jMorp: Japanese Multi-Omics Reference Panel update report 2023.

Modern medicine is increasingly focused on personalized medicine, and multi-omics data is crucial in understanding biological phenomena and disease mechanisms. Each ethnic group has its unique genetic background with specific genomic variations influencing disease risk and drug response. Therefore, multi-omics data from specific ethnic populations are essential for the effective implementation of personalized medicine. Various prospective cohort studies, such as the UK Biobank, All of Us and Lifelines, have been conducted worldwide. The Tohoku Medical Megabank project was initiated after the Great East Japan Earthquake in 2011. It collects biological specimens and conducts genome and omics analyses to build a basis for personalized medicine. Summary statistical data from these analyses are available in the jMorp web database (https://jmorp.megabank.tohoku.ac.jp), which provides a multidimensional approach to the diversity of the Japanese population. jMorp was launched in 2015 as a public database for plasma metabolome and proteome analyses and has been continuously updated. The current update will significantly expand the scale of the data (metabolome, genome, transcriptome, and metagenome). In addition, the user interface and backend server implementations were rewritten to improve the connectivity between the items stored in jMorp. This paper provides an overview of the new version of the jMorp.

COXPRESdb v8: an animal gene coexpression database navigating from a global view to detailed investigations.

Gene coexpression is synchronization of gene expression across many cellular and environmental conditions and is widely used to infer the biological function of genes. Gene coexpression information is complex, comprising a complete graph of all genes in the genome, and requires appropriate visualization and analysis tools. Since its initial release in 2007, the animal gene expression database COXPRESdb (https://coxpresdb.jp) has been continuously improved by adding new gene coexpression data and analysis tools. Here, we report COXPRESdb version 8, which has been enhanced with new features for an overview, summary, and individual examination of coexpression relationships: CoexMap to display coexpression on a genome scale, pathway enrichment analysis to summarize the function of coexpressed genes, and CoexPub to bridges coexpression and existing knowledge. COXPRESdb also facilitates downstream analyses such as interspecies comparisons by integrating RNAseq and microarray coexpression data in a union-type gene coexpression. COXPRESdb strongly support users with the new coexpression data and enhanced functionality.

The role of the STAS domain in SLC26A9 for chloride ion transporter function.

The anion exchanger solute carrier family 26 (SLC26)A9, consisting of the transmembrane (TM) domain and the cytoplasmic STAS domain, plays an essential role in regulating chloride transport across cell membranes. Recent studies have indicated that C-terminal helices block the entrance of the putative ion transport pathway. However, the precise functions of the STAS domain and C-terminal helix, as well as the underlying molecular mechanisms governing the transport process, remain poorly understood. In this study, we performed molecular dynamics simulations of three distinct models of human SLC26A9, full-length, STAS domain removal (ΔSTAS), and C-terminus removal (ΔC), to investigate their conformational dynamics and ion-binding properties. Stable binding of ions to the binding sites was exclusively observed in the ΔC model in these simulations. Comparing the full-length and ΔC simulations, the ΔC model displayed enhanced motion of the STAS domain. Furthermore, comparing the ΔSTAS and ΔC simulations, the ΔSTAS simulation failed to exhibit stable ion bindings to the sites despite the absence of the C-terminus blocking the ion transmission pathway in both systems. These results suggest that the removal of the C-terminus not only unblocks the access of ions to the permeation pathway but also triggers STAS domain motion, gating the TM domain to promote ions' entry into their binding site. Further analysis revealed that the asymmetric motion of the STAS domain leads to the expansion of the ion permeation pathway within the TM domain, resulting in the stiffening of the flexible TM12 helix near the ion-binding site. This structural change in the TM12 helix stabilizes chloride ion binding, which is essential for SLC26A9's alternate-access mechanism. Overall, our study provides new insights into the molecular mechanisms of SLC26A9 transport and may pave the way for the development of novel treatments for diseases associated with dysregulated ion transport.

Gene Rearrangement and Expression of PRKACA and PRKACB Govern Morphobiology of Pancreatobiliary Oncocytic Neoplasms.

