Abstract
Importance:
Adverse prenatal exposures (APEs) often co-occur and independently associate with risk for childhood psychopathology. Whether exposure to multiple APEs associates with persistent clinical effects through adolescence or underlying changes in brain maturation remains uncertain.
Objective:
To evaluate longitudinal associations among cumulative APE burden, risk for psychopathology, and age-related cortical thinning in adolescents.
Design, Setting, and Participants:
This cohort study analyzed 4-year follow-up data from the Adolescent Brain Cognitive Development (ABCD) Study, which enrolled 11,868 youth aged 9 to 10 years beginning in 2016. Sibling-comparison analysis was performed on 414 non-adopted sibling pairs with discordant APEs. Statistical analysis occurred from March to September 2025.
Exposures:
Cumulative APE burden was calculated by summing six binary prenatal exposures that independently associated with psychopathology at baseline: unplanned pregnancy; early maternal prenatal alcohol, tobacco, or marijuana use; complicated pregnancy; and complicated birth.
Main Outcomes and Measures:
Outcomes included annual Child Behavior Checklist (CBCL) scores of dimensional psychopathology, using both continuous and thresholded outcomes; and biennial cortical thickness measures from structural magnetic resonance imaging, analyzed using linear mixed-effects models.
Results:
Of 8,515 singleton children (4,055 [47.6%] female; mean [SD] baseline age, 9.9 [0.6] years), 78% were exposed to at least one APE. Multiple APEs persistently and dose-dependently associated with increased odds of clinically significant psychopathology (CBCL total problems: odds ratio=2.01 to 6.75; corrected P=.0065 to 1.31×10−13). Associations of APEs with attention-deficit/hyperactivity disorder symptoms attenuated over time (interaction: F=13.51; corrected P=7.13×10−8), while those with depressive symptoms potentiated (interaction: F=5.82; corrected P=.0019). Greater APE burden associated with accelerated age-related cortical thinning in 36 of 68 cortical regions (interactions: F=3.26 to 8.89; corrected P’s=0.039 to 4.86×10−4). Siblings with more exposures demonstrated persistently higher CBCL total problems (T=2.25; P=0.025) and accelerated cortical thinning (interactions: T=−3.00 to −2.10; P’s<.05) in 5 of the 36 regions implicated in the larger sample.
Conclusions and Relevance:
Multiple prenatal adversities associated with altered developmental trajectories of psychopathology and cortical maturation into mid-adolescence. These findings highlight the importance of fetal programming to mental health across life course, and the need for additional study of risk and resiliency-conferring factors in utero.
INTRODUCTION
Converging evidence from epidemiologic,1 genomic,2 neuroimaging,3 and other translational neuroscience studies4,5 implicates fetal brain development as a sensitive period for risk of subsequent psychopathology, in both childhood and adulthood.1,6 Adverse prenatal exposures (APEs), such as maternal alcohol,7,8 tobacco,9 cannabis use,10,11 medical complications of pregnancy and childbirth12 and unplanned pregnancy13 may disrupt critical neurodevelopmental processes, thereby laying a biological foundation for subsequent vulnerability to psychopathology.14
A small but growing literature also links individual APEs to alterations in adolescent brain development, potentially influencing prenatal programming of psychopathology risk. Cortical thickness typically shows a steady age-associated decrease across adolescence,15 a maturational process thought to reflect synaptic pruning and cortical myelination.16 Exposure to prenatal adversities has been associated with altered cortical thickness in relatively small, cross-sectional studies.3,17,18 In turn, deviations in thinning trajectories—either delayed onset or accelerated decline—have been implicated in heightened risk for psychopathology.3,19
While literature has focused on the associations of individual APEs on specific psychiatric outcomes,7,10,20 prenatal adversities often co-occur, with high cumulative burden strongly associating with neurodevelopment and psychopathology.13 We previously demonstrated a dose-dependent association between cumulative APE burden and elevated baseline psychopathology in childhood.13 However, it remains unclear whether these associations persist across development, particularly during the transition from childhood to adolescence, a period marked by dynamic changes in both brain development and psychiatric symptoms.21 For example, Attention-Deficit/Hyperactivity Disorder (ADHD) symptoms tend to decline during adolescence,22 whereas depressive symptoms tend to increase.23
Previous studies are limited by cross-sectional observations and modest sample sizes, do not control for potential unmeasured confounders, and fail to account for the co-occurrence of multiple APEs. Whether and to what extent exposure to multiple prenatal adversities alters the longitudinal trajectory of brain development and psychopathology remains unexplored. We hypothesized that greater cumulative APE burden would predict persistent psychopathology and accelerated cortical thinning from late childhood through early adolescence. To address this question, we leveraged data from the Adolescent Brain Cognitive Development (ABCD) Study,24 a large, population-based cohort of 11,868 U.S. children with harmonized, repeated assessments of cortical thickness and dimensional psychopathology. Using longitudinal measures collected between ages 9 and 15, we examined whether cumulative APE exposure associated with downstream alterations in psychopathology and cortical maturation trajectories. To further triangulate these findings, we examined whether variation in cortical thickness, in regions sensitive to APE, moderated associations between APEs and clinical outcomes.
