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. 2023 Sep 30;4(1):11–18. doi: 10.1016/j.bpsgos.2023.09.005

The First “Hit” to the Endocannabinoid System? Associations Between Prenatal Cannabis Exposure and Frontolimbic White Matter Pathways in Children

Julia M Evanski a, Clara G Zundel a, Samantha L Baglot b, Shreya Desai a, Leah C Gowatch a, Samantha L Ely a, Nareen Sadik a, Leslie H Lundahl a, Matthew N Hill b, Hilary A Marusak a,b,c,d,∗
PMCID: PMC10654001  PMID: 38021250

Abstract

Background

Cannabis is the most used federally illicit substance among pregnant people in the United States. However, emerging preclinical data show that a significant portion of cannabis constituents, such as Δ9-tetrahydrocannabinol and its bioactive metabolites, readily cross the placenta and accumulate in the fetal brain, disrupting neurodevelopment. Recent research using the Adolescent Brain Cognitive Development (ABCD) Study cohort has linked prenatal cannabis exposure (PCE) to greater neurobehavioral problems and lower total gray and white matter volume in children. Here, we examined the impact of PCE on frontolimbic white matter pathways that are critical for cognitive- and emotion-related functioning, show a high density of cannabinoid receptors, and are susceptible to cannabis exposure during other periods of rapid neurodevelopment (e.g., adolescence).

Methods

This study included 11,530 children (mean ± SD age = 118.99 ± 7.49 months; 47% female) from the ABCD Study cohort. Linear mixed-effects models were used to examine the effects of caregiver-reported PCE on fractional anisotropy of 10 frontolimbic pathways (5 per hemisphere).

Results

PCE was associated with lower fractional anisotropy of the right (β = −0.005, p < .001) and left (β = −0.003, p = .007) fornix, and these results remained significant after adjusting for a variety of covariates, multiple comparisons, fractional anisotropy of all fibers, and using a quality-control cohort only.

Conclusions

In sum, we demonstrated small, yet reliable, effects of PCE on white matter integrity during childhood, particularly in the fornix, which plays a crucial role in emotion- and memory-related processes. Future studies are needed to understand the impacts of small changes in brain structure or function on neurodevelopment and risk of neurobehavioral problems.

Keywords: Development, Diffusion tensor imaging, Fractional anisotropy, Neuroimaging, Pregnancy, White matter

Cannabis is the most frequently used federally illicit substance among pregnant people in the United States (1). Survey research shows that rates of cannabis use among pregnant individuals more than doubled between 2002 (3.4%) and 2017 (7%), and rates are highest among young people (up to 22%; ages 18–25 years) (2, 3, 4). Many people report using cannabis to combat the negative symptoms associated with pregnancy (e.g., anxiety, nausea/vomiting, and sleep disturbances) (3,4). Individuals report more frequent cannabis use during the first trimester—coinciding with early pregnancy symptoms—compared with the second and third trimesters (5). Furthermore, although symptoms associated with pregnancy can emerge as early as 2 weeks into gestation, many individuals remain unaware of their pregnancy until about 6 weeks (6). The rising popularity of cannabis use accompanied by reduced perceptions of cannabis risk (7) and increased psychoactive Δ9-tetrahydrocannabinol (THC) potency (8) have amplified public health concerns regarding the adverse effects of prenatal cannabis exposure (PCE) on neurodevelopment.

Due to their lipophilic nature, cannabis constituents, such as THC, can easily cross through the placenta and deposit into the fetal brain. Our previous rodent study, using an inhalation model of cannabis during pregnancy, demonstrated that THC and its metabolites accumulate in the placenta, with 30% of circulating THC accumulating in the fetal brain (9). THC binds to cannabinoid type 1 (CB1) receptors, which are expressed in the brain as early as 5 weeks into fetal development (10); therefore, PCE during gestation may impact the developing endocannabinoid (eCB) system. During gestation, CB1 receptors play an initial role in influencing neuronal progenitor cells and axonal growth and then continue to modulate several neuronal processes (e.g., synaptogenesis, myelination) throughout fetal development and into adolescence (11,12).

