imaging (MRI) has been used to study brain structure in newborns, school-aged children, adolescents, and adults with PAE, demonstrating widespread alterations such as reduced total brain volume and alterations to cortical and subcortical regional volumes, cortical thickness, and functional activation (Donald et al., 2015a; Nguyen et al., 2017). White matter appears to be particularly affected by PAE, with volume studies suggesting disproportionate reductions to white matter (Archibald et al., 2001; Jacobson et al., 2017; Nardelli et al., 2011) and diffusion tensor imaging (DTI) studies reporting extensive alterations to microstructure (Donald et al., 2015a; Ghazi Sherbaf et al., 2018; Lebel et al., 2008a). Measures of white matter microstructure, such as fractional anisotropy (FA) and mean, axial and radial diffusivity (MD, AD, RD), reflect properties such as myelination, axon diameter, and/or axon packing density. In small studies of newborns, PAE has been associated with lower AD in transcallosal, projection, and association fibers (Taylor et al., 2016) as well as lower AD in the right superior longitudinal fasciculus (Donald et al., 2015b). Furthermore, altered cerebellar white matter in newborns with PAE has been associated with neurobehavioral outcomes (Donald et al., 2015b). In school-aged children, adolescents and adults with PAE/FASD, lower FA and/or higher MD have been consistently noted throughout the brain (Donald et al., 2015a; Ghazi Sherbaf et al., 2018; Lebel et al., 2008a). Some studies have associated lower FA and/or higher MD with difficulties in processing speed (Fan et al., 2016), reading (Treit et al., 2013), working memory (Wozniak et al., 2009), mathematics (Lebel et al., 2010), and executive functioning (Treit et al., 2017), as well as eyeblink conditioning (Fan et al., 2015). Children with PAE also demonstrate altered development trajectories of white matter, with one study showing steeper decreases in MD in the inferior and superior longitudinal fasciculus and superior fronto-occipital fasciculus from childhood to adolescence (Treit et al., 2013).

There remains a significant gap in the literature on brain abnormalities in young children with PAE, which hinders the development of effective early assessment and intervention (Cook et al., 2015). Early childhood (∼2-7 years) is a period of extensive brain development, with rapid cognitive, behavioural, and social-emotional changes (Deoni et al., 2012; Hermoye et al., 2006; Pfefferbaum et al., 1994), as well as a period when many developmental delays first become apparent (Bitsko et al., 2016; Christensen et al., 2016; Visser et al., 2015). Identifying challenges as early as possible can facilitate early intervention, yet FASD is often not diagnosed until age 7 or older in many clinics (Cook et al., 2015). Here, we aimed to characterize white matter microstructure in young children with PAE using DTI. Based on previous neuroimaging literature in older populations with PAE and/or FASD (Lebel et al., 2008a; Treit et al., 2013), we hypothesized that young children with PAE would demonstrate lower FA and higher MD than unexposed controls across brain white matter tracts.

Materials and Methods

Participants

We recruited 57 children with confirmed PAE through caregiver support groups, early intervention services, and Alberta Children’s Services in Alberta, Canada. Exclusion criteria were birth before 34 weeks’ gestation, children for whom English was not a primary language, history of head trauma, a diagnosis of autism, cerebral palsy, epilepsy or any other medical or genetic disorder associated with serious motor or cognitive disability, and contraindications to MRI (e.g., metal implants, dental braces). Children with attention deficit hyperactivity disorder, learning disabilities, language delays, and/or mental health diagnoses were included, as these frequently co-occur with PAE. None of the children were diagnosed with FASD given that most clinics in Alberta do not assess children for FASD until they are at least 7-years-old. Of the 57 children recruited, 1 child was excluded for an incidental finding on the MRI scan and 2 children did not feel comfortable receiving an MRI scan, leaving 54 children with PAE with usable MRI data, aged 2.49 – 6.97 years (5.21±1.11 years; 27M/27F). The sample included one pair of twins, one pair of non-twin full-siblings, a group of 3 non-twin full-siblings, and 4 pairs of non-twin half-siblings.

Age- and sex-matched unexposed children were selected from an ongoing study of typical brain development (Reynolds et al., 2020; Reynolds et al., 2019). All control participants were born >37 weeks’ gestation, spoke English as a primary language, and had no contraindications to MRI scans as well as had no history of developmental disorders or brain trauma. These unexposed children were aged 2.49-6.97 years (5.21±1.11 years; 27M/27F). Parent/guardian written informed consent and child verbal assent were obtained for each subject. The University of Calgary Conjoint Health Research Ethics Board (CHREB) approved this study (REB14-2266, REB13-020).

Assessment of Prenatal/Postnatal Adverse Exposures

For children with PAE, information pertaining to prenatal and postnatal exposures was obtained from each participant’s child welfare file (which contained information from birth families, social workers, police records, and medical files) and/or from semi-structured interviews with current caregivers, caseworkers, and/or birth families. Prenatal and postnatal profiles were evaluated according to our previously reported framework (Lebel et al., 2019). Among participants with PAE, 31% (n=17) had confirmed PAE greater than or equal to the threshold indicated by the Canadian Guidelines for Diagnosing FASD (Cook et al., 2015): =7 drinks in 1 week and/or 2 or more binge episodes (=4 drinks at one time) during pregnancy; 69% (n=37) of participants had confirmed PAE or a lower or unspecified amount. 94% (51) children with PAE also had prenatal exposure to other substances; 46% (n=25) were exposed to cannabis, 33% (n=18) to tobacco, and 63% (n=34) to illicit substances such as stimulants, methamphetamines, or opioids. 74% (n=40) of participants with PAE had adverse postnatal experiences such as neglect, physical/sexual/emotional abuse, witnessing violence and/or substance use, and/or multiple caregiver transitions. The remaining 26% (n=14) of participants with PAE had no postnatal adverse exposures. The average age of stable placement, after which point there were no more postnatal adverse experiences (as defined above), ranged from 0 to 4.08 years (0.92±1.14 years). Control participants had confirmed absence of PAE and prenatal exposure to other substances based on prospective questionnaires and interviews completed with the mother during pregnancy, no reports of postnatal adversities (i.e., abuse, neglect), and were still residing with their biological parent(s) at the time of their MRI scan.