METHODS
Study Design and Participants
The present study analyzed data from the ABCD Study (Release 5.1), which enrolled 11,868 participants aged 9 to 10 years at baseline from 21 U.S. sites. Analyses used data from baseline to 4-year follow-up. Non-adopted singleton pregnancies were included (eFigure 1). Detailed cohort characteristics24 are summarized in Table 1. Written informed parental consent and verbal assent from participants were obtained. The ABCD Study was approved by a central institutional review board (IRB) from the University of California, San Diego. This secondary analysis of de-identified ABCD data was exempt from IRB review at Mass General Brigham, Boston, U.S. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines were followed.
Table 1.
Baseline characteristics for study participants stratified by adverse prenatal exposure burden
| Participants, No. (%) | |||||||
|---|---|---|---|---|---|---|---|
| Characteristic | Total (n = 8,515) |
No APE (n = 1,871) |
One APE (n = 2,945) |
Two APEs (n = 2,136) |
Three+ APEs (n = 1,563) |
Statistics | P value |
| Female, No. (%) | 4,055 (47.6%) | 883 (47.2%) | 1,392 (47.3%) | 1,034 (48.4%) | 746 (47.7%) | Χ2 = 0.82 | 0.84 |
| Age, y | 9.9 (0.6) | 9.9 (0.6) | 9.9 (0.6) | 9.9 (0.6) | 9.9 (0.6) | F = 0.3 | 0.83 |
| Pubertal stage | 1.9 (0.7) | 1.8 (0.7) | 1.9 (0.7) | 2.0 (0.7) | 2.1 (0.7) | F = 37.76 | 3.43×10−24 |
| Income-to-needs ratio | 3.6 (2.5) | 4.1 (2.4) | 3.8 (2.6) | 3.5 (2.5) | 2.8 (2.3) | F = 85.61 | 1.81×10−54 |
| Intracranial volume (mm3) | 1,505,490 (158,196) | 1,522,239 (160,011) |
1,507,354 (155,877) |
1,501,502 (158,948) | 1,487,278 (157,276) | F = 14.15 | 3.40×10−9 |
| Surface hole number | 28.1 (12.5) | 27.8 (12.1) | 28.1 (12.7) | 28.3 (12.3) | 28.3 (13) | F = 0.59 | 0.62 |
| Scanner | |||||||
| GE | 4,522 (60.1) | 1,013 (61.1) | 1,550 (59) | 1,145 (60.9) | 814 (60.1) | ||
| PHILIPS | 758 (10.1) | 194 (11.7) | 285 (10.9) | 177 (9.4) | 102 (7.5) | ||
| SIEMENS | 2,216 (29.5) | 446 (26.9) | 782 (29.8) | 555 (29.5) | 433 (32) | Χ2=23.09 | 7.67×10−4 |
| Prenatal exposures | |||||||
| Unplanned pregnancy | 3,379 (39.7%) | 0 | 894 (30.4%) | 1,210 (56.6%) | 1,275 (81.6%) | ||
| Early alcohol exposure | 2,157 (25.3%) | 0 | 527 (17.9%) | 668 (31.3%) | 962 (61.5%) | ||
| Early tobacco exposure | 1,107 (13%) | 0 | 70 (2.4%) | 261 (12.2%) | 776 (49.6%) | ||
| Early marijuana exposure | 501 (5.9%) | 0 | 14 (0.5%) | 56 (2.6%) | 431 (27.6%) | ||
| Complicated pregnancy | 3,424 (40.2%) | 0 | 977 (33.2%) | 1,301 (60.9%) | 1,146 (73.3%) | ||
| Complicated birth | 2,082 (24.5%) | 0 | 463 (15.7%) | 776 (36.3%) | 843 (53.9%) | ||
| Child Behavior Checklist (CBCL) measures at baseline | |||||||
| Anxious/depressed | 53.6 (6.0) | 52.9 (5.6) | 53.2 (5.7) | 53.7 (6.0) | 54.9 (6.7) | F = 38.33 | 1.34×10−24a |
| Withdrawn/depressed | 53.5 (5.8) | 52.7 (4.8) | 53.1 (5.4) | 53.7 (5.9) | 55.1 (6.9) | F = 59.94 | 2.75×10−38a |
| Somatic complaints | 55.0 (6.1) | 53.8 (5.2) | 54.5 (5.7) | 55.5 (6.3) | 56.6 (6.9) | F = 67.74 | 3.92×10−43a |
| Social problems | 52.8 (4.7) | 51.9 (3.7) | 52.2 (4.0) | 53.1 (4.9) | 54.6 (6.0) | F = 123.03 | 2.23×10−77a |
| Thought problems | 53.8 (5.9) | 52.8 (5.0) | 53.2 (5.2) | 54.1 (6.1) | 55.8 (7.1) | F = 90.16 | 3.28×10−57a |
