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Alcohol is one of the most widely used substances. Alcohol use accounts for 5.1% of the global disease burden, contributes substantially to societal and economic costs, and leads to approximately 3 million global deaths yearly. Alcohol use disorder (AUD) includes various drinking behavior patterns that lead to short-term or long-lasting effects on health. Ethanol, the main psychoactive molecule acting in alcoholic beverages, directly impacts the GABAergic system, contributing to GABAergic dysregulations that vary depending on the intensity and duration of alcohol consumption. A small number of interventions have been developed that target the GABAergic system, but there are promising future therapeutic avenues to explore. This review provides an overview of the impact of alcohol on the GABAergic system, the current interventions available for AUD that target the GABAergic system, and the novel interventions being explored that in the future could be included among first-line therapies for the treatment of AUD., Competing Interests: TP receives compensation for consulting work from Damona Pharmaceutical Inc., a biotech company developing GABAergic molecules for the treatment of cognitive dysfunctions in depression. ES is co-founder, CEO and CSO of Damona Pharmaceutical Inc. DB receives research support from CIHR, NIH, Brain Canada, and the Temerty Family through the CAMH Foundation. He received research support and in-kind equipment support for an investigator-initiated study from Brainsway Ltd. and has been the site principal investigator for three sponsor-initiated studies for Brainsway Ltd. DB also received in-kind equipment support from Magventure for 3 investigator-initiated studies. DB received medication supplies for an investigator-initiated trial from Indivior. DB has participated in one Scientific Advisory Board Meeting for Janssen and one meeting for Welcony Inc. DV holds the Labatt Family Professorship in Depression Biology, a University Named Professorship at the University of Toronto. She receives research support from CIHR, NIH, the Centre for Addiction and Mental Health (CAMH), University Hospital Network (UHN) and the Department of Psychiatry at the University of Toronto. DV declares no biomedical interests or conflicts. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Dharavath, Pina-Leblanc, Tang, Sloan, Nikolova, Pangarov, Ruocco, Shield, Voineskos, Blumberger, Boileau, Bozinoff, Gerretsen, Vieira, Melamed, Sibille, Quilty and Prevot.)

Introduction: The proportion of older adults within society is sharply increasing and a better understanding of how we age starts to be critical. However, given the paucity of longitudinal studies with both neuroimaging and epigenetic data, it remains largely unknown whether the speed of the epigenetic clock changes over the life course and whether any such changes are proportional to changes in brain aging and cognitive skills. To fill these knowledge gaps, we conducted a longitudinal study of a prenatal birth cohort, studied epigenetic aging across adolescence and young adulthood, and evaluated its relationship with brain aging and cognitive outcomes., Methods: DNA methylation was assessed using the Illumina EPIC Platform in adolescence, early and late 20 s, DNA methylation age was estimated using Horvath's epigenetic clock, and epigenetic age gap (EpiAGE) was calculated as DNA methylation age residualized for batch, chronological age and the proportion of epithelial cells. Structural magnetic resonance imaging (MRI) was acquired in both the early 20 s and late 20 s using the same 3T Prisma MRI scanner and brain age was calculated using the Neuroanatomical Age Prediction using R (NAPR) platform. Cognitive skills were assessed using the Wechsler Adult Intelligence Scale (WAIS) in the late 20 s., Results: The EpiAGE in adolescence, the early 20 s, and the late 20 s were positively correlated ( r = 0.34-0.47), suggesting that EpiAGE is a relatively stable characteristic of an individual. Further, a faster pace of aging between the measurements was positively correlated with EpiAGE at the end of the period ( r = 0.48-0.77) but negatively correlated with EpiAGE at the earlier time point ( r = -0.42 to -0.55), suggesting a compensatory mechanism where late matures might be catching up with the early matures. Finally, higher positive EpiAGE showed small (Adj R 2 = 0.03) but significant relationships with a higher positive brain age gap in all participants and lower full-scale IQ in young adult women in the late 20 s., Discussion: We conclude that the EpiAGE is a relatively stable characteristic of an individual across adolescence and early adulthood, but that it shows only a small relationship with accelerated brain aging and a women-specific relationship with worse performance IQ., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Mareckova, Pacinkova, Marecek, Sebejova, Izakovicova Holla, Klanova, Brazdil and Nikolova.)

