Oraki Kohshour Mojtaba, Papiol Sergi, Ching Christopher R K, Schulze Thomas G
Institute of Psychiatric Phenomics and Genomics, University Hospital LMU Munich, Germany; and Department of Immunology, School of Medicine, Ahvaz Jundishapur University of Medical Sciences, Iran.
Institute of Psychiatric Phenomics and Genomics, University Hospital LMU Munich, Germany; and Department of Psychiatry and Psychotherapy, University Hospital LMU Munich, Germany.
BJPsych Open. 2022 Feb 1;8(2):e36. doi: 10.1192/bjo.2021.1082.
To date, besides genome-wide association studies, a variety of other genetic analyses (e.g. polygenic risk scores, whole-exome sequencing and whole-genome sequencing) have been conducted, and a large amount of data has been gathered for investigating the involvement of common, rare and very rare types of DNA sequence variants in bipolar disorder. Also, non-invasive neuroimaging methods can be used to quantify changes in brain structure and function in patients with bipolar disorder.
To provide a comprehensive assessment of genetic findings associated with bipolar disorder, based on the evaluation of different genomic approaches and neuroimaging studies.
We conducted a PubMed search of all relevant literatures from the beginning to the present, by querying related search strings.
ANK3, CACNA1C, SYNE1, ODZ4 and TRANK1 are five genes that have been replicated as key gene candidates in bipolar disorder pathophysiology, through the investigated studies. The percentage of phenotypic variance explained by the identified variants is small (approximately 4.7%). Bipolar disorder polygenic risk scores are associated with other psychiatric phenotypes. The ENIGMA-BD studies show a replicable pattern of lower cortical thickness, altered white matter integrity and smaller subcortical volumes in bipolar disorder.
The low amount of explained phenotypic variance highlights the need for further large-scale investigations, especially among non-European populations, to achieve a more complete understanding of the genetic architecture of bipolar disorder and the missing heritability. Combining neuroimaging data with genetic data in large-scale studies might help researchers acquire a better knowledge of the engaged brain regions in bipolar disorder.
迄今为止,除全基因组关联研究外,还开展了多种其他基因分析(如多基因风险评分、全外显子组测序和全基因组测序),并且已经收集了大量数据,用于研究常见、罕见和极罕见类型的DNA序列变异在双相情感障碍中的作用。此外,非侵入性神经成像方法可用于量化双相情感障碍患者脑结构和功能的变化。
基于对不同基因组方法和神经成像研究的评估,全面评估与双相情感障碍相关的基因研究结果。
我们通过查询相关检索词,对PubMed中从最初到目前的所有相关文献进行了检索。
通过研究,ANK3、CACNA1C、SYNE1、ODZ4和TRANK1这五个基因已被重复确认为双相情感障碍病理生理学中的关键候选基因。所识别变异解释的表型变异百分比很小(约4.7%)。双相情感障碍多基因风险评分与其他精神疾病表型相关。ENIGMA-BD研究显示,双相情感障碍患者存在可重复的皮质厚度降低、白质完整性改变和皮质下体积减小的模式。
所解释的表型变异量较低,这凸显了进一步开展大规模研究的必要性,尤其是在非欧洲人群中,以更全面地了解双相情感障碍的遗传结构和缺失的遗传度。在大规模研究中将神经成像数据与基因数据相结合,可能有助于研究人员更好地了解双相情感障碍中涉及的脑区。