| Attention problems | 53.9 (6.1) | 52.7 (4.9) | 53.2 (5.4) | 54.2 (6.1) | 56.2 (7.8) | F = 115.88 | 4.25×10−73a |
| Rule-breaking behaviors | 52.7 (4.8) | 51.7 (3.6) | 52.1 (4.0) | 53.0 (5.1) | 54.7 (6.3) | F = 137.16 | 4.93×10−86a |
| Aggressive behaviors | 52.8 (5.4) | 51.8 (4.3) | 52.3 (4.7) | 52.9 (5.5) | 54.7 (7.0) | F = 99.03 | 1.11×10−62a |
| Internalizing problems | 48.7 (10.6) | 46.6 (10.1) | 47.7 (10.3) | 49.4 (10.5) | 52.0 (10.9) | F = 90.11 | 3.28×10−57a |
| Externalizing problems | 45.7 (10.2) | 43.2 (9.3) | 44.6 (9.5) | 46.5 (10.2) | 49.8 (11.2) | F = 142.86 | 2.20×10−89a |
| Total problems | 46.0 (11.3) | 42.9 (10.7) | 44.5 (10.8) | 47.1 (11.0) | 50.9 (11.5) | F = 180.08 | 5.63×10−112a |
| Depressive symptoms | 53.6 (5.7) | 52.7 (4.8) | 53.3 (5.4) | 53.9 (5.9) | 55.3 (6.7) | F = 66.41 | 2.51×10−42a |
| Anxiety symptoms | 53.6 (6.2) | 52.9 (5.5) | 53.1 (5.7) | 53.8 (6.3) | 55.0 (7.1) | F = 43.61 | 6.24×10−28a |
| Somatic symptoms | 55.6 (6.7) | 54.4 (5.8) | 55.1 (6.4) | 56.1 (6.9) | 57.2 (7.5) | F = 61.22 | 4.58×10−39a |
| ADHD symptoms | 53.2 (5.6) | 52.1 (4.5) | 52.6 (5.0) | 53.5 (5.7) | 55.2 (7.0) | F = 106.91 | 1.47×10−67a |
| Oppositional defiant symptoms | 53.5 (5.3) | 52.4 (4.3) | 53.0 (4.8) | 53.7 (5.5) | 55.3 (6.6) | F = 95.02 | 3.27×10−60a |
| Conduct symptoms | 52.9 (5.4) | 51.9 (4.2) | 52.2 (4.5) | 53.3 (5.7) | 54.9 (7.0) | F = 120.02 | 1.34×10−75a |
Categorical variables were assessed using Chi-square tests, and quantitative measures using analysis of variance (ANOVA) among adverse prenatal exposure (APE) groups. Quantitative measures are presented as means and standard deviations (SD); categorical variables are presented as counts and percentages. Group differences in Child Behavior Checklist (CBCL) T-scores between adverse prenatal exposure (APE) groups are presented. ADHD, Attention-Deficit/Hyperactivity Disorder. a Significant after false discovery rate (FDR) correction for 17 multiple comparisons.
Adverse Prenatal Exposures
Six APEs from the ABCD Developmental History Questionnaire, reported retrospectively by participants’ parents/caregivers at baseline, were included: (1) unplanned pregnancy; (2) early alcohol, (3) tobacco, or (4) marijuana use before knowing of pregnancy; (5) complicated pregnancy; and (6) complicated birth (eMethods; eTable 1). These APEs were selected based on (1) ≥5% prevalence within the ABCD cohort, and (2) independent associations with baseline Child Behavior Checklist (CBCL) total problems, after controlling for numerous demographic and socioeconomic factors from our previous analyses.13 As before,13 cumulative APE burden was generated by summing these six binary prenatal exposures, and categorized into four groups for analyses (zero, one, two, and three or more APEs).
Dimensional Psychopathology
Psychopathology was assessed annually from baseline to 4-year follow-up using the parent/caregiver-reported CBCL.25 We analyzed 17 items, comprising 8 sub-syndrome scales; 3 broadband composite scores; and 6 DSM-Oriented symptom scales (eTable 1). Higher scores indicate more severe mental health problems, with T scores ≥ 60 for composite scores (≥ 65 for individual symptoms) representing clinically significant psychopathology.25 Raw scores were used in longitudinal analyses, and age- and sex-corrected T scores were used in cross-sectional analyses.