Importantly, during embryonic development, CB1 receptors exhibit a unique enrichment in white matter tracts, indicating that cannabinoid signaling may be capable of influencing the development of white matter during early developmental stages (13,14). CB1 receptors continue to increase in density from fetal development through childhood and adolescence (15); however, there is a notable developmental shift in the localization of these receptors in both humans and rodents. Indeed, CB1 receptor expression dissipates from white matter tracts to neuronal localization (13,14), where they have the ability to influence synaptic communication in addition to continuing to modulate several neuronal processes, including synaptogenesis and myelination (10,16,17). Consequently, early disruptions to the eCB system, such as by PCE, may have lifelong negative implications for brain development and behavioral health.

Indeed, recent research has linked PCE to several adverse birth and childhood outcomes, including lower birth weight, cardiovascular defects, lower brain volume, alterations in large-scale functional brain networks, and increased risk of neurobehavioral problems, such as attention-deficit/hyperactivity disorder (10,18, 19, 20). For example, one study found that PCE was associated with lower total gray and white matter volumes, as well as greater offspring psychopathology characteristics in 9- to 10-year-old children from the Adolescent Brain Cognitive Development (ABCD) Study cohort (21). In our recent study using the ABCD Study dataset, we found that children with PCE showed lower resting-state functional connectivity between large-scale attentional brain networks (i.e., salience network, ventral attention network) than that observed in unexposed youths (19). Other studies have demonstrated altered neurophysiological functioning, neurocognitive functioning (e.g., visuospatial working memory, response inhibition), and cortical thickness in adolescents and young adults with PCE (22, 23, 24, 25), suggesting that effects of PCE may be evident even decades later, into adulthood.

While these studies reveal concerning alterations in whole-brain measures and large-scale neurocognitive network function following PCE, less is known about the impact on individual white matter pathways. White matter pathways have been implicated in varied neural processes and continue to develop across childhood and adolescence, with specific pathways maturing at different rates (26,27). Frontolimbic pathways, such as the fornix—which connects frontal regions with medial temporal and subcortical structures (e.g., hypothalamus)—show a high density of CB1 receptors and are implicated in emotion- and memory-related processes and mood (26,28). As such, frontolimbic pathways may be particularly sensitive to early exposures, such as PCE.

Previous neuroimaging studies in both adolescents and adults suggest that frontolimbic pathways and regions are susceptible to cannabis exposure during other periods of substantial neurodevelopment, such as adolescence. For example, diffusion magnetic resonance imaging (dMRI) studies show that adults who reported early adolescent cannabis use demonstrated lower fractional anisotropy (FA) of frontolimbic pathways, such as superior and inferior longitudinal fasciculi and the uncinate fasciculus, than those with a later age of onset (29,30). FA, while low in specificity, may reflect a number of different changes in white matter, including myelination, axon density, axon diameter, or permeability (31). Nonetheless, current research suggests that frontolimbic pathways are sensitive to developmental cannabis and cannabinoid exposure. What remains unclear, however, is whether disruptions in frontolimbic development specifically due to cannabis use during pregnancy, are observable in childhood.

To address these gaps, the current study examined the impact of PCE on frontolimbic white matter microstructure in 9- to 10-year-old children from the ABCD Study. Based on previous research, we hypothesized that PCE would be associated with lower integrity of frontolimbic white matter pathways even when controlling for known confounders (e.g., prenatal alcohol, tobacco). In addition, while our main analyses focused on frontolimbic pathways, exploratory analyses examined the effects of PCE on nonfrontolimbic white matter pathways for completeness and to examine the specificity of results.

Methods and Materials

Participants

For the current analysis, data were obtained from the ABCD Data Release 4.0 and included baseline cross-sectional data from 11,530 children from the ABCD Study (mean ± SD age = 118.99 ± 7.49 months; 47% female). Participants were included if they had available PCE (described below) and dMRI data. A manuscript-specific digital object identifier for this study is available at https://doi.org/10.15154/1523155. The parent or guardian (hereafter caregiver) of the participant provided informed consent, and the child gave assent to participate in this study. Local institutional review boards approved the study procedures at each site, and the centralized institutional review board was housed at the University of California, San Diego. More information about the ABCD Study is provided elsewhere (21).