Neuroimaging Data Acquisition

Children underwent an MRI scan at the Alberta Children’s Hospital on the research-dedicated GE 3T MR750w system with a 32-channel head coil. Children were not sedated for scanning, but families were given reading materials to prepare children at home and offered one or more practice sessions in an MRI simulator (Thieba et al., 2018). Foam padding was used to minimize head motion, and headphones with a projector and screen allowed children to watch a movie throughout the scan. Whole-brain diffusion weighted images were acquired in 4:03 minutes using single shot spin echo echo-planar imaging sequence with: 1.6 x 1.6 x 2.2 mm resolution (resampled to 0.78 x 0.78 x 2.2mm on scanner), TR = 6750 ms; TE = 79 ms, 30 gradient encoding directions at b=750 s/mm2, and 5 interleaved images without diffusion encoding at b=0 s/mm2.

Neuroimaging Data Processing

DTI data was visually inspected for quality, and volumes with artifacts or motion corruption were removed according to our previous methods (Reynolds et al., 2019; Walton et al., 2018). Children with fewer than 18 diffusion weighted volumes and 2 non-diffusion weighted volume were eliminated (Reynolds et al., 2019; Walton et al., 2018). In this sample, unexposed controls had between 19-30 diffusion weighted volumes (mean±SD 28±3) and 3-5 non-diffusion weighted volumes (5±0) remaining while children with PAE had 18-30 diffusion weighted volumes (26±4) and 3-5 non-diffusion weighted volumes (5±1) remaining. There were no significant differences between groups for number of volumes. All data was preprocessed using ExploreDTI (V4.8.6) which involved corrections for signal drift, Gibbs ringing, subject motion, and eddy current distortions (Leemans et al., 2009). Next, semi-automated deterministic streamline tractography was used to delineate 10 major white matter tracts: the corpus callosum (genu, body, splenium), and the fornix as well as the left and right cingulum, pyramidal tract, uncinate fasciculus, superior longitudinal fasciculus (SLF), inferior longitudinal fasciculus (ILF), and inferior fronto-occipital fasciculus (IFOF) (Lebel et al., 2012a; Lebel et al., 2008a; Reynolds et al., 2019). All region of interest semi-automated tractography guides can be found at: https://doi.org/10.6084/m9.figshare.7603271 (Reynolds et al., 2020). The minimum FA threshold was set to 0.20 to initiate and continue tracking, and the angle threshold was set to 30° to minimize spurious fibers (Lebel et al., 2008a; Reynolds et al., 2019). All tracts were manually quality checked and additional exclusion regions were drawn as required to remove spurious fibers. FA, MD, AD, RD, and tract volume values were calculated for every tract, separately for left and right hemisphere where relevant (i.e., all tracts except the corpus callosum and fornix). It is important to note that tract volume obtained using tractography is a measure of the volume of white matter in a fiber bundle that exceeds the chosen FA threshold (0.20) and does not necessarily represent the true white matter volume of the tract (Lebel et al., 2011).

Statistical Analysis

Using SPSS (Version 25), a univariate analysis of covariance (ANCOVA) was used to test for group differences in tract volume (each tract separately); age and sex were included as covariates because they are related to brain structure in early childhood (Reynolds et al., 2019). An ANCOVA was then used to test for group differences in diffusion parameters, FA and MD separately, in each tract while controlling for age, sex, and tract volume. To further investigate tracts showing significant group differences in FA or MD, an ANCOVA was conducted to test for group differences in AD and RD separately while controlling for age, sex, and tract volume. Three supplementary analyses were conducted separately for the tracts with significant FA or MD group differences: the first, to account for motion by adding the number of remaining diffusion-weighted volumes for each dataset as a covariate; the second, to account for prenatal substance exposure by adding cannabis, tobacco, and illicit drug use each as a binary (exposed/unexposed) covariate, and the third to account for postnatal adverse exposures by adding age at stable placement as a covariate. MD, AD, and RD values were scaled by 1000 for analyses to bring them to a similar scale as other measures. False discovery rate (FDR) was used to correct for 48 multiple comparisons for post-hoc testing (3 tract parameters – tract volume, FA, MD – for each of 16 individual tracts), with significance set at q < 0.05.

Results

Fractional anisotropy

Children with PAE had significantly higher FA in the genu and the body of the corpus callosum, the left cingulum, and bilateral pyramidal tracts. In the fornix, children with PAE had significantly lower FA than unexposed controls. All findings, with the exception of the left cingulum, survived FDR correction for multiple comparisons and remained significant after accounting for motion (Table 1, Figure 1).

View this table:
Table 1. Group differences (children with PAE vs. unexposed control) in diffusion measures for individual tracts, controlling for age at scan, sex, and tract volume.
Figure 1.
Figure 1. Group differences in FA.