Cortical Thickness
Baseline, Year 2, and Year 4 structural MRI scans were acquired using harmonized protocols.25-27 Minimally processed T1-weighted images were downloaded from the ABCD Data Archive, and preprocessed using FreeSurfer version 7.4 (http://surfer.nmr.mgh.harvard.edu/), including removal of non-brain tissue, intensity normalization, and white matter segmentation. The Desikan-Killiany atlas was used to extract cortical thickness of 68 cortical regions. For quality control, we only included scans with a surface hole number (SHN) < 63, a validated automated metric that reliably excludes poor-quality images in ABCD.28
Statistical Analysis
Longitudinal associations of APE burden with psychopathology and cortical thickness trajectories
Linear mixed-effects models (LMMs) were used to assess associations from APE burden to 17 continuous CBCL measure, covarying for fixed effects of age, sex, pubertal stage, and income-to-needs ratio (INR, a global measure of socioeconomic status; eTable 1); subject ID, family ID, and enrollment site were included as random effects to account for individual, family, and site-level variability. To measure associations of APE burden with odds of clinically significant psychopathology, we used generalized linear mixed-effects models (GLMMs) with binomial error structure and logit link function, substituting binarized CBCL scores (coded as 1 for CBCL composite scores ≥ 60, and other individual measures ≥ 65, and 0 for composite scores below these thresholds) for continuous measures, and adjusting for the fixed and random effects described above. To assess associations of APE with CBCL trajectories, we included an additional APE-by-age interaction term in LMMs.
Similarly, we assessed relationships between APE burden and cortical thickness, as well as cortical thinning trajectories using LMMs. For imaging analyses, age2, intracranial volume, and SHN were included as additional covariates to account for potential non-linear developmental trajectories of cortical thickness and image quality, with scanner manufacturer as an additional random effect to account for inter-scanner variability.
We next tested whether baseline cortical thickness moderated associations between APE burden and age-associated trajectories of CBCL total problems. The analysis was constrained to regions that demonstrated sensitivity to APEs as above, based on the idea that such regions could plausibly influence relationships between prenatal exposures and subsequent psychopathology. LMMs were constructed with three-way interactions among cortical thickness stratified into tertiles based on baseline cortical thickness, APE burden, and age on CBCL total problems scale. All covariates and random effects listed above were included. Of note, we did not assess for mediation of APE burden on CBCL by cortical thickness. Such analyses would be preconditioned on significant associations between cortical thickness and adolescent psychopathology, which are complex and heterogenous in terms of direction of effect and temporospatial specificity.29
To assess the robustness of our findings, sensitivity analyses were conducted with additional adjustment for race/ethnicity, the presence or absence of a partner for the primary caregiver, caregiver education, maternal age at birth, neighborhood safety, presence or absence of an older sibling, parental mental health, and baseline CBCL scores (eTable 1).13 To assess the inclusion of lower quality scans, analyses were performed using iteratively higher image quality control thresholds (SHN<37 and SHN<30).28 The potential impact of missing data in prenatal exposures was examined via multiple imputation by chained equations with 200 iterations (eMethods). Additionally, sex-specific associations of APE burden with psychopathology and cortical thickness trajectories were explored (eMethods). To identify individual APEs contributing to associations observed in cumulative APE burden models, LMMs were conducted to evaluate associations from individual APEs to CBCL scores and cortical thickness, along with their age-associated trajectories (eMethods).
Sibling-pair validation: associations of discordant APE with psychopathology and cortical development
To control for unmeasured familial confounders,28,30,31 we conducted secondary analyses using sibling pairs discordant for APE burden. Within each pair, the sibling with higher exposure was designated as the more-exposed group (coded as 1), and the sibling with lower exposure as the less-exposed group (coded as 0). LMMs were implemented to assess whether effect sizes of APE burden on CBCL scores and cortical thickness, and their age-associated developmental trajectories remained consistent, adjusting for the same covariates and random effects as above. As the sample size in the sibling analysis was considerably smaller (total N=828), this analysis was constrained to CBCL scores and brain regions that were statistically significant in the full sample. We focused primarily on the consistency of effect sizes between the full and sibling samples, setting p<.05 uncorrected for multiple comparisons. Further, LMMs were used to evaluate the magnitude of APE burden differences between sibling pairs using continuous discordance measure derived by subtracting the pairwise mean APE burden for each sibling pair (eMethods).