PCE and Potential Covariates

PCE was determined by retrospective report (yes, no) from the caregiver. Caregivers reported on their child’s race (non-White, White), biological sex, age at the time of the study, maternal education, and family income. Caregiver-reported tobacco, alcohol, and other substance use (e.g., cocaine) during pregnancy were collected for inclusion as covariates. Caregivers also reported on lifetime depression of the child’s biological mother (binary covariate). These covariates were selected due to their known relationships with FA (32). Family identification and site identification were measured for use in statistical analyses as nested variables (family within site). Caregiver-reported youth prescription medication use, presence of an alcohol or other substance use problem in either parent, and youth-reported substance use (measured by ever trying alcohol, cocaine, cannabis, or other substances) were included as covariates in secondary analyses to determine robustness of results (see the Supplement).

Imaging Methods

The imaging protocol was standardized across the 21 ABCD Study data collection sites. MRI scanner (3T) platforms were used, including Siemens Prisma, General Electric 750, and Phillips. The harmonized imaging protocol includes resting-state, T1, T2, diffusion-weighted images and task-based functional MRI (21). The dMRI image acquisition used a multiband echo planar imaging sequence with 96 diffusion directions and an acceleration factor of 3 (33). Centralized processing and analysis of MRI data was performed by the ABCD Data Analysis and Informatics Center. Brain microstructure using dMRI was analyzed, and head motion was estimated and corrected by quantifying an average frame-to-frame head movement. AtlasTrack was used to identify and label white matter tracts (33), and FA was computed for each tract in the right and left hemispheres separately. Primary analyses focused on the entire sample of participants. Secondary analyses included only (n = 10,114) participants with dMRI data that passed ABCD quality-control parameters (imgincl_dfmri_include = 1 and imgincl_t1w_include = 1) (see the Supplement).

Primary analyses utilized tabulated dMRI data from the National Institute of Mental Health Data Archive Data Release 4.0. We focused on FA of 10 (5 per hemisphere) frontolimbic white matter pathways: 1) the fornix, 2) cingulum bundle, 3) parahippocampal cingulum bundle, 4) uncinate fasciculus, and 5) inferior-fronto-occipital fasciculus (Figure 1). For completeness and to test for specificity of results to nonfrontolimbic pathways, we examined FA of the 21 nonfrontolimbic white matter tracts derived from AtlasTrack after adjusting for average FA of all tracts (whole brain) provided by AtlasTrack.

Figure 1.

Figure 1

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Frontolimbic white matter tracts of interest.

Statistical Analyses

First, we examined the frequency of children with versus without PCE. Next, linear mixed-effects models were used to test for correlations between PCE and sociodemographic factors, such as age and sex. Then, separate linear mixed-effects models were used to examine the impact of PCE (1 = exposed, 0 = unexposed) as a predictor of FA, with separate models conducted for the 10 separate tracts. False discovery rate (FDR) was used to correct for multiple comparisons (FDR-corrected p < .05). The following covariates were added to test for robustness of results: race/ethnicity; age; sex; maternal depression; parent education; family income; planned pregnancy; premature birth; and prenatal alcohol, tobacco, or other drug (e.g., cocaine) exposure. Random effects of family and site identity were also included. All analyses were performed in RStudio version 2022.12.0+353 using lme4 (34). We report upper and lower 95% CIs as well as p values. To test for robustness of results, we conducted several secondary analyses. First, we included additional covariates that may impact FA: youth prescription medical use, youth substance use, and presence of a parent drug or alcohol problem (see the Supplement). Second, we repeated analyses excluding one participant who had extreme values for FA (>0.9) across several tracts and one participant with an extreme FA value (>0.9) for the left fornix. Third, we repeated our analyses using the subset of participants (n = 10,114) who passed all ABCD quality-control parameters and excluded participants who were on any medications (n = 5365). Notably, the main results remained significant in these secondary analyses (see the Supplement).