Children with PAE (purple) had significantly higher FA in genu and the body of the corpus callosum, and the bilateral pyramidal tracts compared to unexposed controls (blue). Children with PAE had significantly lower FA in the fornix compared to controls. Data is represented as mean FA ± 95% confidence interval for FA values for individual tracts. FA values are corrected for the participant’s age, sex, and tract volume. CC Genu = genu of the corpus callosum, CC Body = body of the corpus callosum, CC Splenium = splenium of the corpus callosum, UF = uncinate fasciculus. ***p<0.001, **p<0.01, *p<0.05.

Mean diffusivity

Children with PAE had significantly lower MD in the genu of the corpus callosum and bilateral uncinate fasciculus compared to unexposed controls. All findings survived FDR correction for multiple comparisons and remained significant after accounting for motion (Table 1, Figure 2).

Figure 2.
Figure 2. Group differences in MD.

Children with PAE (purple) had significantly lower MD in the genu of the corpus callosum and the bilateral uncinate fasciculus compared to unexposed controls (blue). Data is represented as mean MD ± 95% confidence interval for MD values for individual tracts. MD values are corrected for the participant’s age, sex, and tract volume. CC Genu = genu of the corpus callosum, CC Body = body of the corpus callosum, CC Splenium = splenium of the corpus callosum, UF = uncinate fasciculus. ***p<0.001, **p<0.01, *p<0.05.

Radial and axial diffusivity

Children with PAE had lower RD in the genu of the corpus callosum (p = 0.001) and the bilateral uncinate fasciculus (left: p = 0.013; right: p = 0.015) compared to unexposed controls. The PAE group showed lower AD in the left (p = 0.034) and the right (p = 0.006) uncinate fasciculus.

Tract volume

Children with PAE had significantly lower tract volume in the corpus callosum (genu, body, and splenium), left cingulum, right SLF, right pyramidal tract, and bilateral IFOF compared to unexposed controls. The only tract with significantly higher volume in the PAE group was the left SLF. Findings in the body and genu of the corpus callosum, bilateral IFOF, and the right SLF survived FDR correction for multiple comparisons (Table 1, Figure 3).

Figure 3.
Figure 3. Group differences in tract volume.

Children with PAE (purple) had significantly lower tract volume compared to unexposed controls in the genu and the body of the corpus callosum, as well as the right and left IFOF, and the right SLF. Data is represented as mean tract volume ± 95% confidence interval for tract volume values for individual tracts. Tract volume values are corrected for the participant’s age and sex. CC Genu = genu of the corpus callosum, CC Body = body of the corpus callosum, CC Splenium = splenium of the corpus callosum, UF = uncinate fasciculus. ***p<0.001, **p<0.01, *p<0.05.

Other Prenatal and Postnatal Adverse Exposures

When accounting for other prenatal substance exposure (cannabis, tobacco, illicit drugs), group differences of FA in the body (p=0.004) and the genu (p=0.005) of the corpus callosum and bilateral pyramidal tracts (right: p=0.001; left: p=0.028) remained significant; the fornix no longer had significant group differences (p=0.67). MD group differences in the genu (p=0.021) of the corpus callosum and the right uncinate fasciculus (p=0.006) remained significant after controlling for other substance use; the left uncinate fasciculus group difference was no longer significant (p=0.19).

All group differences remained significant (p<0.05) after controlling for age at stable placement as a measure for postnatal adversities.

Discussion

Here, we show altered white matter microstructure in young children with PAE for the first time. Higher FA and lower MD were noted in young children with PAE, which differs from previous findings in older children and adolescents (Donald et al., 2015a; Fan et al., 2016; Ghazi Sherbaf et al., 2018; Nguyen et al., 2017; Wozniak et al., 2011), though limited previous research in newborns has shown lower AD (Donald et al., 2015b; Taylor et al., 2016). Throughout childhood, FA increases and MD decreases with age across the brain (Lebel et al., 2011; Lebel et al., 2008b; Reynolds et al., 2019); thus, higher FA and lower MD may reflect premature development of white matter. Because previous studies consistently show lower FA and higher MD in older children and adolescents with PAE (Donald et al., 2015a; Ghazi Sherbaf et al., 2018; Nguyen et al., 2017), it is likely that premature development is then followed by early plateaus in developmental trajectories of white matter.

The corpus callosum facilitates interhemispheric communication (Aboitiz et al., 2003; Grohs et al., 2018) and is especially affected by PAE (Boronat et al., 2017; Yang et al., 2013). Previous research consistently reports higher FA and/or lower MD in the corpus callosum of individuals with PAE/FASD (Ma et al., 2005; Paolozza et al., 2017; Treit et al., 2013; Uban et al., 2017; Wozniak et al., 2009). Some isolated findings align more closely with our results, including lower genu MD (Lebel et al., 2008a) in children with FASD, higher FA in the body of the corpus callosum in boys with PAE (Uban et al., 2017), and lower AD in transcallosal pathways of 11 newborns with PAE (Taylor et al., 2016). The uncinate fasciculus, which connects frontal regions and limbic structures and is implicated in social-emotional processing and memory (Olson et al., 2015), and the pyramidal tracts, projection fibers implicated in motor performance (Jang, 2014; Yeo et al., 2014), also had higher FA in the PAE group. Previous research consistently reports lower FA and/or higher MD in the uncinate fasciculus and corticospinal tracts (Fan et al., 2016; Lebel et al., 2008a; O’Conaill et al., 2015; Paolozza et al., 2017; Treit et al., 2013; Uban et al., 2017) in older children and adolescents, though lower AD was reported in newborns (Taylor et al., 2016). These findings suggest that white matter differences associated with PAE are present across ages but may change directions between early and late childhood.