For all analyses, unless otherwise stated, quantitative measures were scaled. Standardized coefficients (β) and associated two-tailed p-values from each model were reported for continuous outcomes, and adjusted odds ratios (ORs) for binary variables. Analysis of variance (ANOVA) was used to evaluate overall associations between APE burden and psychopathology and cortical thickness, as well as the overall APE-by-age interactions. False discovery rate (FDR) of 0.05 was used to declare significant findings across 17 CBCL scores and 68 cortical thickness comparisons (eMethods). Analyses were conducted in R (version 4.4.0) with lme4, lmerTest, and mice packages.
RESULTS
Characteristics of APE in Children
Of 8,515 singleton children with complete data on the six APEs (4,055 females [47.6%]; mean [SD] age, 9.9 [0.6] years at baseline; eFigure 1), 6,644 (78%) had at least one APE (Figure 1A). Table 1 summarizes baseline characteristics of participants, stratified by cumulative APE burden. Children exposed to more APEs exhibited earlier pubertal development, more severe psychopathology, and greater socioeconomic disadvantage. High cumulative APE burden was associated with increased psychopathology (Figure 1B).
Figure 1. Distribution and co-occurrence of adverse prenatal exposures.
(A) Distribution of six adverse prenatal exposures (APEs), including complicated pregnancy, unplanned pregnancy, complicated birth, early alcohol, tobacco, and marijuana use before knowing of pregnancy. Participants were categorized into four groups based on the number of APEs: zero APE, one APE, two APEs, and three or more (three+) APEs. Individual APEs with sample sizes exceeding 100 are labeled within each APE group, where darker color indicates higher APE burden. (B) Co-occurrence patterns of APEs (bottom), with co-occurring exposures vertically aligned and connected by dots and lines. The corresponding mean Child Behavior Checklist (CBCL) total problems at Baseline, Year 1, Year 2, Year 3, and Year 4 follow-up are displayed for each exposure combination, ordered by mean baseline CBCL scores, with the number of participants labeled as text. Error bars represent standard errors. The mean baseline CBCL score for the unexposed APE group is indicated by a black dotted line.
Associations of APE Burden with Clinical Trajectories
From baseline to 4-year follow-up, children with greater APE burden exhibited higher CBCL total problems (eTable 2). Although scores declined over time across all APE groups, the stratification by APE burden remained stable (Figure 2A). In adjusted GLMMs, cumulative APE burden was associated with clinically significant CBCL total problem scores (χ2=69.72; PFDR<.001; Figure 2B). Specifically, compared with unexposed children, sequentially stronger associations were observed for exposure to one APE (OR, 2.01; 95% CI, 1.28–3.16; PFDR = .0065), two APEs (OR, 3.82; 95% CI, 2.39–6.11; PFDR<.001), and three or more APEs (OR, 6.75; 95% CI, 4.14–11.02; PFDR<.001), demonstrating a dose-dependent pattern. Results for other binarized CBCL scores are presented in eFigure 2 and eTable 3.
Figure 2. Associations between adverse prenatal exposure (APE) burden and risk of psychopathology and their developmental trajectories.
(A) Longitudinal trajectories of Child Behavior Checklist (CBCL) total problems from baseline to 4-year follow-up, stratified by cumulative number of APEs. From baseline to 4-year follow-up, children exposed to more prenatal adversities persistently exhibited significantly higher CBCL total problems at each time point (*, PFDR’s <.001; eTable 2), which declined across all APE groups over time, but their stratification by APE burden remained stable. (B) Adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for clinically significant psychopathology across cumulative APE levels (one APE, two APEs, three or more [three+] APEs) compared with the unexposed group, adjusting for age, sex, pubertal stage, socioeconomic status, and random effects for subject ID, family ID, and site effects. The black squares and horizontal lines represent ORs and 95% CIs. (C) Effects of APE burden from main effect models (upper panel) and age-by-APE interaction effects from interaction models (lower panel) across APE groups on CBCL scores. Heatmaps illustrate F statistics for overall effects, and T statistics for pairwise comparisons versus the unexposed group. Significant group differences were observed for all CBCL scores across APE groups, with notably altered age-associated trajectories in children exposed to multiple APEs. Asterisks indicate statistical significance (*, P < .05; **, P < .01; ***, P < .001; FDR corrected for 17 comparisons). (D) Estimated means (lines) with 95% CIs for age-associated trajectories of CBCL total problems, depressive symptoms, and Attention-Deficit/Hyperactivity Disorder (ADHD) symptoms stratified by APE burden. Note that while stratification of ADHD symptoms by APE burden decreased over time (APE x age interaction: F=13.51, PFDR=7.13×10−8), stratification of depressive symptoms by APE burden increased over time (interaction: F=5.82, PFDR=.0019), driven in both cases by changes in the most exposed (3+) group.
