7 research outputs found
Alterations in amygdala–prefrontal circuits in infants exposed to prenatal maternal depression
Prenatal exposure to maternal depression is common and puts offspring at risk for developing a range of neuropsychiatric
disorders. Despite its prevalence and adverse associations, neurobiological processes by which prenatal maternal depression (PMD)
confers risk remain poorly understood. Maternal mood and fetal behavior were assessed between 34 and 37 gestational weeks.
Using resting-state functional magnetic resonance imaging (fMRI) and diffusion MRI, we examined functional and structural
connectivity within amygdala–prefrontal circuits in 64 infants (mean age = 5.8 ± 1.7 weeks) with (n = 20) and without (n = 44) in utero
exposure to PMD. Resting fMRI and diffusion MRI both indicated atypical amygdala–prefrontal connectivity in PMD-exposed infants:
Resting fMRI indicated increased inverse, or negative, functional connectivity between the amygdala and the dorsal prefrontal
cortex (PFC), bilaterally, and diffusion MRI indicated decreased structural connectivity between the right amygdala and the right
ventral PFC. Spectral dynamic causal modeling supported these findings suggesting altered amygdala–PFC effective (or directed)
connectivity in PMD-exposed infants. Last, path analyses supported a mechanistic account relating PMD to a third-trimester fetal
behavior: PMD alters amygdala–PFC connectivity, which in turn, is associated with an increase in fetal heart rate reactivity to in utero
perturbation. These data suggest that the maturation and coordination of central and peripheral physiology are altered by prenatal
exposure to maternal depression. To the best of our knowledge, this is the first study to directly associate infant MRI measures with
a behavior—fetal heart rate response, and supports hypotheses that PMD-associated variations in the development of amygdala–
PFC circuits are relevant for future neurobehavioral maturation
Additional file 3 of Overestimated prediction using polygenic prediction derived from summary statistics
Additional file 3: Table S3. rPRS and sPRS results on A
Additional file 7 of Overestimated prediction using polygenic prediction derived from summary statistics
Additional file 7: Fig. S1. The number of test set subjects required to gain statistical significance (P < 0.01) for hypertension using UK Bioban
Additional file 5 of Overestimated prediction using polygenic prediction derived from summary statistics
Additional file 5: Table S5. PRS performance comparisons for height in UK Bioban
Additional file 4 of Overestimated prediction using polygenic prediction derived from summary statistics
Additional file 4: Table S4. PRS performance comparisons for hypertension in UK Bioban
Additional file 2 of Overestimated prediction using polygenic prediction derived from summary statistics
Additional file 2: Table S2. PRS performance after excluding genetically close individuals from the test se
Additional file 6 of Overestimated prediction using polygenic prediction derived from summary statistics
Additional file 6: Table S6. Performance comparisons between PRS and Lassosu