Behavioural dysfunctions of 10-year-old children born extremely preterm associated with corticotropin-releasing hormone expression in the placenta

From songbird to humans: The multifaceted roles of FOXP2 in speech and motor learning

Motor learning involves a complex network of brain structures and is crucial for tasks like speech. The cerebral cortex, subcortical nuclei, and cerebellum are involved in motor learning and vocalization. Vocal learning has been demonstrated across species. However, it is a task that should be further studied and reevaluated, particularly in species considered non-vocal learners, to potentially uncover new insights. FOXP2, a transcription factor, has been implicated in speech learning and execution. Several variants have been involved in speech and cognitive impairments; the most studied is the R553H, found in the KE family, where more than half of the members show verbal dyspraxia. Brain FOXP2 expression shows consistent patterns across species in regions associated with motor learning and execution. Animal models expressing mutated FOXP2 showed impaired motor learning and vocalization. Genes regulated by FOXP2 are related to neural differentiation, connectivity, and synaptic plasticity, indicating its role in brain development and function. This review explores the intricate relationship between FOXP2, motor learning, and speech in an anatomical and functional context.

Sex-specific associations between placental corticotropin releasing hormone and problem behaviors in childhood

Placental corticotropin-releasing hormone (pCRH) is a neuroactive peptide produced in high concentrations in mid-late pregnancy, during key periods of fetal brain development. Some evidence suggests that higher pCRH exposure during gestation is associated with adverse neurodevelopment, particularly in female offspring. In 858 mother-child dyads from the sociodemographically diverse CANDLE cohort (Memphis, TN), we examined: (1) the slope of pCRH rise in mid-late pregnancy and (2) estimated pCRH at delivery as a measure of cumulative prenatal exposure. When children were 4 years-old, mothers reported on problem behaviors using the Child Behavior Checklist (CBCL) and cognitive performance was assessed by trained psychologists using the Stanford-Binet Intelligence Scales. We fitted linear regression models examining pCRH in relation to behavioral and cognitive performance measures, adjusting for covariates. Using interaction models, we evaluated whether associations differed by fetal sex, breastfeeding, and postnatal neighborhood opportunity. In the full cohort, log-transformed pCRH measures were not associated with outcomes; however, we observed sex differences in some models (interaction p-values≤0.01). In male offspring, an interquartile (IQR) increase in pCRH slope (but not estimated pCRH at delivery), was positively associated with raw Total (β=3.06, 95%CI: 0.40, 5.72), Internalizing (β=0.89, 95%CI: 0.03, 1.76), and Externalizing (β=1.25, 95%CI: 0.27, 2.22) Problem scores, whereas, in females, all associations were negative (Total Problems: β=-1.99, 95%CI: -3.89, -0.09; Internalizing: β=-0.82, 95%CI: -1.42, -0.23; Externalizing: β=-0.56, 95%CI: -1.34, 0.22). No associations with cognitive performance were observed nor did we observe moderation by breastfeeding or postnatal neighborhood opportunity. Our results provide further evidence that prenatal pCRH exposure may impact subsequent child behavior in sex-specific ways, however in contrast to prior studies suggesting adverse impacts in females, steeper mid-gestation pCRH rise was associated with more problem behaviors in males, but fewer in females.

Identification of key pathways and genes responsible for aggressive behavior

Aggression is a complex behavior, underpinned by cross talk between several biomolecules. To date a composite molecular network of the behavioral disorder has not been constructed. The present study aims to develop the same from the system network analyses recruiting genes with empirical evidence demonstrating their role in the incidence and progression of aggression. In short, 327 genes were recruited in the study after extensive literature survey and subsequent shortlisting by sieving out the comorbidities like cancer and other pathological and physiological ailments, other languages and repeated citations. Subsequent String network analysis coalesces 275 genes in a network with 2223 edges. The developed network was then subjected to delineate modules using MCODE which via gene clustering on the basis of gene ontology segregate all genes into 14 modules. Of these, as expected top 5 modules involved entailing of neuronal signaling pathways with redundant repetitions. Finally, 10 genes (known) were picked randomly, accounting average module size, and subjected to the network analysis with 100,000 bootstrap replicates. This results in the detection of certain novel genes that lacks empirical evidence for their association with the aggression. Amongst those, most notable are genes involved in protein turnover regulation like UBC, UBA, mitogenic proteins such as Rho and Myc, transcription factors like Tp53. The findings in turn fill caveats in the molecular resolution of cross talk that underscore the development of aggressive behavior and may then be exploited as screening biomarker and/or therapeutic intervention for aggression.