We next examined associations between APE burden and continuous CBCL scores, as well as APE-by-age interactions on their developmental trajectories. In adjusted LMMs, children with greater APE burden had significantly higher CBCL scores across all domains compared with unexposed children (main effects of APE burden: β=0.06–0.58; T value=2.27–17.63; PFDR<0.05; Figure 2C; eTable 4). In models with additional APE-by-age interaction terms, significant interactions were observed for 11 of 17 CBCL scores, suggesting that greater APE burden altered age-associated symptom trajectories (Figure 2C; eTable 5). For example, greater APE burden was associated with a steeper age-associated decline in CBCL total problems (interaction: F=5.51; PFDR=.0023) and ADHD symptoms (interaction: F=13.51; PFDR<.001); associations with ADHD symptoms were particularly pronounced in children exposed to three or more APEs (interaction: β=−0.067; T value=−5.75; PFDR<.001), resulting in a narrowing of the symptom gap with unexposed children over time. In contrast, greater APE burden was associated with age-associated increases in DSM-oriented depression symptoms over time (interaction: F=5.82; PFDR=.0019), again most evident in three or more APE groups (interaction: β=0.051; T value=3.54; PFDR=.0014; Figure 2D).
Associations of APE Burden with Altered Cortical Development
Association between APE burden and cortical thickness were largely unremarkable, with only one region, the right paracentral cortex, showing significantly decreased thickness in children with APE compared to unexposed children (F=5.96; PFDR=.032; eFigure 3-4; eTable 6). However, significant APE-by-age interactions were identified in 36 of 68 cortical regions (β=−0.085 to −0.034; F=3.26 to 8.89; PFDR<.05; Figure 3A; eTable 7), indicating APE-associated acceleration of cortical thinning across development. To further assess dose-dependence, when compared with unexposed children, significant APE-by-age interactions were identified in 0, 19, and 46 cortical regions among children exposed to one, two, and three or more APEs, respectively. The most prominent effects were observed in right middle temporal cortex (β=−0.078 for three or more APEs; F=8.89; PFDR<.001, Figure 3B).
Figure 3. Longitudinal associations of adverse prenatal exposure (APE) burden on cortical thinning.
(A) Of 68 regions, 36 regions exhibited significant APE-by-age interaction effects on cortical thickness (*, PFDR’s <.05, FDR corrected for 68 comparisons). Specifically, compared with unexposed children, significant APE-by-age interactions were identified in 0, 19, and 46 cortical regions among children exposed to one, two, and three or more APEs, respectively. F statistics are shown for overall interaction effects (purple colors), and T statistics are illustrated for pairwise comparison between each APE and no APE group (blue/orange colors). (B) Mean and standard error of z-scored cortical thickness in the right middle temporal cortex, and right paracentral cortex across APE burden groups at baseline, Year 2, Year 4 follow-up (upper panel). APE-by-age interactions on cortical thickness in the above regions, with y-axis representing residualized cortical thickness after adjusting for age2, pubertal stage, intracranial volume, surface hole number, socioeconomic status, and random effects of scanner, subject ID, family ID, and site. Significant APE-by-age interactions showed that higher APE burden is associated with accelerated cortical thinning. Cortical regions with significant interactions included right middle temporal, right inferior parietal, left rostral middle frontal, left supramarginal, left inferior temporal, right lateral occipital, left inferior parietal, right fusiform, right paracentral, right superior temporal, right precentral, left fusiform, left precuneus, right precuneus, left pars triangularis, left middle temporal, left paracentral lobule, right rostral middle frontal, right inferior temporal, right supramarginal gyrus, right pars orbitalis, right lingual, left pars opercularis, right cuneus, left medial orbitofrontal, right banks of the superior temporal sulcus, left banks of the superior temporal sulcus, left precentral, right frontal pole, left cuneus, right superior parietal, left temporal pole, left superior temporal, left lateral occipital, right superior frontal, left parahippocampal, left isthmus cingulate, right pars opercularis, left superior parietal, right parahippocampal, left caudal middle frontal, right posterior cingulate, right transverse temporal, left postcentral, right pericalcarine, and right pars triangularis cortices. L, left; R, right.
We next examined whether cortical thickness moderated associations between APE group and age-associated trajectories of CBCL total problems by stratifying cortical thickness into tertiles. Of 36 regions examined, nominally significant moderation associations were identified in four regions (eTable 8), particularly the left precentral cortex (β=0.13 for three or more APEs at high cortical thickness; F=2.90; uncorrected P=.008). Specifically, children with the thickest cortex at baseline and high APE burden exhibited persistently elevated psychopathology symptoms across adolescence (eFigure 5).
