Localized Prediction of Glutamate from Whole-Brain Functional Connectivity of the Pregenual Anterior Cingulate Cortex

Cross-sectional study of retrospective self-reported childhood emotional neglect and inhibitory neurometabolite levels in the pregenual anterior cingulate cortex in adult humans

High childhood emotional maltreatment (CM-EMO) is reported in mood and anxiety disorders. The associations with an increased risk for psychopathology are not fully understood. One potential factor may be through alterations in gamma-Aminobutyric acid (GABA). The pregenual anterior cingulate cortex (pgACC) is an important brain region for emotion processing and its' GABA levels were previously implicated in mood and anxiety disorders pathophysiology. We examined the association between the self-reported CM-EMO in adulthood and GABA + levels in the pgACC and in a control region, anterior mid cingulate cortex. GABA+ and total creatine (tCr) were measured in the pgACC and aMCC voxels in seventy-four healthy volunteers (32 (43%) women, ages 19-54, age [standard deviation] = 27.1 [6.5]) using proton magnetic resonance spectroscopy at 7 T. Childhood Trauma Questionnaire was completed by adult participants to measure retrospective self-reported experience of emotional neglect (CM-EMO-NEG) and emotional abuse (CM-EMO-AB) during childhood. Linear mixed models tested the interaction between the region and the two subscales, and GABA+/tCr ratios, with an adjusted alpha = 0.025. Following, linear models, including with covariates were tested. There was an interaction effect between region and CM-EMO-NEG (B = -0.007, p = 0.009), driven by a negative relationship between CM-EMO-NEG and GABA+/tCr in the pgACC (B = -0.004, p = 0.013). Results for CM-EMO-NEG were robust to inclusion of different covariates (ps < 0.035). There was no interaction effect for the CM-EMO-AB (B = 0.007, p = 0.4). Limitations include cross-sectional measurement and retrospective nature of the CTQ. The findings indicate preliminary importance of inhibitory neurometabolite concentrations in the pgACC for retrospective reporting of CM-EMO-NEG.

Correlation of receptor density and mRNA expression patterns in the human cerebral cortex

Changes in distribution of associated molecular targets have been reported across several neuropsychiatric disorders. However, the high-resolution topology of most proteins is unknown and simultaneous in vivo measurement in multi-receptor systems is complicated. To account for the missing proteomic information, messenger ribonucleic acid (mRNA) transcripts are typically used as a surrogate. Nonetheless, post-transcriptional and post-translational processes might cause the discrepancy between the final distribution of proteins and gene expression patterns. Therefore, this study aims to investigate ex vivo links between mRNA expression and corresponding receptor density in the human cerebral cortex. To this end, autoradiography data on the density of 15 different receptors in 38 brain regions were correlated with the expression patterns of 50 associated genes derived from microarray data (mA), RNA sequencing data (RNA-Seq) provided by the Allen Human Brain Atlas and predicted mRNA expression patterns (pred-mRNA). Spearman's rank correlation was used to evaluate the possible links between proteomic data and mRNA expression patterns. Correlations between mRNA and protein density varied greatly between targets: Positive associations were found for e.g. the serotonin 1A (pred-mRNA: rs = 0.708; mA: rs = 0.601) or kainate receptor (pred-mRNA: rs = 0.655; mA: rs = 0.601; RNA-Seq: rs = 0.575) as well as a few negative associations e.g. γ-Aminobutyric acid (GABA) A receptor subunit α3 (pred-mRNA: rs = -0.638; mA: rs = -0.619) or subunit α5 (pred-mRNA: rs = -0.565; mA: rs = -0.563), while most of the other investigated target receptors showed low correlations. The high variability in the correspondence of mRNA expression and receptor spatial distribution warrants caution when inferring the topology of molecular targets in the brain from transcriptome data. This not only highlights the longstanding value of molecular imaging but also indicates a need for comprehensive proteomic studies.