Genes associated with cortical thickness alterations in behavioral addiction.
Hongsheng XieYuanyuan WangFei ZhuFeifei ZhangBaolin WuZiru ZhaoRuoqiu GanQiyong GongZhi-Yun JiaPublished in: Cerebral cortex (New York, N.Y. : 1991) (2024)
Behavioral addiction (BA) is a conceptually new addictive phenotype characterized by compulsive reward-seeking behaviors despite adverse consequences. Currently, its underlying neurogenetic mechanism remains unclear. Here, this study aimed to investigate the association between cortical thickness (CTh) and genetic phenotypes in BA. We conducted a systematic search in five databases and extracted gene expression data from the Allen Human Brain Atlas. Meta-analysis of 10 studies (343 addicted individuals and 355 controls) revealed that the BA group showed thinner CTh in the precuneus, postcentral gyrus, orbital-frontal cortex, and dorsolateral prefrontal cortex (P < 0.005). Meta-regression showed that the CTh in the precuneus and postcentral gyrus were negatively associated with the addiction severity (P < 0.0005). More importantly, the CTh phenotype of BA was spatially correlated with the expression of 12 genes (false discovery rate [FDR] < 0.05), and the dopamine D2 receptor had the highest correlation (rho = 0.55). Gene enrichment analysis further revealed that the 12 genes were involved in the biological processes of behavior regulation and response to stimulus (FDR < 0.05). In conclusion, our findings demonstrated the thinner CTh in cognitive control-related brain areas in BA, which could be associated with the expression of genes involving dopamine metabolism and behavior regulation.
Keyphrases
- prefrontal cortex
- genome wide
- genome wide identification
- gene expression
- poor prognosis
- dna methylation
- single cell
- bioinformatics analysis
- optical coherence tomography
- binding protein
- genome wide analysis
- working memory
- copy number
- mental health
- big data
- small molecule
- high throughput
- transcription factor
- machine learning
- transcranial magnetic stimulation
- deep learning
- blood brain barrier
- electronic health record
- uric acid
- multiple sclerosis
- cerebral ischemia
- protein kinase
- smooth muscle