The only brain region that had lower FA in children with PAE was the fornix, a limbic tract related to memory (Ly et al., 2016). The fornix also undergoes rapid development during early childhood and reaches a developmental plateau earlier than other tracts (Lebel et al., 2012a; Reynolds et al., 2019). Thus, if white matter in children with PAE develops prematurely, the fornix would be the first to reverse from higher to lower FA compared to unexposed controls. The fornix also has high variability in diffusion parameters, in part due to its proximity to the ventricles, which may result in partial volume effects (Lebel et al., 2017). Finally, the FA differences in the fornix did not remain significant after controlling for other prenatal substance exposures, suggesting they may be less robust than the differences in the corpus callosum, uncinate, and pyramidal tracts.

Lower volume was noted across multiple white matter tracts, which aligns with extensive work showing smaller total brain volume (Donald et al., 2015a; Nguyen et al., 2017) and white matter volume (Archibald et al., 2001; Jacobson et al., 2017; Nardelli et al., 2011), related to PAE. Lower tract volume, coupled with higher FA and/or lower MD, may indicate that axons are more tightly packed together within the tract (Beaulieu, 2002). Both tract volume and FA increase with age, though they follow different trajectories (Lebel et al., 2012a; Moura et al., 2016; Reynolds et al., 2019), which may lead to different group profiles in older children with PAE (i.e., lower FA and lower volume) relative to unexposed controls.

This premature brain development suggested by our findings may reflect a compensatory neural mechanism caused by PAE where the brain tries to adapt to a challenging environment by achieving a mature structure sooner rather than following a prolonged development trajectory (Bick et al., 2016; Callaghan et al., 2016; Mehta et al., 2009; Whittle et al., 2013). Interestingly, premature development related to early postnatal adversity (e.g., institutionalization, maltreatment) has been noted most prominently within the limbic system, including the uncinate fasciculus (Gee et al., 2013; Mehta et al., 2009; Merz et al., 2018; Tottenham et al., 2010; Whittle et al., 2013). Deviation from typical brain development can alter windows of plasticity in populations with neurodevelopmental challenges (Fagiolini et al., 2011), and previous research has suggested altered brain plasticity in children with PAE, including earlier peaks for cortical volume (Lebel et al., 2012b) and steeper decreases in MD (Treit et al., 2013). Specific mechanisms that trigger the shift from brain overdevelopment to underdevelopment and alter brain plasticity require further investigation.

This study has several limitations. As with most human studies of PAE, it is challenging to retrospectively obtain accurate and precise information about PAE. We rigorously screened participant records to confirm PAE all participants, but specific details of dose and timing were often unavailable. PAE is rarely the sole adverse exposure (Astley, 2010), and most participants in this study had additional prenatal or postnatal exposures. Most results remained significant after controlling for these additional exposures, but larger samples are necessary to fully disentangle the effects. Lastly, the elimination of diffusion-weighted volumes can result in an overestimation of diffusion parameters (Chen et al., 2015) however there were no significant differences between groups for number of diffusion-weighted volumes remaining. This study was cross-sectional, which limits the conclusions we can draw about developmental trajectories. Future longitudinal studies are necessary to better characterize the development of brain structure in children with PAE.

Conclusions

This study demonstrates higher FA and lower MD in white matter in young children with PAE for the first time. These findings provide novel insight into brain development in early childhood of 2-to 7-year-olds with PAE, possibly suggesting premature development. Understanding the structural underpinnings of neurobehavioral symptoms can support approaches for early diagnoses and indicators for early intervention, for young children with PAE.

Footnotes

  • Data Availability: Neuroimaging data for typically-developing controls is publicly available on the Open Science Framework here: https://osf.io/axz5r/ (Reynolds et al., 2020). Neuroimaging data for children with prenatal alcohol exposure is available upon request from the corresponding author.

  • Funding Source: This was supported by grants from the Canadian Institutes of Health Research (CIHR) (IHD-134090; MOP-136797, the Alberta Children’s Hospital Research Institute and the Kids Brain Health Network. P.K. was supported by an Alberta Children’s Hospital Research Institute Graduate Scholarship, a Queen Elizabeth II Graduate Scholarship and a Harley N. Hotchkiss Graduate Scholarship. J.E.R. was supported by an Eyes High University of Calgary Postdoctoral Scholarship, a T. Chen Fong Fellowship in Medical Imaging Science, and a CIHR postdoctoral fellowship (MFE-164703). M.G. was supported by a Queen Elizabeth II Graduate Scholarship.

  • Conflict of Interest Disclosures: The authors have no conflicts of interest relevant to this article to disclose.

  • Ethics Approval: The University of Calgary Conjoint Health Research Ethics Board (CHREB) approved this study (REB14-2266, REB13-020).

  • Consent: Parent/guardian written informed consent and child verbal assent were obtained for each subject.