For tracts that showed significant associations between FA and PCE, we explored whether these effects were driven by PCE before versus after maternal knowledge of pregnancy. These were modeled as separate factors given the overlap in use before and after knowledge of pregnancy, emulating recent PCE research (19,35). For tracts showing significant associations between FA and PCE, follow-up analyses explored the effects of PCE on transverse diffusivity, longitudinal diffusivity, and mean diffusivity (see the Supplement). Finally, to test for specificity of effects to frontolimbic pathways, we performed exploratory analyses examining the effects of PCE on FA of the 21 nonfrontolimbic pathways derived from AtlasTrack and whether main results remained significant while controlling for average FA of all tracts (frontolimbic and nonfrontolimbic). In addition, we provide exploratory associations between white matter and parent-reported neurobehavioral outcomes in the Supplement.

Results

Prenatal Cannabis Exposure

In this sample, 6.04% of caregivers (n = 697) reported using cannabis during pregnancy. Demographics for the entire sample and separately by PCE groups are reported in Table 1. No significant difference in age or biological sex was observed between exposed and unexposed children. However, there were significant associations between PCE and various sociodemographic factors (see Table 1). Parents using cannabis reported learning of their pregnancy later, at 8.24 weeks on average, than those in the unexposed group (6.84 weeks, p < .001).

Table 1.

Participant Demographics Overall and by PCE

Variable Total, N = 11,530 PCE, n = 697 Unexposed, n = 10,833 Group Comparison
Age in Months, Mean (SD) 118.99 (7.49) 118.50 (7.66) 119.01 (7.49) p = .06
Biological Sex, n
 Female 5507 347 5160 p = .15
 Male 6203 350 5673
Race/Ethnicitya, n
 Non-White 5462 440 5022 p < .001b
 White 6068 257 5811
Week Learned of Their Pregnancy in Weeks, Mean (SD) 6.92 (6.78) 8.24 (7.25) 6.84 (6.74) p < .001b
Parent Level of Education, n
 Less than high school 769 60 709 p < .001b
 High school diploma/GED 1216 133 1083
 Some college 3382 311 3071
 Bachelor’s degree 3258 111 3147
 Postgraduate degree 2888 82 2806
Family Incomea, n
 Low income, <$50,000 3121 358 2763 p < .001b
 Middle income, $50,000–$99,999 2981 168 2813
 High income, >$100,000 4441 108 4333
Prenatal Alcohol Exposure, n
 Prenatal alcohol exposure 2845 418 2427 p < .001b
 No prenatal alcohol exposure 8684 279 8405
Prenatal Tobacco Exposure, n
 Prenatal tobacco exposure 1540 416 1124 p < .001b
 No prenatal tobacco exposure 9988 281 9707
Prenatal Exposure to Other Substances, n
 Prenatal substance exposure 114 65 49 p < .001b
 No prenatal substance exposure 11,353 583 10,770
Maternal Depression, n
 History of maternal depression 2569 282 2287 p < .001b
 No history of maternal depression 8496 359 8137
Premature Birth, n
 Premature birth 2155 110 2045 p = .2465
 Not premature birth 9317 571 8746
Planned Pregnancy, n
 Planned pregnancy 4365 501 3864 p < .001b
 Unplanned pregnancy 7043 168 6875
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GED, general educational development; PCE, prenatal cannabis exposure.

a

Values may not add up to total sample because of missing data or data not reported.

b

p < .001.

Effects of PCE on Frontolimbic White Matter Integrity Without Covariates

Compared with the unexposed group, children with PCE showed lower FA in the following 4 pathways: left fornix (β = −0.004, 95% CI, −0.006 to −0.00193, p < .001) (Figure 2A), right fornix (β = −0.005, 95% CI, −0.00665 to −0.00243, p < .001) (Figure 2B), right parahippocampal cingulum (β = −0.004, 95% CI, −0.00692 to −0.00110, p = .007) (Figure 2C), and left uncinate (β = −0.003, 95% CI, −0.00492 to −0.00024, p = .031) (Figure 2D). PCE was not associated with FA in the other frontolimbic tracts (p > .05).