Main results for psychopathology and cortical thickness were largely consistent after adjustment for additional sociodemographic covariates (eFigures 6-7; eTables 9-12), parental mental health (eFigures 8-9; eTables 13-16), and baseline CBCL scores (eFigure 10; eTables 17-18); they also remained significant across different SHN thresholds (SHN<37 and SHN<30; eFigure 11; eTables 19-20),28 and in imputation datasets (eFigures 12-13; eTables 21-24). No sex-specific associations were observed between APE burden and trajectories of psychopathology and cortical thickness (eFigures 14-15; eTables 25-26). Associations of individual APEs with CBCL scores and cortical thickness, along with APE-by-age interactions, are presented in eFigures 16-19 and eTables 27-30.
Sibling-pair validation
To control for unmeasured familial confounds, we conducted analyses using 414 sibling pairs discordant for APE burden (eTable 31). More-exposed siblings exhibited higher CBCL total problems across development (β=0.11; T=2.25; P=.025; Figure 4A; eFigure 20; eTable 32). For CBCL scores, 9 of the 11 (82%) significant APE-by-age interactions identified in the main analyses demonstrated consistent directions of interaction effects in CBCL trajectories in sibling comparisons (Figure 4B; eTable 33). Specifically, more-exposed siblings had more externalizing problems (β=0.13; T=2.41; P=.017) but the gap diminished over time, whereas an increase in depressive symptoms (β=0.13; T=2.59; P=.010) in the more-exposed siblings became more pronounced over time (Figure 4C). Similarly, 34 of 36 (94%) significant interactions on cortical thickness in the main analyses were replicated in sibling comparisons (Figure 4D; eTable 34), with five significant regions (β=−0.093 to −0.067; T=−2.10 to −3.00; P=.0028 to .036; Figure 4E), where more-exposed siblings showing significantly accelerated cortical thinning. These findings were also observed in sibling-pair analyses examining the magnitude of APE burden differences (eFigures 21-22; eTables 35-37).
Figure 4. Sibling-pair validation of associations between adverse prenatal exposure (APE), cortical thickness and psychopathology development.
(A) Longitudinal trajectories of Child Behavior Checklist (CBCL) total problems in 414 matched sibling pairs discordant for APE burden from baseline to 4-year follow-up. More-exposed siblings persistently showed elevated CBCL total problems across development compared with their less-exposed siblings (β=0.11; T = 2.25; P = .025). (B) Concordance of APE-by-age interaction effects on CBCL trajectories between the main analyses and sibling comparisons. Among 11 CBCL measures with significant interaction effects for three or more APE groups in the main analysis, 9 (82%) showed consistent direction of interaction effects in the sibling analyses. (C) More-exposed siblings had more externalizing problems (β=0.13; T=2.41; P=.017) but the gap diminished over time, whereas an increase in depressive symptoms (β=0.13; T=2.59; P=.010) in the more-exposed siblings became more pronounced over time. (D) Concordance of APE-by-age interaction effects on cortical thickness thinning between the main analyses and sibling comparisons. Of 36 cortical regions with significant APE-by-age interactions for three or more APE groups in the main analyses, 34 (94%) showed consistent direction of interaction effects in the within-sibling comparisons. Red dots indicated regions with discordant direction of interaction effects. (E) Five significant regions of cortical thickness in observed sibling comparison analyses (β=−0.093 to −0.067; T=−2.10 to −3.00; P=.0028 to .036), all of which were also significant in the full sample. Figures indicate distribution (mean and standard deviation) and age-associated decline of two representative regions, the right middle temporal cortex and right paracentral cortex. More-exposed siblings exhibited accelerated age-associated cortical thinning compared with less-exposed siblings (compare to Figure 3B).
DISCUSSION
The present study demonstrates that exposure to multiple prenatal adversities associates with a dose-dependent risk for clinically significant psychopathology that persists into mid-adolescence, as well as with altered trajectories of cortical development. These findings arise from one of the largest available prospective, longitudinal adolescent neurodevelopmental cohort studies; were robust to adjustment for biological, design-related, and socioeconomic factors; and were validated in sibling pairs with discordant APEs, thus accounting for unmeasured familial confounders. The strength of these clinical associations, their persistence over time, and dose-dependence provide convergent support for the importance of fetal life in risk for childhood psychopathology.
While previous studies have primarily focused on isolated prenatal exposures,7,10,11 the present findings build upon our previous association of APE burden with dose-dependent increases in psychopathology risk at baseline (age 9-10) in the ABCD Study.13 When following the same participants through age 15, group differences diminished over time for externalizing problems, but intensified for depressive symptoms among children with multiple APEs. This pattern echoes findings that externalizing disorders (e.g., ADHD) typically emerge in early to mid-childhood, while the incidence of depression rises during adolescence,32 highlighting the importance of disorder-specific sensitive periods for assessment, prevention and early intervention.
