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. Author manuscript; available in PMC: 2024 Mar 1.
Published in final edited form as: J Perinatol. 2022 Jun 18;43(3):390–391. doi: 10.1038/s41372-022-01427-0

Early white matter tract changes in neonates with prenatal opioid exposure: a pilot study

Pooja Sikka 1, Neel Madan 2, Elizabeth Yen 3,4
PMCID: PMC9759619  NIHMSID: NIHMS1826947  PMID: 35717459

TO THE EDITOR:

The impact of prenatal opioids on the developing brain is not well studied, specifically on white matter tract development shortly after birth [13]. Our pilot study aims to evaluate and compare white matter changes in opioid- and non-exposed neonates in the immediate postnatal period.

Brain MRI was acquired within 48 h of birth using a ‘feed-and-swaddle’ method in 10 opioid-exposed neonates born at ≥34 weeks’ gestational age (GA), prior to the start of pharmacotherapy, and 11 healthy sex- and age-matched non-exposed controls. Exclusion criteria were <34 weeks’ GA, those already on pharmacotherapy at the time of recruitment, and those with congenital or chromosomal anomalies. Due to the GA matching and fixed timing of the brain MRI, neonates in both cohorts were equivalent in postmenstrual age at MRI acquisition. Diffusion tensor imaging (DTI) was acquired for each patient with a baseline image (b = 0 s/mm2) and 15 different diffusion orientations (b = 1000 s/mm2). The pediatric radiologist was blinded to the clinical status of the neonates. Single-subject and group-level DTI analyses were carried out using FMRIB’s Software Library (www.fmrib.ox.ac.uk/fsl), including corrections for eddy current-induced distortions and gross subject movement. Slices with signal loss caused by subject movement coinciding with the diffusion encoding were detected and replaced by predictions made by a Gaussian Process. To determine differences in white matter between the two groups, voxel-wise whole tract analysis of the fractional anisotropy (FA) data was performed with Tract Based Spatial Statistics using a pipeline optimized for neonatal DTI data (thresholded at FA > 0.19), with sex and GA at birth listed as covariates [4]. Continuous data were analyzed using a t-test, and categorical data using Chi-square. Significance was set at p ≤ 0.05. All FA data were further subjected to permutation (10,000) testing and family-wise error correction for multiple comparisons following threshold-free cluster enhancement (TFCE) to obtain a corrected t-statistical map, representing areas in the white matter tracts with relative FA reduction across the exposed and non-exposed cohorts.

As shown in Table 1, opioid-exposed neonates had lower birth weight and head circumference percentiles (p = 0.05) and length percentile (p = 0.07) compared to non-exposed neonates. Following adjustment for sex and GA, the opioid-exposed cohort showed no quantitative difference in FA from the non-exposed cohort (0.299 + 0.020 vs. 0.300 + 0.021 respectively, p = 0.52). However, a visual comparison of the corrected t-statistical map demonstrated qualitatively reduced FA in the opioid-exposed cohort in multiple bilateral white matter pathways involving the anterior and posterior corona radiata, inferior fronto-occipital fasciculus, superior and inferior longitudinal fasciculi, corpus callosum, anterior and posterior thalamic radiations, cingulum, internal and external capsules, amygdala, corticopontine, and corticospinal tracts (p > 0.05, TFCE corrected). The Johns Hopkins DTI white matter tractography atlas provided by the FSL software was used to define and confirm the location of these pathways.

Table 1.

Neonatal demographic characteristics and diffusion tensor imaging measurements

Non-Exposed (N= 11) Opioid-Exposed (N= 10) P-value
Gestational Age 37.1 (36.8, 38.4) 37.3 (37.0, 38.9) 0.71

Female 6 (54.5) 6 (60.0) 0.80

C-Section 6 (54.5) 3 (30.0) 0.26

Birth Weight (g) 3146.36 ± 337.9 2667.30 ± 677.39 0.05

Birth Weight Percentile 65.17 ± 10.40 26.40 ± 26.42 0.05

Head Circumference (cm) 35.37 ± 4.28 32.43 ± 2.93 0.09

Head Circumference Percentile 63.76 ± 25.53 33.77 ± 36.35 0.05

Length (cm) 46.76 ± 4.61 46.28 ± 4.65 0.82

Length Percentile 52.72 ± 22.91 28.73 ± 32.59 0.07

Apgar 1 minute 8.00 (8.00, 9.00) 8.00 (8.00, 8.75) 1.00

Apgar 5 minute 9.00 (7.50, 9.00) 9.00 (9.00, 9.00) 0.36

Maternal Opioids NA --- NA
 Buprenorphine 7 (70.0)
 Methadone 3 (30.0)

Fractional Anisotropy 0.300 ± 0.021 0.299 ± 0.020 0.52

Data are presented as mean ± standard deviation, median (interquartile range) for continuous measures, and N (%) for categorical measures. NA not applicable.

In conclusion, opioid exposure in utero is associated with structural and microstructural changes within major white matter tracts, as shown by a smaller head circumference and reduced FA in the amygdala and cerebral cortex. While our result is not statistically significant due to a small sample size, the white matter changes and FA reduction seen in opioid-exposed neonates corroborate prior studies [13]. Furthermore, to the best of our knowledge brain imaging in our study was conducted earlier than previous studies. Acquired immediately after birth, we demonstrated early white matter changes in opioid-exposed neonates that most likely are attributed to opioid exposure in utero rather than other postnatal factors. As reduced FA has been associated with long-term cognitive and motor deficits [5], our preliminary study holds important insights into the effects of opioid exposure on neonatal brain development. Future directions will include a larger sample size, serial brain imaging, and longitudinal neurodevelopmental follow-up to monitor the impact of these structural and microstructural changes on long-term neural growth and development in opioid-exposed neonates.

ACKNOWLEDGEMENTS

We would like to thank all the families for their participation in this study and the entire staff at the Tufts Shields MRI for their assistance in organizing and acquiring the images. Authors would also like to acknowledge the following groups for their support: (A) K12 Building Interdisciplinary Research for Careers in Women’s Health; (B) Tufts Tiny Feet Funds.

FUNDING

This study received funding from K12 Building Interdisciplinary Research for Careers in Women’s Health (BIRCWH) Grant #5K12HD092535–05 (EY) and Tufts Tiny Feet Funds (EY). The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding agencies.

Footnotes

COMPETING INTERESTS

The authors declare no competing interests.

ETHICS APPROVAL

The study protocol was approved by the Tufts Institutional Review Board (IRB). Consent from each participant was obtained prior to study enrollment. This study was performed in accordance with the Declaration of Helsinki.

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