jMorp updates in 2020: large enhancement of multi-omics data resources on the general Japanese population

Abstract

In the Tohoku Medical Megabank project, genome and omics analyses of participants in two cohort studies were performed. A part of the data is available at the Japanese Multi Omics Reference Panel (jMorp; https://jmorp.megabank.tohoku.ac.jp) as a web-based database, as reported in our previous manuscript published in Nucleic Acid Research in 2018. At that time, jMorp mainly consisted of metabolome data; however, now genome, methylome, and transcriptome data have been integrated in addition to the enhancement of the number of samples for the metabolome data. For genomic data, jMorp provides a Japanese reference sequence obtained using de novo assembly of sequences from three Japanese individuals and allele frequencies obtained using whole-genome sequencing of 8,380 Japanese individuals. In addition, the omics data include methylome and transcriptome data from ∼300 samples and distribution of concentrations of more than 755 metabolites obtained using high-throughput nuclear magnetic resonance and high-sensitivity mass spectrometry. In summary, jMorp now provides four different kinds of omics data (genome, methylome, transcriptome, and metabolome), with a user-friendly web interface. This will be a useful scientific data resource on the general population for the discovery of disease biomarkers and personalized disease prevention and early diagnosis.

Wide-Targeted Metabolome Analysis Identifies Potential Biomarkers for Prognosis Prediction of Epithelial Ovarian Cancer

“…The metabolome data of EOC patients were compared to those of the ToMMo cohort matched for age, height, weight, and BMI [ 45 , 46 ]. Data normalization was based on the median of gQC of each plate (four replicates/plate).…”

Comparison of Kit-Based Metabolomics with Other Methodologies in a Large Cohort, towards Establishing Reference Values

“…Metabolic profiling in plasma samples has been widely performed via Kit-Met in several large-scale cohort studies, such as EPIC (European Prospective Investigation into Cancer and Nutrition) [ 30 , 43 , 44 ] and KORA (Cooperative Health Research in the Region of Augsburg) [ 31 ], and biomarker candidates have been reported to predict disease expression and progression when a previous version of this kit (AbsoluteIDQ p180 Kit, kit180) was used. In fact, kit180 stably quantified 110 metabolites in 10 μL plasma samples within a large-scale analysis in our previous study [ 38 ]. The current version, Kit-Met, increased the number of quantified metabolites by more than 600, and therefore, Kit-Met was utilized by the UHPLC-MS/MS system.…”

“…One of the main goals of this cohort was to identify predictive biomarkers of disease expression for future precision medicine by using metabolic profiling techniques combined with other datasets, such as genomics, phenotypes, and/or habitudes [ 36 , 37 ]. During this large-scale cohort metabolic profiling project, forty-five metabolites from more than 30,000 plasma samples were analyzed by NMR, 110 metabolites from approximately 2000 plasma samples and 421 metabolites from approximately 2300 plasma samples were analyzed by Kit-Met [ 6 ], and their quantified values were included in the commercial database “Japanese Multi Omics Reference Panel, jMorp” [ 38 ]. The database has expanded both the number of samples and the number of quantified metabolites, and the quantified values from cohort participants could potentially be utilized as references for biomarker discovery studies.…”

Two Approaches for a Genetic Analysis of Pompe Disease: A Literature Review of Patients with Pompe Disease and Analysis Based on Genomic Data from the General Population

“…In the present study, GAA genetic variants found in KRGDB (30× coverage group, 1465 individuals) were analyzed. In addition, the Japanese Multi Omics Reference Panel (jMorp, , accessed on 16 March 2021) was used to analyze GAA variants in the Japanese general population [ 6 , 7 ]. To date, the jMorp database contains the genomic data (whole-genome sequencing data) of 8380 Japanese individuals.…”