key: cord-1021455-ju36749f
authors: Triplett, Regina L.; Lean, Rachel E.; Parikh, Amisha; Miller, J. Philip; Alexopoulos, Dimitrios; Kaplan, Sydney; Meyer, Dominique; Adamson, Christopher; Smyser, Tara A.; Rogers, Cynthia E.; Barch, Deanna M.; Warner, Barbara; Luby, Joan L.; Smyser, Christopher D.
title: Association of Prenatal Exposure to Early-Life Adversity With Neonatal Brain Volumes at Birth
date: 2022-04-12
journal: JAMA Netw Open
DOI: 10.1001/jamanetworkopen.2022.7045
sha: 689d505942a9fdf6a8825157cf61c360657722e7
doc_id: 1021455
cord_uid: ju36749f

IMPORTANCE: Exposure to early-life adversity alters the structural development of key brain regions underlying neurodevelopmental impairments. The association between prenatal exposure to adversity and brain structure at birth remains poorly understood. OBJECTIVE: To examine whether prenatal exposure to maternal social disadvantage and psychosocial stress is associated with neonatal global and regional brain volumes and cortical folding. DESIGN, SETTING, AND PARTICIPANTS: This prospective, longitudinal cohort study included 399 mother-infant dyads of sociodemographically diverse mothers recruited in the first or early second trimester of pregnancy and their infants, who underwent brain magnetic resonance imaging in the first weeks of life. Mothers were recruited from local obstetric clinics in St Louis, Missouri from September 1, 2017, to February 28, 2020. EXPOSURES: Maternal social disadvantage and psychosocial stress in pregnancy. MAIN OUTCOMES AND MEASURES: Confirmatory factor analyses were used to create latent constructs of maternal social disadvantage (income-to-needs ratio, Area Deprivation Index, Healthy Eating Index, educational level, and insurance status) and psychosocial stress (Perceived Stress Scale, Edinburgh Postnatal Depression Scale, Everyday Discrimination Scale, and Stress and Adversity Inventory). Neonatal cortical and subcortical gray matter, white matter, cerebellum, hippocampus, and amygdala volumes were generated using semiautomated, age-specific, segmentation pipelines. RESULTS: A total of 280 mothers (mean [SD] age, 29.1 [5.3] years; 170 [60.7%] Black or African American, 100 [35.7%] White, and 10 [3.6%] other race or ethnicity) and their healthy, term-born infants (149 [53.2%] male; mean [SD] infant gestational age, 38.6 [1.0] weeks) were included in the analysis. After covariate adjustment and multiple comparisons correction, greater social disadvantage was associated with reduced cortical gray matter (unstandardized β = −2.0; 95% CI, −3.5 to −0.5; P = .01), subcortical gray matter (unstandardized β = −0.4; 95% CI, −0.7 to −0.2; P = .003), and white matter (unstandardized β = −5.5; 95% CI, −7.8 to −3.3; P < .001) volumes and cortical folding (unstandardized β = −0.03; 95% CI, −0.04 to −0.01; P < .001). Psychosocial stress showed no association with brain metrics. Although social disadvantage accounted for an additional 2.3% of the variance of the left hippocampus (unstandardized β = −0.03; 95% CI, −0.05 to −0.01), 2.3% of the right hippocampus (unstandardized β = −0.03; 95% CI, −0.05 to −0.01), 3.1% of the left amygdala (unstandardized β = −0.02; 95% CI, −0.03 to −0.01), and 2.9% of the right amygdala (unstandardized β = −0.02; 95% CI, −0.03 to −0.01), no regional effects were found after accounting for total brain volume. CONCLUSIONS AND RELEVANCE: In this baseline assessment of an ongoing cohort study, prenatal social disadvantage was associated with global reductions in brain volumes and cortical folding at birth. No regional specificity for the hippocampus or amygdala was detected. Results highlight that associations between poverty and brain development begin in utero and are evident early in life. These findings emphasize that preventive interventions that support fetal brain development should address parental socioeconomic hardships.

