Introduction: Opioid use during pregnancy and subsequent neonatal opioid withdrawal syndrome (NOWS) have been associated with poor developmental outcomes including cognitive functioning. Less is known about the underlying molecular effects of prenatal opioid exposure and subsequent withdrawal; however, given the recent increase in NOWS cases, there is a pressing need to better understand these effects, which may partially explain cognitive deficits that have been observed in both preclinical NOWS models and patients with NOWS. This study evaluated the effects of prenatal heroin exposure and subsequent precipitated withdrawal symptoms on microglial reactivity in the nucleus accumbens (NAc), dorsal hippocampus (HC), and ventral tegmental area (VTA) in rat neonates, as well as cognitive functioning at three developmental time points using the Morris Water Maze (MWM) task.
Methods: Heroin or saline (2 mg/kg) was randomly assigned and administered to six pregnant Sprague Dawley rat dams via osmotic minipump. A total of 63 rat neonates underwent naloxone-precipitated (5 mg/kg, subcutaneous injection) withdrawal testing at postnatal day 10 (PN10). Following withdrawal testing, neonates were randomly assigned to undergo perfusion and subsequent immunohistochemistry experiments to fluoresce Iba-1 for microglia detection, or to undergo the MWM task at three separate developmental time points (PN21-23; PN37; PN60) for cognitive testing.
Results: Results suggest that in-utero heroin exposure led to an increase in ultrasonic vocalizations during naloxone-precipitated withdrawal; a sensitive index of withdrawal in rat neonates. Additional results suggest increased microglial reactivity in the HC and VTA, but not the NAc, as well as reduced performance during the MWM in the group exposed to heroin in-utero.
Discussion: Together, these data suggest that in-utero opioid exposure is associated with microglial reactivity in brain regions associated with learning and memory, and may be associated with later cognitive deficits. Further research is needed to characterize these findings, which may inform future therapeutic strategies for this vulnerable population.
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http://dx.doi.org/10.1016/j.ntt.2024.107385 | DOI Listing |
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Computational and Biological Learning Lab, Department of Engineering, University of Cambridge, Cambridge, United Kingdom.
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Speech comprehension involves the dynamic interplay of multiple cognitive processes, from basic sound perception, to linguistic encoding, and finally to complex semantic-conceptual interpretations. How the brain handles the diverse streams of information processing remains poorly understood. Applying Hidden Markov Modeling to fMRI data obtained during spoken narrative comprehension, we reveal that the whole brain networks predominantly oscillate within a tripartite latent state space.
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