References

  1. Aboitiz, F., Montiel, J., 2003. One hundred million years of interhemispheric communication: The history of the corpus callosum. Brazilian Journal of Medical and Biological Research 36, 409–420.
    OpenUrlCrossRefPubMedWeb of Science
  2. ↵
    Archibald, S.L., Fennema-Notestine, C., Gamst, A., Riley, E.P., Mattson, S.N., Jernigan, T.L., 2001. Brain dysmorphology in individuals with severe prenatal alcohol exposure. Developmental Medicine and Child Neurology 43, 148–154.
    OpenUrlCrossRefPubMedWeb of Science
  3. ↵
    Astley, S.J., 2010. Profile of the first 1,400 patients receiving diagnostic evaluations for fetal alcohol spectrum disorder at the Washington State Fetal Alcohol Syndrome Diagnostic & Prevention Network. Journal of Population Therapeutics and Clinical Pharmacology 17, 132–164.
    OpenUrl
  4. ↵
    Beaulieu, C., 2002. The basis of anisotropic water diffusion in the nervous system - A technical review. NMR in Biomedicine, pp. 435–455.
  5. Bick, J., Nelson, C.A., 2016. Early adverse experiences and the developing brain. Neuropsychopharmacology 41, 177–196.
    OpenUrlCrossRefPubMed
  6. ↵
    Bitsko, R.H., Holbrook, J.R., Robinson, L.R., Kaminski, J.W., Ghandour, R., Smith, C., Peacock, G., 2016. Health Care, Family, and Community Factors Associated with Mental, Behavioral, and Developmental Disorders in Early Childhood — United States, 2011–2012. MMWR. Morbidity and Mortality Weekly Report 65, 221–226.
    OpenUrl
  7. ↵
    Boronat, S., Sanchez-Montanez, A., Gomez-Barros, N., Jacas, C., Martinez-Ribot, L., Vazquex, E., Campo, M.d., 2017. Correlation between morphological MRI findings and specific diagnostic categories in fetal alcohol spectrum disorders. European Journal of Medical Genetics 60, 65–71.
    OpenUrl
  8. Callaghan, B.L., Tottenham, N., 2016. Stress Acceleration Hypothesis. Curr Opin Behav Sci 25, 289–313.
    OpenUrl
  9. ↵
    Chen, Y., Tymofiyeva, O., Hess, C.P., Xu, D., 2015. Effects of rejecting diffusion directions on tensor-derived parameters. NeuroImage, pp. 160–170.
  10. ↵
    Christensen, D.L., Bilder, D.A., Zahorodny, W., Pettygrove, S., Durkin, M.S., Fitzgerald, R.T., Rice, C., Kurzius-spencer, M., Baio, J., Yeargin-Allsopp, M., 2016. Prevalence and Characteristics of Autism Spectrum Disorder Among 4-Year-Old Children in the Autism and Developmental Disabilities Monitoring Network. Journal of Developmental Behavior Pediatrics 037, 1–8.
    OpenUrl
  11. ↵
    Cook, J.L., Green, C.R., Lilley, C.M., Anderson, S.M., Baldwin, M.E., Chudley, A.E., Conry, J.L., Leblanc, N., Loock, C.A., Lutke, J., Msw, B.F.M., Mba, A.A.M., 2015. Fetal alcohol spectrum disorder: a guideline for diagnosis across the lifespan. CMAJ: Canadian Medical Association journal = journal de l’Association medicale canadienne, 1–7.
  12. ↵
    Deoni, S.C.L., Dean, D.C., O’Muircheartaigh, J., Dirks, H., Jerskey, B.A., 2012. Investigating white matter development in infancy and early childhood using myelin water faction and relaxation time mapping. NeuroImage 63, 1038–1053.
    OpenUrlCrossRefPubMedWeb of Science
  13. ↵
    Donald, K.A., Eastman, E., Howells, F.M., Adnams, C., Riley, E.P., Woods, R.P., Narr, K.L., Stein, D.J., 2015a. Neuroimaging effects of prenatal alcohol exposure on the developing human brain: A magnetic resonance imaging review. Acta Neuropsychiatrica 27, 251–269.
    OpenUrl
  14. ↵
    Donald, K.A., Roos, A., Fouche, J.-P., Koen, N., Howells, F.M., Woods, R.P., Zar, H.J., Narr, K.L., Stein, D.J., 2015b. A study of the effects of prenatal alcohol exposure on white matter microstructural integrity at birth. Acta Neuropsychiatrica 27, 197–205.
    OpenUrl
  15. Fagiolini, M., Leblanc, J.J., 2011. Autism: A critical period disorder? Neural Plasticity 2011.
  16. ↵
    Fan, J., Jacobson, S.W., Taylor, P.A., Molteno, C.D., Dodge, N.C., Stanton, M.E., Jacobson, J.L., Meintjes, E.M., 2016. White matter deficits mediate effects of prenatal alcohol exposure on cognitive development in childhood. Human Brain Mapping 37, 2943–2958.
    OpenUrl
  17. ↵
    Fan, J., Meintjes, E.M., Molteno, C.D., Spottiswoode, B.S., Dogde, N.C., Alhamud, A., Stanton, M.E., Peterson, B.S., Jacobson, J.L., Jacobson, S.W., 2015. White matter integrity of the cerebellar peduncles as a mediator of effects of prenatal alcohol exposure on eyeblink conditioning. Human Brain Mapping, pp. 2470–2482.
  18. ↵
    Flannigan, K., Unsworth, K., Harding, K., 2018. FASD Prevalence in Special Populations. Canada FASD Research Network, 1–4.
  19. ↵
