Laboratory of Genetics, Department of Biotechnology, Agricultural University of Athens, 11855 Athens, Greece.
Section of Molecular Pathology and Human Genetics, Department of Internal Medicine, School of Medicine, University of Crete, 71003 Heraklion, Greece.
Int J Mol Med. 2021 Jun;47(6). doi: 10.3892/ijmm.2021.4948. Epub 2021 Apr 28.
Demetra Application is a holistic integrated and scalable bioinformatics web‑based tool designed to assist medical experts and researchers in the process of diagnosing endometriosis. The application identifies the most prominent gene variants and single nucleotide polymorphisms (SNPs) causing endometriosis using the genomic data provided for the patient by a medical expert. The present study analyzed >28.000 endometriosis‑related publications using data mining and semantic techniques aimed towards extracting the endometriosis‑related genes and SNPs. The extracted knowledge was filtered, evaluated, annotated, classified, and stored in the Demetra Application Database (DAD). Moreover, an updated gene regulatory network with the genes implements in endometriosis was established. This was followed by the design and development of the Demetra Application, in which the generated datasets and results were included. The application was tested and presented herein with whole‑exome sequencing data from seven related patients with endometriosis. Endometriosis‑related SNPs and variants identified in genome‑wide association studies (GWAS), whole‑genome (WGS), whole‑exome (WES), or targeted sequencing information were classified, annotated and analyzed in a consolidated patient profile with clinical significance information. Probable genes associated with the patient's genomic profile were visualized using several graphs, including chromosome ideograms, statistic bars and regulatory networks through data mining studies with relative publications, in an effort to obtain a representative number of the most credible candidate genes and biological pathways associated with endometriosis. An evaluation analysis was performed on seven patients from a three‑generation family with endometriosis. All the recognized gene variants that were previously considered to be associated with endometriosis were properly identified in the output profile per patient, and by comparing the results, novel findings emerged. This novel and accessible webserver tool of endometriosis to assist medical experts in the clinical genomics and precision medicine procedure is available at http://geneticslab.aua.gr/.
Demetra 应用程序是一个整体的、集成的和可扩展的生物信息学网络工具，旨在协助医学专家和研究人员进行子宫内膜异位症的诊断。该应用程序使用医学专家为患者提供的基因组数据来识别导致子宫内膜异位症的最突出的基因变异和单核苷酸多态性（SNP）。本研究使用数据挖掘和语义技术分析了超过 28000 篇与子宫内膜异位症相关的文献，旨在提取与子宫内膜异位症相关的基因和 SNP。提取的知识经过过滤、评估、注释、分类和存储在 Demetra 应用程序数据库（DAD）中。此外，还建立了一个带有子宫内膜异位症相关基因的更新的基因调控网络。之后，设计和开发了 Demetra 应用程序，其中包括生成的数据集和结果。该应用程序已经过测试，并在此展示了来自 7 名相关子宫内膜异位症患者的全外显子组测序数据。在全基因组关联研究（GWAS）、全基因组（WGS）、全外显子组（WES）或靶向测序信息中识别的与子宫内膜异位症相关的 SNP 和变体，在具有临床意义信息的综合患者档案中进行分类、注释和分析。通过相对出版物的数据挖掘研究，使用几个图（包括染色体图谱、统计条形图和调控网络）可视化与患者基因组谱相关的可能基因，以获得与子宫内膜异位症相关的最可信候选基因和生物学途径的代表性数量。对来自一个三代子宫内膜异位症家庭的 7 名患者进行了评估分析。每个患者的输出档案中都正确识别了先前被认为与子宫内膜异位症相关的所有识别出的基因变异，通过比较结果，出现了新的发现。这个新的、易于访问的子宫内膜异位症网络服务器工具旨在协助医学专家进行临床基因组学和精准医学程序，可在 http://geneticslab.aua.gr/ 获得。