Intraductal oncocytic papillary neoplasms (IOPNs) are distinct from intraductal papillary mucinous neoplasms based on characteristic morphologic and genetic features represented by fusion genes involving PRKACA or PRKACB (PRKACA/B). However, pancreatic and biliary tumors with partial oncocytic features are often encountered clinically, and their molecular features are yet to be clarified. This study included 80 intraductal papillary neoplasms: 32 tumors with mature IOPN morphology (typical), 28 with partial or subclonal oncocytic features (atypical), and 20 without oncocytic features (control). We analyzed PRKACA/B fusion genes, including ATP1B1::PRKACA, DNAJB1::PRKACA, and ATP1B1::PRKACB, by reverse-transcription PCR; mRNA expression of fusion genes and nonrearranged PRKACA/B genes by quantitative reverse-transcription PCR; mutations in KRAS, BRAF, and GNAS by targeted sequencing or droplet digital PCR; and the expression of cyclic adenosine monophosphate (cAMP)-dependent protein kinase catalytic subunits α (PRKACA) and ß (PRKACB), phosphorylated cAMP response element-binding protein, and aberrations of p16, p53, SMAD4, STK11, and ß-catenin by immunohistochemistry. PRKACA/B fusion genes were detected in 100% (32/32) of typical, 46% (13/28) of atypical, and 0% (0/20) of control (P < .05). Expression of PRKACA, PRKACB, and phosphorylated cAMP response element-binding protein was upregulated in neoplasms with PRKACA/B fusion genes (P < .05). mRNA expression of the PRKACA/B fusion genes and protein expression of PRKACA or PRKACB tended to be higher in typical than in atypical cases (mRNA, P = .002; protein expression, P = .054). In some atypical neoplasms with mixed subtypes, PRKACA/B fusion genes were superimposed exclusively on oncocytic components. Typical IOPNs harbored fewer KRAS and GNAS mutations than control samples and fewer alterations in p53 and STK11 than atypical samples (P < .05). In conclusion, PRKACA/B fusion genes not only are the characteristic drivers of IOPNs but also play a crucial role in the development of subclonal oncocytic neoplasms. Moreover, oncocytic morphology is strongly associated with upregulation of PRKACA/B, which may provide clues for potential therapeutic options.

Two-stage strategy using denoising autoencoders for robust reference-free genotype imputation with missing input genotypes.

Widely used genotype imputation methods are based on the Li and Stephens model, which assumes that new haplotypes can be represented by modifying existing haplotypes in a reference panel through mutations and recombinations. These methods use genotypes from SNP arrays as inputs to estimate haplotypes that align with the input genotypes by analyzing recombination patterns within a reference panel, and then infer unobserved variants. While these methods require reference panels in an identifiable form, their public use is limited due to privacy and consent concerns. One strategy to overcome these limitations is to use de-identified haplotype information, such as summary statistics or model parameters. Advances in deep learning (DL) offer the potential to develop imputation methods that use haplotype information in a reference-free manner by handling it as model parameters, while maintaining comparable imputation accuracy to methods based on the Li and Stephens model. Here, we provide a brief introduction to DL-based reference-free genotype imputation methods, including RNN-IMP, developed by our research group. We then evaluate the performance of RNN-IMP against widely-used Li and Stephens model-based imputation methods in terms of accuracy (R2), using the 1000 Genomes Project Phase 3 dataset and corresponding simulated Omni2.5 SNP genotype data. Although RNN-IMP is sensitive to missing values in input genotypes, we propose a two-stage imputation strategy: missing genotypes are first imputed using denoising autoencoders; RNN-IMP then processes these imputed genotypes. This approach restores the imputation accuracy that is degraded by missing values, enhancing the practical use of RNN-IMP.

Dietary habits and plasma lipid concentrations in a general Japanese population.

INTRODUCTION: Accumulating data on the associations between food consumption and lipid composition in the body is essential for understanding the effects of dietary habits on health. OBJECTIVES: As part of omics research in the Tohoku Medical Megabank Community-Based Cohort Study, this study sought to reveal the dietary impact on plasma lipid concentration in a Japanese population. METHODS: We conducted a correlation analysis of food consumption and plasma lipid concentrations measured using mass spectrometry, for 4032 participants in Miyagi Prefecture, Japan. RESULTS: Our analysis revealed 83 marked correlations between six food categories and the concentrations of plasma lipids in nine subclasses. Previously reported associations, including those between seafood consumption and omega-3 fatty acids, were validated, while those between dairy product consumption and odd-carbon-number fatty acids (odd-FAs) were validated for the first time in an Asian population. Further analysis suggested that dairy product consumption is associated with odd-FAs via sphingomyelin (SM), which suggests that SM is a carrier of odd-FAs. These results are important for understanding odd-FA metabolism with regards to dairy product consumption. CONCLUSION: This study provides insight into the dietary impact on plasma lipid concentration in a Japanese population.

