Corticolimbic DCC gene co-expression networks as predictors of impulsivity in children

Abstract

Inhibitory control deficits are prevalent in multiple neuropsychiatric conditions. The communication- as well as the connectivity- between corticolimbic regions of the brain are fundamental for eliciting inhibitory control behaviors, but early markers of vulnerability to this behavioral trait are yet to be discovered. The gradual maturation of the prefrontal cortex (PFC), in particular of the mesocortical dopamine innervation, mirrors the protracted development of inhibitory control; both are present early in life, but reach full maturation by early adulthood. Evidence suggests the involvement of the Netrin-1/DCC signaling pathway and its associated gene networks in corticolimbic development. Here we investigated whether an expression-based polygenic score (ePRS) based on corticolimbic-specific DCC gene co-expression networks associates with impulsivity-related phenotypes in community samples of children. We found that lower ePRS scores associate with higher measurements of impulsive choice in 6-year-old children tested in the Information Sampling Task and with impulsive action in 6- and 10-year-old children tested in the Stop Signal Task. We also found the ePRS to be a better overall predictor of impulsivity when compared to a conventional PRS score comparable in size to the ePRS (4515 SNPs in our discovery cohort) and derived from the latest GWAS for ADHD. We propose that the corticolimbic DCC-ePRS can serve as a novel type of marker for impulsivity-related phenotypes in children. By adopting a systems biology approach based on gene co-expression networks and genotype-gene expression (rather than genotype-disease) associations, these results further validate our methodology to construct polygenic scores linked to the overall biological function of tissue-specific gene networks.

Disturbed relationship between glucocorticoid receptor and 5-HT1AR/5-HT2AR in ADHD rats: A correlation study

“…Furthermore, the prefrontal cortex (PFC) serves as the chief executive officer of the brain, controlling the highest level of cognitive and emotional processes, which are commonly disrupted in mental illnesses, such as ADHD ( Hiser and Koenigs, 2018 ; Yan and Rein, 2022 ). Many studies of ADHD have reported volumetric abnormalities in PFC and indicated that ventromedial prefrontal cortex structure is a biomarker for ADHD symptomatology ( Albaugh et al, 2017 ; Bayard et al, 2020 ; Restrepo-Lozano et al, 2022 ). Aberrant serotonergic neurotransmission has long been implicated in the pathogenesis of neuropsychiatric disorders associated with PFC dysfunction, including schizophrenia, depression, and anxiety ( Leonardo and Hen, 2006 ).…”

Immune signaling as a node of interaction between systems that sex-specifically develop during puberty and adolescence

“…In fact, dopamine receptor over-expression in the dorsal striatum was confirmed to be independent of gonadal hormones in rats of both sex via gonadectomies ( Andersen et al, 2002 ). Adolescent dopamine receptor overexpression may be related to more recent reports of DCC-netrin-mediated dopaminergic axonal outgrowth, impulsivity, and behavioral response to addictive substances in male mice ( Reynolds et al, 2018 , Cuesta et al, 2020 , Restrepo-Lozano et al, 2022 ). As yet, there is no link between synaptic overexpression and immune signaling, but microglia are important for dopamine neuron axon outgrowth earlier in life ( Squarzoni et al, 2014 ).…”

Homeostatic inflammation in the placenta is protective against adult cardiovascular and depressive outcomes

“…In a comparison with the Gene-Tissue Expression (GTEx) v8 eQTL catalogue 74 , the combination of these eQTLs associated with cyan module genes were highly specific to the placenta ( Figure S1D ). We then identified these variants in the children of the GUSTO cohort and weighted them based on their effect size from Peng et al , before summing them within individuals to create a fetoplacental PGS (as described previously 49,50 ). We reasoned that a PGS comprised of eQTLs would be representative of individual variation in cyan module expression.…”

“…PGS based on gene lists were generated as previously described [49][50][51] . In brief, SNPs located on genes in a relevant list were identified using the biomaRt package 52,53 .…”