Health insurance status (private, public/no insurance) and highest educational level were obtained at study entry (during the first trimester). Household income and composition were obtained in each of the three trimesters and generated the Income to Needs Ratio (I/R). 1 An I/R of 1.0 is equivalent to the federal poverty line. Home addresses were obtained at birth and used to calculate the national Area Deprivation Index (ADI) percentile. The ADI scores neighborhood disadvantage using US Census data regarding poverty, education, housing, and employment, with higher values indicating greater disadvantage. 2 The Diet History Questionnaire II (DHQ-II), 3 was obtained at the time of neonatal scan. The DHQ-II is a yearly food frequency measure used to characterize nutrition via the Healthy Eating Index (HEI). 4

Perceived Stress Scale (PSS) 5 and the Edinburgh Postnatal Depression Scale (EPDS) 6 were collected in each trimester. The Stress and Adversity Inventory (STRAIN) 7 is a composite measure of stressful and traumatic life experiences that was obtained at time of neonatal scan (n=186) or at follow-up at one or two years (n=77). On post-hoc analyses, we did not find differences in the STRAIN stressful/traumatic life event count (t-statistic=.85, two-tailed p=0. 4) or severity (t-statistic=1.01, two-tailed p=0.3) between mothers who had this collected at birth or at subsequent follow up. The Everyday Discrimination Scale (EDS) was obtained at time of neonatal scan and was scored for the "day-to-day" experience of racial discrimination, with participant response choices that ranged from "never" or "less than once a year" to "every day". 8 Latent Constructs. Confirmatory factor analysis, distinct from exploratory factor analysis, confirms that variables identified a priori load on each factor. MPlus software was used to validate our a priori grouping of early life adversity variables into a Social Disadvantage latent factor (variables listed above) and a Psychosocial Stress factor (variables listed above).

Maximum likelihood estimation was used to derive latent factor scores for these two composite measures for all participants, despite occasional missing datapoints in observed variables. 9 Selfreported race was highly correlated with Social Disadvantage, offering no additional improvement to the model after other variables were accounted for and, thus, it was not included in either the latent Social Disadvantage or Psychosocial Stress composites.

Additionally, maternal substance use, health, and BMI all have complex relationships with both SES and psychosocial factors. Therefore, we analyzed these measures independently of our defined constructs of Social Disadvantage and Psychosocial Stress. The T2-weighted images were then preprocessed using the following standard steps: gradient and readout distortion correction using the Human Connectome Project preprocessing pipeline, 10 FSL axis reorientation to the MNI152 standard-space template, 11 image denoising using Advanced Normalization Tools for Brain and Image Analysis (ANTS) Registration Suite, 12 and co-registration using the Washington University School of Medicine Neuroimaging Laboratory (NIL)'s 4-dimensional floating point (4dfp)-based image analysis. 13 The resulting T2 images were then used as input for Melbourne Children's Regional Infant Brain atlas Surface (M-CRIB-S) segmentation and surface extraction toolkit, which automatically generated anatomical volume segmentations and reconstructed cortical surfaces. 14, 15 The M-CRIB-S toolkit included N4 bias field correction and brain extraction, as well as automatic segmentation into white and gray matter, cerebellum, brainstem, and subcortical gray matter subdivisions corresponding to FreeSurfer-like labeling. Curvature-based spherical registration and mapping, alignment, and averaging were performed, allowing for spatial normalization within the cohort and to the M-CRIB atlas.

The segmentation volumes and the cortical surfaces were then projected on the T2 images Step 1

Step 2 .46 a Standardized coefficient values. b Birthweight was not included as an independent variable for relative region of interest volumes adjusted for total brain volume to avoid overfitting. Standardized region of interest volumes were computed as the volume of the region divided by total brain volume. Step 1

Step 2 

Making Neighborhood-Disadvantage Metrics Accessible -The Neighborhood Atlas

Diet History Questionnaire. National Institutes of Health, Epidemiology and Genomics Research Program, National Cancer Institute

Update of the Healthy Eating Index: HEI-2015

A global measure of perceived stress

Detection of Postnatal Depression: Development of the 10-item Edinburgh Postnatal Depression Scale

Assessing Lifetime Stress Exposure Using the Stress and Adversity Inventory for Adults (Adult STRAIN): An Overview and Initial Validation

Racial Differences in Physical and Mental Health: Socio-economic Status, Stress and Discrimination

The minimal preprocessing pipelines for the Human Connectome Project

Adaptive non-local means denoising of MR images with spatially varying noise levels: Spatially Adaptive Nonlocal Denoising

A new neonatal cortical and subcortical brain atlas: the Melbourne Children's Regional Infant Brain (M-CRIB) atlas

Parcellation of the Cortex Using Surface-Based Melbourne Children's Regional Infant Brain Atlases (M-CRIB-S)