GWAS meta-analysis of kidney function traits in Japanese populations.

BACKGROUND: Genetic epidemiological evidence for the kidney function traits in East Asian population including Japanese remain still relatively unclarified. Especially, the number of GWASs for kidney traits reported still remains limited, and the sample size of each independent study is relatively small. Given the genetic variability between ancestries/ethnicities, implementation of GWAS with sufficiently large sample sizes in specific population of Japanese is considered meaningful. METHODS: We conducted the GWAS meta-analyses of kidney traits by leveraging the GWAS summary data of the representative large genome cohort studies with about 200,000 Japanese participants (n = 202,406 for estimated glomerular filtration rate [eGFR] and n = 200,845 for serum creatinine [SCr]). RESULTS: In the present GWAS meta-analysis, we identified 110 loci with 169 variants significantly associated with eGFR (on chromosomes 1-13 and 15-22; p < 5×10-8), whereas we also identified 112 loci with 176 variants significantly associated with SCr (on chromosomes 1-22; p < 5×10-8), of which one locus (more than 1Mb distant from known loci) with one variant (CD36 rs146148222 on chromosome 7) for SCr was considered as the truly novel finding. CONCLUSIONS: The present GWAS meta-analysis of largest genome cohort studies in Japanese provided some original genomic loci associated with kidney function in Japanese, which may contribute to the possible development of personalized prevention of kidney diseases based on genomic information in the near future.

Progress report of the Tohoku Medical Megabank Community-Based Cohort Study: Study profile of the repeated center-based survey during second period in Miyagi Prefecture.

BACKGROUND: The purpose of this study was to report the basic profile of the Miyagi Prefecture part of a repeated center-based survey during the second period (2nd period survey) of the Tohoku Medical Megabank Community-Based Cohort Study (TMM CommCohort Study), as well as the participants' characteristics based on their participation type in the baseline survey. METHODS: The 2nd period survey, conducted from June 2017 to March 2021, included participants of the TMM CommCohort Study (May 2013 to March 2016). In addition to the questionnaire, blood, urine, and physiological function tests were performed during the 2nd period survey. There were three main ways of participation in the baseline survey: Type 1, Type 1 additional, or Type 2 survey. The 2nd period survey was conducted in the same manner as the Type 2 survey, which was based on the community support center (CSC). RESULTS: In Miyagi Prefecture, 29,383 (57.7%) of 50,967 participants participated in the 2nd period survey. The participation rate among individuals who had visited the CSC was approximately 80%. Although some factors differed depending on the participation type in the baseline survey, the 2nd period survey respondents in the Type 1 and Type 2 survey groups at baseline had similar traits. CONCLUSIONS: The 2nd period survey of the TMM CommCohort Study provided detailed follow-up information. Following up on the health conditions of the participants will clarify the long-term effects of disasters and contribute to personalized prevention.

Study Profile of the Tsuruoka Metabolomics Cohort Study (TMCS).

The Tsuruoka Metabolomics Cohort Study (TMCS) is an ongoing population-based cohort study being conducted in the rural area of Yamagata Prefecture, Japan. This study aimed to enhance the precision prevention of multi-factorial, complex diseases, including non-communicable and aging-associated diseases, by improving risk stratification and prediction measures. At baseline, 11,002 participants aged 35-74 years were recruited in Tsuruoka City, Yamagata Prefecture, Japan, between 2012 and 2015, with an ongoing follow-up survey. Participants underwent various measurements, examinations, tests, and questionnaires on their health, lifestyle, and social factors. This study used an integrative approach with deep molecular profiling to identify potential biomarkers linked to phenotypes that underpin disease pathophysiology and provide better mechanistic insights into social health determinants. The TMCS incorporates multi-omics data, including genetic and metabolomic analyses of 10,933 participants and comprehensive data collection ranging from physical, psychological, behavioral, and social to biological data. The metabolome is used as a phenotypic probe because it is sensitive to changes in physiological and external conditions. The TMCS focuses on collecting outcomes for cardiovascular disease, cancer incidence and mortality, disability, functional decline due to aging and disease sequelae, and the variation in health status within the body represented by omics analysis that lies between exposure and disease. It contains several sub-studies on aging, heated tobacco products, and women's health. This study is notable for its robust design, high participation rate (89%), and long-term repeated surveys. Moreover, it contributes to precision prevention in Japan and East Asia as a well-established multi-omics platform.