    Gee, D.G., Gabard-Durnam, L.J., Flannery, J., Goff, B., Humphreys, K.L., Telzer, E.H., 2013. Early developmental emergence of human amygdala – prefrontal connectivity after maternal deprivation. Proceedings of the National Academy of Sciences of the United States of America 110, 15638 – 15643.
    OpenUrlAbstract/FREE Full Text
  20. ↵
    Ghazi Sherbaf, F., Aarabi, M.H., Hosein Yazdi, M., Haghshomar, M., 2018. White matter microstructure in fetal alcohol spectrum disorders: A systematic review of diffusion tensor imaging studies. Human Brain Mapping, 1–20.
  21. ↵
    Goodlett, C.R., Horn, K.H., Zhou, F.C., 2005. Alcohol teratogenesis: mechanisms of damage and strategies for intervention. Experimental biology and medicine (Maywood, N.J.) 230, 394–406.
    OpenUrlCrossRefPubMedWeb of Science
  22. ↵
    Grohs, M.N., Reynolds, J.E., Dewey, D., Lebel, C., 2018. Corpus callosum microstructure is associated with motor function in preschool children. NeuroImage 183, 828–835.
    OpenUrl
  23. ↵
    Hermoye, L., Saint-Martin, C., Cosnard, G., Lee, S.K., Kim, J., Nassogne, M.C., Menten, R., Clapuyt, P., Donohue, P.K., Hua, K., Wakana, S., Jiang, H., Van Zijl, P.C.M., Mori, S., 2006. Pediatric diffusion tensor imaging: Normal database and observation of the white matter maturation in early childhood. NeuroImage 29, 493–504.
    OpenUrlCrossRefPubMedWeb of Science
  24. ↵
    Jacobson, S.W., Jacobson, J.L., Molteno, C.D., Warton, C.M.R., Wintermark, P., Hoyme, H.E., De Jong, G., Taylor, P., Warton, F., Lindinger, N.M., Carter, R.C., Dodge, N.C., Grant, E., Warfield, S.K., Zöllei, L., van der Kouwe, A.J.W., Meintjes, E.M., 2017. Heavy Prenatal Alcohol Exposure is Related to Smaller Corpus Callosum in Newborn MRI Scans. Alcoholism: Clinical and Experimental Research, pp. 965–975.
  25. ↵
    Jang, S.H., 2014. The corticospinal tract from the viewpoint of brain rehabilitation. Journal of Rehabilitation Medicine 46, 193–199.
    OpenUrlCrossRefPubMed
  26. ↵
    Lebel, C., Beaulieu, C., 2011. Longitudinal Development of Human Brain Wiring Continues from Childhood into Adulthood. c, 10937–10947.
  27. ↵
    Lebel, C., Gee, M., Camicioli, R., Wieler, M., Martin, W., Beaulieu, C., 2012a. Diffusion tensor imaging of white matter tract evolution over the lifespan. NeuroImage 60, 340–352.
    OpenUrlCrossRefPubMedWeb of Science
  28. ↵
    Lebel, C., Narr, K.L., Sowell, E.R., Kan, E., Abaryan, Z., Mattson, S.N., Riley, E.P., Jones, K.L., Adnams, C.M., May, P.A., Bookheimer, S.Y., O’Connor, M.J., 2012b. A longitudinal study of the long-term consequences of drinking during pregnancy: Heavy in utero alcohol exposure disrupts the normal processes of brain development. Journal of Neuroscience 32, 15243–15251.
    OpenUrlAbstract/FREE Full Text
  29. ↵
    Lebel, C., Rasmussen, C., Wyper, K., Andrew, G., Beaulieu, C., 2010. Brain microstructure is related to math ability in children with fetal alcohol spectrum disorder. Alcoholism: Clinical and Experimental Research 34, 354–363.
    OpenUrlPubMed
  30. ↵
    Lebel, C., Rasmussen, C., Wyper, K., Walker, L., Andrew, G., Yager, J., Beaulieu, C., 2008a. Brain diffusion abnormalities in children with fetal alcohol spectrum disorder. Alcoholism: Clinical and Experimental Research 32, 1732–1740.
    OpenUrlCrossRefPubMedWeb of Science
  31. ↵
    Lebel, C., Treit, S., Beaulieu, C., 2017. A review of diffusion MRI of typical white matter development from early childhood to young adulthood. NMR in Biomedicine, 1–23.
  32. ↵
    Lebel, C., Walker, L., Leemans, A., Phillips, L., Beaulieu, C., 2008b. Microstructural maturation of the human brain from childhood to adulthood. 40, 1044–1055.
    OpenUrl
  33. ↵
    Lebel, C.A., McMorris, C.A., Kar, P., Ritter, C., Andre, Q., Tortorelli, C., Gibbard, W.B., 2019. Characterizing adverse prenatal and postnatal experiences in children. Birth Defects Research, 1–11.
  34. ↵
    Leemans, A., Jeurissen, B., Sijbers, J., Jones, D., 2009. ExploreDTI: a graphical toolbox for processing, analyzing, and visualizing diffusion MR data. Proceedings 17th Scientific Meeting, International Society for Magnetic Resonance in Medicine 17, 3537.
    OpenUrl
  35. ↵
    Lucas, B.R., Doney, R., Latimer, J., Watkins, R.E., Tsang, T.W., Hawkes, G., Fitzpatrick, J.P., Oscar, J., Carter, M., Elliott, E.J., 2016. Impairment of motor skills in children with fetal alcohol spectrum disorders in remote Australia: The Lililwan Project. Drug and Alcohol Review 35, 719– 727.
    OpenUrl
  36. ↵
    Ly, M., Adluru, N., Destiche, D.J., Lu, S.Y., Oh, J.M., Hoscheidt, S.M., Alexander, A.L., Okonkwo, O.C., Rowley, H.A., Sager, M.A., Johnson, S.C., Bendlin, B.B., 2016. Fornix microstructure and memory performance is associated with altered neural connectivity during episodic recognition. Journal of the International Neuropsychological Society 22, 191–204.