Figure 2.

Figure 2

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Impact of prenatal cannabis exposure (PCE) on fractional anisotropy (FA) of the (A) left fornix, (B) right fornix, (C) right parahippocampal cingulum, and (D) left uncinate. All results remained significant after adjusting for covariates. Only the left and right fornix remained significant after adjusting for multiple comparisons. Error bars represent standard error. ∗p < .05. Means shown are not adjusted for covariates. Two outliers with extreme values on FA were excluded.

Effects of PCE on Frontolimbic White Matter Integrity With Covariates and Multiple Comparisons Correction

After including covariates, the left fornix (β = −0.003, 95% CI, −0.00586 to −0.00202, p = .007), right fornix (β = −0.005, 95% CI, −0.00767 to −0.0000255, p < .001), right parahippocampal cingulum (β = −0.004, 95% CI, −0.00736 to −0.00026, p = .036), and left uncinate (β = −0.003, 95% CI, −0.00581 to −0.00013, p = .041) remained significantly negatively associated with PCE. However, only the right and left fornix survived FDR correction. Follow-up analyses showed that, for the right fornix, effects of PCE were significant before (β = −0.002, 95% CI, −0.00562 to −0.00026, p = .031) but not after (β = −0.012, 95% CI, −0.03328 to −0.00931, p = .27) knowledge of pregnancy. In contrast, the left fornix effects were significant for PCE after knowledge of pregnancy (β = −0.02567, 95% CI= −0.04620 to −0.00514, p = .014) and not significant for before knowledge (β = −0.00221, 95% CI= −0.00479 to −0.00037, p = .094). After adjusting for covariates, the effects of PCE on the right and left fornix FA were r = −0.04 and r = −0.029, respectively. The right parahippocampal cingulum, right uncinate, and left uncinate did not have specific effects before or after knowledge (ps > .05) of pregnancy.

Effects on Nonfrontolimbic Pathways

To test whether results were specific to frontolimbic pathways, we explored effects of PCE on the 21 other white matter pathways included in AtlasTrack. After adjusting for covariates, 4 of the 21 tracts were significantly negatively associated with PCE: the left inferior frontal superior frontal cortex (IFSFC, frontal aslant tract), the right IFSFC, the left superior longitudinal fasciculus, and the right superior longitudinal fasciculus (see the Supplement). However, only the left and right IFSFC survived FDR correction. In addition, the effects of PCE on FA of the right fornix remained significant when adjusting for FA of all diffusion tensor imaging tract fibers (see the Supplement).

Discussion

In this study, we examined the impact of PCE on the integrity of frontolimbic white matter tracts in a large sample of 9- to 10-year-old children from the ABCD Study. We found that PCE was associated with lower FA of the left fornix, right fornix, right parahippocampal cingulum, and left uncinate. After quality control, adjusting for covariates, and multiple comparisons correction, the association between PCE and reduced FA remained significant only in the right and left fornix. Given the critical role of frontolimbic pathways in emotion, memory, and mood (36, 37, 38), our findings suggest that PCE has observable associations with neurodevelopment a decade following exposure. These findings may be in accordance with the double hit hypothesis, wherein PCE represents the first insult or vulnerability to the eCB system, and a “second hit” or postnatal stressor later in life (i.e., psychosocial stress, environmental stressors) may be needed to reveal neurobehavioral effects of PCE (39,40). Thus, altered microstructure of frontolimbic pathways may contribute to the reported elevated risk of cognitive, behavioral, and social problems reported in youths with PCE (35). Notably, the observed effects of PCE on fornix FA were small, yet reliable. Future studies are needed to understand the impacts of small changes in brain structure or function on neurodevelopment and neuropsychiatric risk.

PCE was associated with lower FA of the fornix, which connects the frontal lobe to the limbic system and is involved in emotion regulation, cognition, and episodic memory recall (41). In children and adolescents, lower FA of the fornix has previously been linked to attention-deficit/hyperactivity disorder, poorer cognitive functioning, and greater externalizing symptoms (35,42,43). Results of the current study suggest that altered frontolimbic white matter pathways may underlie the reported link between PCE and memory, learning, and attention deficits (35,44). Longitudinal associations among PCE, white matter microstructure, and cognitive and behavioral outcomes should be explored in future waves of the ABCD Study.