Effects of NRF2 polymorphisms on safety and efficacy of bardoxolone methyl: subanalysis of TSUBAKI study.

BACKGROUND: In the TSUBAKI study, bardoxolone methyl significantly increased measured and estimated glomerular filtration rates (GFR) in patients with multiple forms of chronic kidney disease (CKD), including Japanese patients with type 2 diabetes and stage 3-4 CKD. Since bardoxolone methyl targets the nuclear factor erythroid 2-related factor 2 pathway, this exploratory analysis of the TSUBAKI study investigated the impact of the regulatory single nucleotide polymorphism, rs6721961, on the effects of bardoxolone methyl. METHODS: Japanese patients aged 20-79 years with type 2 diabetes and stage 3-4 CKD were randomized to bardoxolone methyl 5-15 mg/day (titrated as tolerated) or placebo for 16 weeks. Genotype frequency, clinical characteristics, renal function, and adverse events were primarily assessed. RESULTS: Of 104 patients (bardoxolone methyl n = 55, placebo n = 49); 57% were genotype C/C, 32% C/A and 12% A/A. The frequency of the A/A genotype was higher among patients with diabetic kidney disease than in the general Japanese population (~ 5%). Measured and estimated GFRs increased from baseline in all genotypes receiving bardoxolone methyl. There were no significant differences between genotypes for safety parameters, including blood pressure, bodyweight, and levels of B-type natriuretic peptide, or in the type and frequency of adverse events, suggesting that the efficacy and safety of bardoxolone methyl are unaffected by the rs6721961 polymorphism-617 (C→A) genotype. CONCLUSIONS: Our approach of combining genome analysis with clinical trials for an investigational drug provides important and useful clues for exploring the efficacy and safety of the drug. TRIAL REGISTRATION: ClinicalTrials.gov; NCT02316821.

Multi-Omics Profiling Reveals Phenotypic and Functional Heterogeneity of Neutrophils in COVID-19.

Accumulating evidence has revealed unexpected phenotypic heterogeneity and diverse functions of neutrophils in several diseases. Coronavirus disease (COVID-19) can alter the leukocyte phenotype based on disease severity, including neutrophil activation in severe cases. However, the plasticity of neutrophil phenotypes and their relative impact on COVID-19 pathogenesis has not been well addressed. This study aimed to identify and validate the heterogeneity of neutrophils in COVID-19 and evaluate the functions of each subpopulation. We analyzed public single-cell RNA-seq, bulk RNA-seq, and proteome data from healthy donors and patients with COVID-19 to investigate neutrophil subpopulations and their response to disease pathogenesis. We identified eight neutrophil subtypes: pro-neutrophil, pre-neutrophil, immature neutrophil, and five mature neutrophil subpopulations. The subtypes exhibited distinct features, including diverse activation signatures and multiple enriched pathways. The pro-neutrophil subtype was associated with severe and fatal disease, while the pre-neutrophil subtype was particularly abundant in mild/moderate disease. One of the mature neutrophil subtypes showed consistently large fractions in patients with different disease severity. Bulk RNA-seq dataset analyses using a cellular deconvolution approach validated the relative abundances of neutrophil subtypes and the expansion of pro-neutrophils in severe COVID-19 patients. Cell-cell communication analysis revealed representative ligand-receptor interactions among the identified neutrophil subtypes. Further investigation into transcription factors and differential protein abundance revealed the regulatory network differences between healthy donors and patients with severe COVID-19. Overall, we demonstrated the complex interactions among heterogeneous neutrophil subtypes and other blood cell types during COVID-19 disease. Our work has great value in terms of both clinical and public health as it furthers our understanding of the phenotypic and functional heterogeneity of neutrophils and other cell populations in multiple diseases.

Decreased ß-hydroxybutyrate and ketogenic amino acid levels in depressed human adults.