    OpenUrl
  37. ↵
    Ma, X., Coles, C.D., Lynch, M., Laconte, S.M., Hu, X., 2005. Evaluation of Corpus Callosum Anisotropy in Young Adults with Fetal Alcohol Syndrome Using Diffusion Tensor Imaging. Mattson, S.N., Bernes, G.A., Doyle, L.R., 2019. Fetal Alcohol Spectrum Disorders: A Review of the Neurobehavioral Deficits Associated With Prenatal Alcohol Exposure. Alcoholism: Clinical and Experimental Research 43, 1046–1062.
    OpenUrl
  38. ↵
    May, P.A., Amy Baete, M., JaymiRusso, M., Amy J. Elliott, P., Jason Blankenship, P., Wendy O. Kalberg, M. LED, David Buckley, M., Marita Brooks, B., Julie Hasken, M., Omar Abdul-Rahman, M., Margaret P. Adam, M., Luther K. Robinson, M., Melanie Manning, M., and H. Eugene Hoyme, M., May, P.A., Baete, A., Russo, J., Elliott, A.J., Blankenship, J., Kalberg, W.O., Buckley, D., Brooks, M., Hasken, J., Abdul-Rahman, O., Adam, M.P., Robinson, L.K., Manning, M., Hoyme, H.E., 2014. Prevalence and characteristics of fetal alcohol spectrum disorders. Pediatrics 134, 855–866.
    OpenUrlAbstract/FREE Full Text
  39. ↵
    Mehta, M.A., Golembo, N.I., Nosarti, C., Colvert, E., Mota, A., Williams, S.C.R., Rutter, M., Sonuga-Barke, E.J.S., 2009. Amygdala, hippocampal and corpus callosum size following severe early institutional deprivation: the English and Romanian Adoptees study pilot. Journal of child psychology and psychiatry, and allied disciplines 50, 943–951.
    OpenUrlCrossRefPubMedWeb of Science
  40. ↵
    Merz, E.C., Tottenham, N., Noble, K.G., 2018. Socioeconomic Status, Amygdala Volume, and Internalizing Symptoms in Children and Adolescents. J Clin Child Adolesc Psychol 47, 312–323.
    OpenUrlCrossRef
  41. ↵
    Moura, L.M., Kempton, M., Barker, G., Salum, G., Gadelha, A., Pan, P.M., Hoexter, M., Del Aquilla, M.A.G., Picon, F.A., Anés, M., Otaduy, M.C.G., Amaro, E., Rohde, L.A., McGuire, P., Bressan, R.A., Sato, J.R., Jackowski, A.P., 2016. Age-effects in white matter using associated diffusion tensor imaging and magnetization transfer ratio during late childhood and early adolescence. Magnetic Resonance Imaging. Elsevier Inc., pp. 529–534.
  42. ↵
    Nardelli, A., Lebel, C., Rasmussen, C., Andrew, G., Beaulieu, C., 2011. Extensive deep gray matter volume reductions in children and adolescents with fetal alcohol spectrum disorders. Alcoholism: Clinical and Experimental Research 35, 1404–1417.
    OpenUrlCrossRefPubMed
  43. ↵
    Nguyen, V.T., Chong, S., Tieng, Q.M., Mardon, K., Galloway, G.J., Kurniawan, N.D., 2017. Radiological studies of fetal alcohol spectrum disorders in humans and animal models: An updated comprehensive review. Magnetic Resonance Imaging 43, 10–26.
    OpenUrl
  44. ↵
    O’Conaill, C.R., Malisza, K.L., Buss, J.L., Bolster, R.B., Clancy, C., De Gervai, P.D., Chudley, A.E., Longstaffe, S., 2015. Visual search for feature conjunctions: An fMRI study comparing alcohol-related neurodevelopmental disorder (ARND) to ADHD. Journal of Neurodevelopmental Disorders 7, 1–18.
    OpenUrlCrossRef
  45. ↵
    Olson, I.R., Heide, R.J.V.D., Alm, K.H., Vyas, G., 2015. Development of the uncinate fasciculus: Implications for theory and developmental disorders. Developmental Cognitive Neuroscience 14, 50–61.
    OpenUrl
  46. ↵
    Paolozza, A., Treit, S., Beaulieu, C., Reynolds, J.N., 2017. Diffusion tensor imaging of white matter and correlates to eye movement control and psychometric testing in children with prenatal alcohol exposure. Human Brain Mapping 38, 444–456.
    OpenUrl
  47. ↵
    Pei, J., Denys, K., Hughes, J., Rasmussen, C., 2011. Mental health issues in fetal alcohol spectrum disorder. Journal of Mental Health 20, 473–483.
    OpenUrl
  48. ↵
    Pfefferbaum, A., Mathalon, D.H., Sullivan, E.V., Rawles, J.M., Zipursky, R.B., Lim, K.O., 1994. A Quantitative Magnetic Resonance Imaging Study of Changes in Brain Morphology From Infancy to Late Adulthood. JAMA Neurology 51, 874–887.
    OpenUrl
  49. ↵
    Popova, S., Lange, S., Poznyak, V., Chudley, A.E., Shield, K.D., Reynolds, J.N., Murray, M., Rehm, J., 2019. Population-based prevalence of fetal alcohol spectrum disorder in Canada. 1–12.
  50. ↵
    Reynolds, J., Long, X., Dmitrii, P., Bagshawe, M., Dewey, D., Lebel, C., 2020. Calgary Preschool MRI Dataset.
  51. ↵
    Reynolds, J.E., Grohs, M.N., Dewey, D., Lebel, C., 2019. Global and regional white matter development in early childhood. NeuroImage 196, 49–58.
    OpenUrl
  52. ↵
