Yu Chenglong, Baune Bernhard T, Licinio Julio, Wong Ma-Li
Mind and Brain Theme, South Australian Health and Medical Research Institute, North Terrace, Adelaide, SA 5000, Australia; School of Medicine, Flinders University, Bedford Park, SA 5042, Australia.
Discipline of Psychiatry, School of Medicine, University of Adelaide, Adelaide, SA 5005, Australia.
Psychiatry Res. 2017 Jun;252:75-79. doi: 10.1016/j.psychres.2017.02.041. Epub 2017 Feb 20.
Recent advances in DNA technologies have provided unprecedented opportunities for biological and medical research. In contrast to current popular genotyping platforms which identify specific variations, whole-genome sequencing (WGS) allows for the detection of all private mutations within an individual. Major depressive disorder (MDD) is a chronic condition with enormous medical, social and economic impacts. Genetic analysis, by identifying risk variants and thereby increasing our understanding of how MDD arises, could lead to improved prevention and the development of new and more effective treatments. Here we investigated the distributions of whole-genome single nucleotide variants (SNVs) on 12 different genomic regions for 25 human subjects using the symmetrised Kullback-Leibler divergence to measure the similarity between their SNV distributions. We performed cluster analysis for MDD patients and ethnically matched healthy controls. The results showed that Mexican-American controls grouped closer; in contrast depressed Mexican-American participants grouped away from their ethnically matched controls. This implies that whole-genome SNV distribution on the genomic regions may be related to major depression.
DNA技术的最新进展为生物学和医学研究提供了前所未有的机遇。与目前流行的识别特定变异的基因分型平台不同，全基因组测序（WGS）能够检测个体内所有的私人突变。重度抑郁症（MDD）是一种具有巨大医学、社会和经济影响的慢性疾病。通过识别风险变异，从而增进我们对MDD发病机制的理解，基因分析可能会改善预防措施，并推动新的、更有效的治疗方法的开发。在这里，我们使用对称化的库尔贝克-莱布勒散度来衡量25名人类受试者12个不同基因组区域上全基因组单核苷酸变异（SNV）的分布，以测量它们的SNV分布之间的相似性。我们对MDD患者和种族匹配的健康对照进行了聚类分析。结果显示，墨西哥裔美国对照组聚集得更近；相比之下，抑郁的墨西哥裔美国参与者与他们种族匹配的对照组分开聚类。这意味着基因组区域上的全基因组SNV分布可能与重度抑郁症有关。
