Smoking contributes to a variety of neurodegenerative diseases and neurobiological abnormalities, suggesting that smoking is associated with accelerated brain aging. However, the neurobiological mechanisms affected by smoking, and whether they are genetically influenced, remain to be investigated.

Using structural magnetic resonance imaging data from the UK Biobank (n = 33 293), a brain age predictor was trained on non-smoking healthy groups and tested on smokers to obtain the BrainAge Gap (BAG). The cumulative effect of multiple common genetic variants associated with smoking was then calculated to acquire a polygenic risk score (PRS). The relationship between PRS, BAG, total gray matter volume (tGMV), and smoking parameters was explored and further genes included in the PRS were annotated to identify potential molecular mechanisms affected by smoking.

The BrainAge in smokers was predicted with very high accuracy (r = 0.725, MAE = 4.16). Smokers had a greater BAG (Cohen's d = 0.074, p < 0.0001) and higher PRS (Cohen's d = 0.63, p < 0.0001) than non-smokers. A higher PRS was associated with increased amount of smoking, mediated by BAG and tGMV. Several neurotransmitters and ion channel pathways were enriched in the group of smoking-related genes involved in addiction, brain synaptic plasticity, and some neurological disorders.

By using a simplified single indicator of the entire brain (BAG) in combination with the PRS, this study highlights the greater BAG in smokers and its linkage with genes and smoking behavior, providing insight into the neurobiological underpinnings and potential features of smoking-related aging.

Our previous genome-wide association study (CONVERGE sample) identified significant association between single nucleotide polymorphisms (SNPs) near the SIRT1 gene and major depressive disorder (MDD) in Chinese populations.

To investigate whether SNPs across the SIRT1 gene locus affect regional grey matter density in the Han Chinese population.

T1-weighted structural magnetic resonance imaging was conducted on 92 healthy participants from Eastern China. Grey matter was segmented from the image, which consisted of voxel-wise grey matter density. The effect of SIRT1 SNPs on grey matter density was determined by a multiple linear regression framework.

SNP rs4746720 was significantly associated with grey matter density in two brain cortical regions: the orbital part of the right inferior frontal gyrus and the orbital part of the left inferior frontal gyrus (family-wise error-corrected P < 0.05; voxel-wise P < 0.001). Also, rs4746720 exceeded genome-wide significance in association with MDD in our CONVERGE sample (P = 3.32 × 10−08, odds ratio 1.161).

Our results provided evidence for a potential role of the SIRT1 gene in the brain, implying a possible pathophysiological mechanism underlying susceptibility to MDD.

Cortical glutamatergic dysfunction is thought to be fundamental for psychosis development, and may lead to structural degeneration through excitotoxicity. Glutamate levels have been related to gray matter volume (GMV) alterations in people at ultra-high risk of psychosis, and we previously reported GMV changes in individuals with high schizotypy (HS), which refers to the expression of schizophrenia-like characteristics in healthy people. This study sought to examine whether GMV changes in HS subjects are related to glutamate levels.

We selected 22 healthy subjects with HS and 23 healthy subjects with low schizotypy (LS) based on their rating on a self-report questionnaire for psychotic-like experiences. Glutamate levels were measured in the bilateral anterior cingulate cortex (ACC) using proton magnetic resonance spectroscopy, and GMV was assessed using voxel-based morphometry.

Subjects with HS showed GMV decreases in the rolandic operculum/superior temporal gyrus (pFWE = 0.045). Significant increases in GMV were also detected in HS, in the precuneus (pFWE = 0.043), thereby replicating our previous finding in a separate cohort, as well as in the ACC (pFWE = 0.041). While the HS and LS groups did not differ in ACC glutamate levels, in HS subjects ACC glutamate was negatively correlated with ACC GMV (pFWE = 0.026). Such association was absent in LS.

Our study shows that GMV findings in schizotypy are related to glutamate levels, supporting the hypothesis that glutamatergic function may lead to structural changes associated with the expression of psychotic-like experiences.