Prenatal lead exposure impacts cross-hemispheric and long-range connectivity in the human fetal brain.
Neuroimage
; 191: 186-192, 2019 05 01.
Article
in En
| MEDLINE
| ID: mdl-30739062
Lead represents a highly prevalent metal toxicant with potential to alter human biology in lasting ways. A population segment that is particularly vulnerable to the negative consequences of lead exposure is the human fetus, as exposure events occurring before birth are linked to varied and long-ranging negative health and behavioral outcomes. An area that has yet to be addressed is the potential that lead exposure during pregnancy alters brain development even before an individual is born. Here, we combine prenatal lead exposure information extracted from newborn bloodspots with the human fetal brain functional MRI data to assess whether neural network connectivity differs between lead-exposed and lead-naïve fetuses. We found that neural connectivity patterns differed in lead-exposed and comparison groups such that fetuses that were not exposed demonstrated stronger age-related increases in cross-hemispheric connectivity, while the lead-exposed group demonstrated stronger age-related increases in posterior cingulate cortex (PCC) to lateral prefrontal cortex (PFC) connectivity. These are the first results to demonstrate metal toxicant-related alterations in human fetal neural connectivity. Remarkably, the findings point to alterations in systems that support higher-order cognitive and regulatory functions. Objectives for future work are to replicate these results in larger samples and to test the possibility that these alterations may account for significant variation in future child cognitive and behavioral outcomes.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Prenatal Exposure Delayed Effects
/
Brain
/
Lead Poisoning, Nervous System, Childhood
/
Neural Pathways
Type of study:
Diagnostic_studies
/
Etiology_studies
Limits:
Female
/
Humans
/
Pregnancy
Language:
En
Journal:
Neuroimage
Journal subject:
DIAGNOSTICO POR IMAGEM
Year:
2019
Type:
Article