Interestingly, in our follow-up analyses, we found that the effects of PCE on right fornix FA were specific to PCE before knowledge of pregnancy, whereas effects on the left fornix were specific to PCE after knowledge of pregnancy. The left fornix is thought to carry verbal memory information, and the right fornix is thought to carry visuospatial memory information; therefore, the observed laterality effect may reflect a differential sensitivity of verbal memory, visuospatial memory, and emotion-related processing to PCE that is experienced earlier versus later in gestation, respectively (45). This hypothesis requires further study.

In this sample, caregivers in the PCE group reported finding out that they were pregnant at over 8 weeks, on average, which is after the fetal eCB system is thought to be intact and functional—at around 5 weeks gestation (10). Given the critical role of the eCB system in fetal as well as placental homeostasis, synaptogenesis, and myelination (10,16,17,41,46), it is possible that early gestational exposure can affect the developing eCB system and may have implications for neurodevelopment. Our findings are noteworthy because the fornix is one of the earliest white matter tracts to develop and can be detected in the fetal brain as early as 13 weeks into gestation (44,47,48). By 18 to 20 weeks into gestation, the fornix begins to resemble its adult-like structure (47,49,50). This is especially relevant given the dense expression of CB1 receptors in developing white matter tracts (14). The observed null effects of PCE on other frontolimbic pathways may be due to their later developmental appearance; for example, the inferior fronto-occipital fasciculus appears at around 20 weeks of gestation (47).

Notably, our exploratory analyses indicated that only 2 of the tested 21 nonfrontolimbic pathways (i.e., left and right IFSFC) were associated with PCE after adjusting for covariates and multiple comparisons. This suggests that the previously observed effects of PCE on total white matter volume (35) may be driven by specific pathways and that certain white matter pathways may be more sensitive to the effects of PCE than others. Our analyses suggest that the fornix and the IFSFC may be particularly sensitive to PCE and that these effects are not limited to frontolimbic pathways. The IFSFC is a recently discovered association fiber tract that connects the inferior frontal cortex and superior frontal cortex. While the functional role of the IFSFC remains unclear, a recent systematic review implicates this tract in various functions, including speech and language, working memory, visual-motor activities, and attention (51). Therefore, observed effects of PCE on FA of the IFSFC may contribute to previously reported cognitive alterations in children with PCE (52). Future studies should explore longitudinal associations between white matter integrity and neurobehavioral outcomes, especially as the ABCD Study sample enters adolescence. For instance, rodent studies have found that PCE is associated with deficits in social behavior (53); thus, future preclinical work should investigate the role of alterations in white matter integrity as a contributor to these behavioral effects.

Examining the effects of PCE in a large cohort such as the ABCD Study afforded an ability to detect more precise and reliable effects (54) of PCE on white matter microstructure. Large samples also provide enhanced statistical power to detect small effect sizes of statistical significance, which may limit the real-world relevance of the findings. However, Carey et al. noted that even effects that are perceived as small can have large impacts when scaled to large populations (55). Furthermore, prenatal exposure to substances, such as alcohol, are associated with similar small effect sizes on white matter integrity, ranging from β = −0.01 to −0.03 (our values highlight even smaller effects, ranging from −0.003 to −0.006) (56). However, due to pervasive underreporting of substance use, particularly during pregnancy (57), these estimates may underestimate effects of PCE. Furthermore, a recent multimethod survey of effect sizes within the ABCD Study revealed that effect sizes are much smaller in large, real-world samples (median r = 0.03) than commonly used heuristics established by Cohen (e.g., small effect: r = 0.1), which are likely miscalibrated to effects typically found in psychological research (58). The article by Owens et al. proposed new benchmarks for the ABCD Study; according to these new benchmarks, the observed effects of PCE on fornix FA would approximate the median effect size observed (semipartial rs = 0.028–0.04). For a comparison, Owens et al. suggested that even highly intuitive effects, such as the effects of physical activity on weight, also fall within this effect size range (r = 0.03), suggesting that intuition tends to overestimate effect sizes (58). It is also possible that such small effects can accumulate over time and that larger effects of PCE on neurobehavioral outcomes will emerge longitudinally (58,59). Nonetheless, we observed—according to Cohen’s heuristic—small yet reliable effects of PCE on frontolimbic white matter microstructure in children. Future studies are needed to comprehensively understand the impacts of changes in brain structure or function on neurodevelopment and neuropsychiatric risk.