This study extends previous work associating altered cortical thickness with individual exposures to prenatal alcohol,18 tobacco33 use, and gestational diabetes.12 Many brain regions exhibited significant APE-by-age interactions, highlighting the long-lasting impact of prenatal adversity on cortical maturation. Importantly, these interactions emerged only among children exposed to ≥two APEs, emphasizing the importance of integrating co-occurring prenatal adversities into such analyses.13 Notably, accelerated cortical thinning was predominantly located in the middle temporal cortex, and rostral middle frontal cortex, implicated in attentional control, memory processing, and visual perception.34,35
Additionally, cortical thickness in the precentral cortex may moderate the influence of prenatal exposures on age-related psychopathology trajectories. Notably, individuals with high APE burden and thicker baseline cortex had elevated psychopathology across development. While this result may seem counterintuitive, it is important to note that the direction of these associations may change over development. In many cortical regions, APE burden associated not only with steeper thinning but also with baseline thicker cortex (eFigure 4). These results parallel a previous study of cortical development in autism that demonstrated relatively thicker cortical thickness in younger children followed by more rapid thinning during adolescence.36
Several limitations should be considered when interpreting our findings. First, the ABCD study includes families with higher socioeconomic status compared to the US as a whole,37 limiting generalizability to populations with socioeconomic adversity. However, findings were robust to the inclusion of socioeconomic measures, suggesting their broader relevance. Retrospective and potentially imprecise self-reporting of prenatal exposures from parents may introduce bias,13 such as commonly underreported substance use,38 and both over- and underestimated unplanned pregnancy,39 although underreporting would potentially attenuate associations toward the null hypothesis. Future studies (e.g., HEALthy Brain and Child Development Study)40 may provide more accurate measurements of APE burden and its association with psychopathology and brain development before age 9, as well as more precise timing of prenatal substance use and its downstream effects.10 Individual APEs may have heterogeneous associations with psychopathology and brain development; future studies may explore weighted or dimensional approaches to better capture the joint effects of APEs. Finally, the sample size in the sibling-pair validation was relatively small, limiting statistical power; however, the direction of effects was largely consistent with the primary findings, suggesting their robustness.
In summary, this study demonstrates clear and persistent impacts of multiple APEs on psychopathology and cortical development through mid-adolescence. These findings underscore the importance of the prenatal environment to cortical maturation and psychopathology risk, and the need to develop early interventions, perhaps as early as prenatally, to mitigate such risk.
Supplementary Material
Key Points.
Question:
Is adverse prenatal exposure (APE) burden associated with long-term risk for psychopathology and altered cortical maturation trajectories in adolescents?
Findings:
In this 4-year follow-up cohort study of 8,515 singleton children in the ABCD Study, exposure to multiple APEs associated with persistent, dose-dependent increases in the risk of clinically significant psychopathology and diffuse acceleration in age-associated cortical thinning during adolescence. Findings were further supported by within-family comparisons in 414 sibling pairs discordant for APEs.
Meaning:
These findings emphasize the need for early identification, longitudinal monitoring, and neurodevelopmentally informed prevention strategies for at-risk youth.
Acknowledgments
JLR is supported by R01MH124694. JMG is supported by K02DA052684 and R01DA051540. SEH is supported by R01DA057566 and K18DA059913. The ABCD study is supported by the National Institutes of Health (NIH) and additional federal partners under award numbers U01DA041048, U01DA050989, U01DA051016, U01DA041022, U01DA051018, U01DA051037, U01DA050987, U01DA041174, U01DA041106, U01DA041117, U01DA041028, U01DA041134, U01DA050988, U01DA051039, U01DA041156, U01DA041025, U01DA041120, U01DA051038, U01DA041148, U01DA041093, U01DA041089, U24DA041123, U24DA041147. Additional support for this work was made possible from NIEHS R01-ES032295 and R01-ES031074. A full list of supporters is available online. A list of participating sites and a complete list of the study investigators can be found online. ABCD consortium investigators designed and implemented the study and provided data but did not necessarily participate in analysis or writing of this report. This manuscript reflects the views of the authors and does not reflect the opinions or views of the NIH or ABCD consortium investigators. The ABCD data repository grows and changes over time. The ABCD data used in this report came from http://dx.doi.org/10.15154/z563-zd24. Dr. Dongmei Zhi had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Role of the Funder/Sponsor
The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Footnotes
Declaration of Interests
All other authors have no interests to declare.
Data Sharing
The Adolescent Brain Cognitive Development data used in this report are available from the NIMH Data Achieve (https://nda.nih.gov) to Authorized Users.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The Adolescent Brain Cognitive Development data used in this report are available from the NIMH Data Achieve (https://nda.nih.gov) to Authorized Users.