Rout Madhusmita, Kour Bhumandeep, Vuree Sugunakar, Lulu Sajitha S, Medicherla Krishna Mohan, Suravajhala Prashanth
Department of Pediatrics, University of Oklahoma Health Sciences Centre, Oklahoma City, OK 73104, United States.
Department of Biotechnology, Lovely Professional University, Phagwara 144001, Punjab, India.
World J Clin Cases. 2022 Jun 26;10(18):5957-5964. doi: 10.12998/wjcc.v10.i18.5957.
An emerging area of interest in understanding disease phenotypes is systems genomics. Complex diseases such as diabetes have played an important role towards understanding the susceptible genes and mutations. A wide number of methods have been employed and strategies such as polygenic risk score and allele frequencies have been useful, but understanding the candidate genes harboring those mutations is an unmet goal. In this perspective, using systems genomic approaches, we highlight the application of phenome-interactome networks in diabetes and provide deep insights. LINC01128, which we previously described as candidate for diabetes, is shown as an example to discuss the approach.
系统基因组学是理解疾病表型中一个新兴的研究领域。糖尿病等复杂疾病在理解易感基因和突变方面发挥了重要作用。人们已经采用了大量方法,多基因风险评分和等位基因频率等策略也很有用,但了解携带这些突变的候选基因仍是一个尚未实现的目标。从这个角度来看,我们运用系统基因组学方法,重点介绍了表型-相互作用组网络在糖尿病中的应用,并提供了深入见解。我们以之前描述为糖尿病候选基因的LINC01128为例来讨论这种方法。