Strengths of this study include the large sample size (n > 10,000) and the fact that the results were robust to several different approaches and covariate adjustment, such as prenatal exposure to alcohol and tobacco, maternal depression, total brain FA, and MRI image quality. However, several limitations of this study should be noted. PCE was assessed using retrospective caregiver report from nearly a decade ago, which is highly susceptible to reporting bias, and there is a strong likelihood of underreported cannabis usage rates during pregnancy. Not surprisingly, self-reports of cannabis use during pregnancy are known to underestimate toxicology reports (60). Therefore, the observed neurodevelopmental effects may underestimate the effects of PCE. Although several steps were taken to minimize between-site and between-scan platform differences by the ABCD Study team and in our analyses, different MR scanners and manufacturers may still influence results (21). Future studies should incorporate more objective measures, such as regular drug testing during gestation or the collection of maternal and cord blood. In addition, in-depth data were not collected on cannabis use, including potency or route of administration. Subsequent research should explore these use patterns and effects on offspring in greater detail.

Conclusions

In summary, rapidly increasing access to and higher potency of cannabis raises concerns about neurodevelopmental effects on vulnerable populations, such as children. Our results may contribute to recent findings of neurobehavioral alterations in children with PCE to include variation in frontolimbic white matter development, particularly in the fornix, a pathway that is critical for emotional learning and memory. Future studies are needed to increase our understanding of the impacts of changes in brain structure or function on neurodevelopment and risk of neurobehavioral problems.

Acknowledgments and Disclosures

Data used in the preparation of this article were obtained from the Adolescent Brain Cognitive Development (ABCD) Study (https://abcdstudy.org), held in the National Institute of Mental Health Data Archive. This is a multisite, longitudinal study designed to recruit more than 10,000 children ages 9 to 10 years and follow them over 10 years into early adulthood. The ABCD Study is supported by the National Institutes of Health and additional federal partners (Grant Nos. U01DA041048, U01DA050989, U01DA051016, U01DA041022, U01DA051018, U01DA051037, U01DA050987, U01DA041174, U01DA041106, U01DA041117, U01DA041028, U01DA041134, U01DA050988, U01DA051039, U01DA041156, U01DA041025, U01DA041120, U01DA051038, U01DA041148, U01DA041093, U01DA041089, U24DA041123, and U24DA041147).

A full list of supporters is available at https://abcdstudy.org/federal-partners.html. A listing of participating sites and a complete listing of the study investigators can be found at https://abcdstudy.org/consortium_members/. This manuscript reflects the views of the authors and may not reflect the opinions or views of the National Institutes of Health or ABCD consortium investigators.

The ABCD data repository grows and changes over time. The ABCD data used in this report came from https://doi.org/10.15154/1523041.

HAM is supported by National Institute of Mental Health (Grant Nos. K01MH119241 and R01MH132830) and Eunice Kennedy Shriver National Institute of Child Health and Human Development (Grant No. R21HD105882).

JME and HAM conceptualized and designed the project. JME, HAM, and CGZ analyzed and interpreted the data. All authors critically revised the final version of the manuscript. ABCD consortium investigators designed and implemented the study and/or provided data but did not necessarily participate in the analysis or writing of this report.

The authors report no biomedical financial interests or potential conflicts of interest.

Footnotes

Supplementary material cited in this article is available online at https://doi.org/10.1016/j.bpsgos.2023.09.005.

Supplementary Material

Supplement
mmc1.pdf (197.1KB, pdf)
Key Resources Table
mmc2.xlsx (20.6KB, xlsx)

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