    Taylor, P.A., Jacobson, S.W., van der Kouwe, A., Molteno, C.D., Chen, G., Wintermark, P., Alhamud, A., Jacobson, J.L., Meintjes, E.M., Christopher, D., Chen, G., Wintermark, P., Alhamud, A., Jacobson, J.L., Meintjes, E.M., Imaging, M., Africa, S., Cape, W., Africa, S., Hospital, M.G., Health, M., Africa, S., Core, S.C., Institutes, N., Neurosciences, B., 2016. A DTI-based tractography study of effects on brain structure associated with prenatal alcohol exposure in newborns. Human Brain Mapping 36, 170–186.
    OpenUrl
  53. ↵
    Thieba, C., Frayne, A., Walton, M., Mah, A., Benischek, A., Dewey, D., Lebel, C., 2018. Factors Associated With Successful MRI Scanning in Unsedated Young Children. Frontiers in Pediatrics 6, 6–8.
    OpenUrl
  54. ↵
    Tottenham, N., Hare, T.A., Quinn, B.T., McCarry, T.W., Nurse, M., Gilhooly, T., Millner, A., Galvan, A., Davidson, M.C., Eigsti, I.M., Thomas, K.M., Freed, P.J., Booma, E.S., Gunnar, M.R., Altemus, M., Aronson, J., Casey, B.J., 2010. Prolonged institutional rearing is associated with atypically large amygdala volume and difficulties in emotion regulation. Developmental Science 13, 46–61.
    OpenUrlCrossRefPubMedWeb of Science
  55. ↵
    Treit, S., Chen, Z., Zhou, D., Baugh, L., Rasmussen, C., Andrew, G., Pei, J., Beaulieu, C., 2017. Sexual dimorphism of volume reduction but not cognitive deficit in fetal alcohol spectrum disorders: A combined diffusion tensor imaging, cortical thickness and brain volume study. NeuroImage: Clinical 15, 284–297.
    OpenUrl
  56. ↵
    Treit, S., Lebel, C., Baugh, L., Rasmussen, C., Andrew, G., Beaulieu, C., 2013. Longitudinal MRI Reveals Altered Trajectory of Brain Development during Childhood and Adolescence in Fetal Alcohol Spectrum Disorders. The Journal of Neuroscience 33, 10098–10109.
    OpenUrlAbstract/FREE Full Text
  57. ↵
    Uban, K.A., Herting, M.M., Wozniak, J.R., Sowell, E.R., 2017. Sex differences in associations between white matter microstructure and gonadal hormones in children and adolescents with prenatal alcohol exposure. Psychoneuroendocrinology 83, 111–121.
    OpenUrl
  58. ↵
    Visser, S.N., Holbrook, J.R., Danielson, M.L., Bitsko, R.H., 2015. Diagnostic Experiences of Children With Attention-Deficit/Hyperactivity Disorder. National Health Statistics Reports Number 81.
  59. ↵
    Walton, M., Dewey, D., Lebel, C., 2018. Brain white matter structure and language ability in preschool-aged children. Brain and Language 176, 19–25.
    OpenUrlCrossRefPubMed
  60. ↵
    Whittle, S., Dennison, M., Vijayakumar, N., Simmons, J.G., Yücel, M., Lubman, D.I., Pantelis, C., Allen, N.B., 2013. Childhood maltreatment and psychopathology affect brain development during adolescence. Journal of the American Academy of Child and Adolescent Psychiatry 52.
  61. ↵
    Wilhelm, C.J., Guizzetti, M., 2016. Fetal Alcohol Spectrum Disorders: An Overview from the Glia Perspective. Frontiers in Integrative Neuroscience 9, 1–16.
    OpenUrl
  62. Wozniak, J.R., Muetzel, R.L., 2011. What does diffusion tensor imaging reveal about the brain and cognition in fetal alcohol spectrum disorders? Neuropsychology Review 21, 133–147.
    OpenUrlCrossRefPubMed
  63. ↵
    Wozniak, J.R., Muetzel, R.L., Mueller, B.A., McGee, C.L., Freerks, M.A., Ward, E.E., Nelson, M.L., Chang, P.-N., Lim, K.O., 2009. Microstructural Corpus Callosum Anomalies in Children With Prenatal Alcohol Exposure: An Extension of Previous Diffusion Tensor Imaging Findings. Alcohol Clinical Experimental Research 33, 1825–1835.
    OpenUrlCrossRefPubMed
  64. ↵
    Wyper, K.R., Rasmussen, C.R., 2011. Language Impairments In Children With Fetal Alcohol Spectrum Disorder. J Popul Ther Clin Pharmacol 18, 364–376.
    OpenUrl
  65. ↵
    Yang, Y., Ph, D., Phillips, O.R., Kan, E., Sulik, K.K., Mattson, S.N., Riley, E.P., Jones, K.L., Colleen, M., May, P.A., Connor, M.J.O., Narr, K.L., Sowell, E.R., 2013. Callosal Thickness Reductions relate to Facial Dysmorphology in Fetal Alcohol Spectrum Disorders. 36, 798–806.
    OpenUrl
  66. ↵
    Yeo, S.S., Jang, S.H., Son, S.M., 2014. The different maturation of the corticospinal tract and corticoreticular pathway in normal brain development: diffusion tensor imaging study. Frontiers in Human Neuroscience 8, 1–6.
    OpenUrl
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Posted January 07, 2021.
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White Matter Alterations in Young Children with Prenatal Alcohol Exposure
Preeti Kar, Jess E. Reynolds, Melody N. Grohs, W. Ben Gibbard, Carly McMorris, Christina Tortorelli, Catherine Lebel
bioRxiv 2021.01.05.425489; doi: https://doi.org/10.1101/2021.01.05.425489
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