Introduction: As the population skews toward older age, elucidating mechanisms underlying human brain aging becomes imperative. Structural MRI has facilitated non-invasive investigation of lifespan brain morphology changes, yet this domain remains uncharacterized in rodents despite increasing use as models of disordered human brain aging., Methods: Young (2m, n = 10), middle-age (10m, n = 10) and old (22m, n = 9) mice were utilized for maturational (young vs. middle-age) and aging-related (middle-age vs. old mice) comparisons. Regional brain volume was averaged across hemispheres and reduced to 32 brain regions. Pairwise group differences in regional volume were tested using general linear models, with total brain volume as a covariate. Sample-wide associations between regional brain volume and Y-maze performance were assessed using logistic regression, residualized for total brain volume. Both analyses corrected for multiple comparisons. Structural covariance networks were generated using the R package "igraph." Group differences in network centrality (degree), integration (mean distance), and segregation (transitivity, modularity) were tested across network densities (5-40%), using 5,000 (1,000 for degree) permutations with significance criteria of p < 0.05 at ≥5 consecutive density thresholds., Results: Widespread significant maturational changes in volume occurred in 18 brain regions, including considerable loss in isocortex regions and increases in brainstem regions and white matter tracts. The aging-related comparison yielded 6 significant changes in brain volume, including further loss in isocortex regions and increases in white matter tracts. No significant volume changes were observed across either comparison for subcortical regions. Additionally, smaller volume of the anterior cingulate area (χ 2 = 2.325, p BH = 0.044) and larger volume of the hippocampal formation (χ 2 = -2.180, p BH = 0.044) were associated with poorer cognitive performance. Maturational network comparisons yielded significant degree changes in 9 regions, but no aging-related changes, aligning with network stabilization trends in humans. Maturational decline in modularity occurred (24-29% density), mirroring human trends of decreased segregation in young adulthood, while mean distance and transitivity remained stable., Conclusion/implications: These findings offer a foundational account of age effects on brain volume, structural brain networks, and working memory in mice, informing future work in facilitating translation between rodent models and human brain aging., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Clifford, Miles, Prevot, Misquitta, Ellegood, Lerch, Sibille, Nikolova and Banasr.)

The A allele of the FRAS1-related extracellular matrix protein 3 (FREM3) rs7676614 single nucleotide polymorphism (SNP) was linked to major depressive disorder (MDD) in an early genome-wide association study (GWAS), and to symptoms of psychomotor retardation in a follow-up investigation. In line with significant overlap between age- and depression-related molecular pathways, parallel work has shown that FREM3 expression in postmortem human brain decreases with age. Here, we probe the effect of rs7676614 on amygdala reactivity and perceptual processing speed, both of which are altered in depression and aging. Amygdala reactivity was assessed using a face-matching BOLD fMRI paradigm in 365 Caucasian participants in the Duke Neurogenetics Study (DNS) (192 women, mean age 19.7 ± 1.2). Perceptual processing speed was indexed by reaction times in the same task and the Trail Making Test (TMT). The effect of rs7676614 on FREM3 mRNA brain expression levels was probed in a postmortem cohort of 169 Caucasian individuals (44 women, mean age 50.8 ± 14.9). The A allele of rs7676614 was associated with blunted amygdala reactivity to faces, slower reaction times in the face-matching condition (p < 0.04), as well as marginally slower performance on TMT Part B (p = 0.056). In the postmortem cohort, the T allele of rs6537170 (proxy for the rs7676614 A allele), was associated with trend-level reductions in gene expression in Brodmann areas 11 and 47 (p = 0.066), reminiscent of patterns characteristic of older age. The low-expressing allele of another FREM3 SNP (rs1391187) was similarly associated with reduced amygdala reactivity and slower TMT Part B speed, in addition to reduced BA47 activity and extraversion (p < 0.05). Together, these results suggest common genetic variation associated with reduced FREM3 expression may confer risk for a subtype of depression characterized by reduced reactivity to environmental stimuli and slower perceptual processing speed, possibly suggestive of accelerated aging.