全基因组关联研究
双相情感障碍
遗传建筑学
基因组学
生物
遗传关联
表观遗传学
表达数量性状基因座
遗传学
计算生物学
功能基因组学
特质
表型
锂(药物)
候选基因
基因组
基因
基因型
单核苷酸多态性
内分泌学
计算机科学
程序设计语言
作者
Sergi Papiol,Thomas G. Schulze,Urs Heilbronner
标识
DOI:10.1016/j.neulet.2022.136786
摘要
Lithium is an effective mood stabilizer in bipolar disorder (BD). There is, however, high variability in treatment response to lithium and only 20–30% of individuals with BD are excellent responders. This subgroup has been shown to have specific phenotypic characteristics, and family studies have implicated genetics as an important factor. However, candidate gene studies did not find evidence for major effect genes. Genome-wide association studies (GWAS) have emphasized that lithium response is a polygenic trait. GWAS based on larger sample sizes and non-European ancestries are likely to shed light on the genomic architecture of this trait. Furthermore, induced pluripotent stem cells, transcriptomics, epigenetics, the integration of multiple omics data, and their combination with advanced machine learning techniques hold promise for the understanding of the complex biological underpinnings of lithium treatment response.
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