ß-hydroxybutyrate (BHB) is a major ketone body synthesized mainly in the liver mitochondria and is associated with stress and severity of depression in humans. It is known to alleviate depressive-like behaviors in mouse models of depression. In this study, plasma BHB, ketogenic and glucogenic amino acids selected from the Tohoku Medical Megabank Project Community-Based Cohort Study were analysed and measured using nuclear magnetic resonance spectroscopy. The Center for Epidemiologic Studies Depression Scale (CES-D) was utilized to select adult participants with depressive symptoms (CES-D ≥ 16; n = 5722) and control participants (CES-D < 16; n = 18,150). We observed significantly reduced plasma BHB, leucine, and tryptophan levels in participants with depressive symptoms. Using social defeat stress (SDS) mice models, we found that BHB levels in mice sera increased after acute SDS, but showed no change after chronic SDS, which differed from human plasma results. Furthermore, acute SDS increased mitochondrial BHB levels in the prefrontal cortex at 6 h. In contrast, chronic SDS significantly increased the amount of food intake but reduced hepatic mitochondrial BHB levels in mice. Moreover, gene transcriptions of voltage-dependent anion-selective channel 1 (Vdac1) and monocarboxylic acid transporter 1 (Mct1), major molecules relevant to mitochondrial biogenesis and BHB transporter, significantly decreased in the liver and PFC after chronic SDS exposure. These results provide evidence that hepatic and prefrontal mitochondrial biogenesis plays an important role in BHB synthesis under chronic stress and in humans with depressive symptoms.

Functional Characterization of 12 Dihydropyrimidinase Allelic Variants in Japanese Individuals for the Prediction of 5-Fluorouracil Treatment-Related Toxicity.

The drug 5-fluorouracil (5-FU) is the first-choice chemotherapeutic agent against advanced-stage cancers. However, 10% to 30% of treated patients experience grade 3 to 4 toxicity. The deficiency of dihydropyrimidinase (DHPase), which catalyzes the second step of the 5-FU degradation pathway, is correlated with the risk of developing toxicity. Thus, genetic polymorphisms within DPYS, the DHPase-encoding gene, could potentially serve as predictors of severe 5-FU-related toxicity. We identified 12 novel DPYS variants in 3554 Japanese individuals, but the effects of these mutations on function remain unknown. In the current study, we performed in vitro enzymatic analyses of the 12 newly identified DHPase variants. Dihydrouracil or dihydro-5-FU hydrolytic ring-opening kinetic parameters, Km and Vmax , and intrinsic clearance (CLint = Vmax /Km ) of the wild-type DHPase and eight variants were measured. Five of these variants (R118Q, H295R, T418I, Y448H, and T513A) showed significantly reduced CLint compared with that in the wild-type. The parameters for the remaining four variants (V59F, D81H, T136M, and R490H) could not be determined as dihydrouracil and dihydro-5-FU hydrolytic ring-opening activity was undetectable. We also determined DHPase variant protein stability using cycloheximide and bortezomib. The mechanism underlying the observed changes in the kinetic parameters was clarified using blue-native polyacrylamide gel electrophoresis and three-dimensional structural modeling. The results suggested that the decrease or loss of DHPase enzymatic activity was due to reduced stability and oligomerization of DHPase variant proteins. Our findings support the use of DPYS polymorphisms as novel pharmacogenomic markers for predicting severe 5-FU-related toxicity in the Japanese population. SIGNIFICANCE STATEMENT: DHPase contributes to the degradation of 5-fluorouracil, and genetic polymorphisms that cause decreased activity of DHPase can cause severe toxicity. In this study, we performed functional analysis of 12 DHPase variants in the Japanese population and identified 9 genetic polymorphisms that cause reduced DHPase function. In addition, we found that the ability to oligomerize and the conformation of the active site are important for the enzymatic activity of DHPase.

Functional Characterization of 29 Cytochrome P450 4F2 Variants Identified in a Population of 8380 Japanese Subjects and Assessment of Arachidonic Acid ω-Hydroxylation.

Cytochrome P450 4F2 (CYP4F2) is an enzyme that is involved in the metabolism of arachidonic acid (AA), vitamin E and K, and xenobiotics including drugs. CYP4F2*3 polymorphism (rs2108622; c.1297G>A; p.Val433Met) has been associated with hypertension, ischemic stroke, and variation in the effectiveness of the anticoagulant drug warfarin. In this study, we characterized wild-type CYP4F2 and 28 CYP4F2 variants, including a Val433Met substitution, detected in 8380 Japanese subjects. The CYP4F2 variants were heterologously expressed in 293FT cells to measure the concentrations of CYP4F2 variant holoenzymes using carbon monoxide-reduced difference spectroscopy, where the wild type and 18 holoenzyme variants showed a peak at 450 nm. Kinetic parameters [Vmax , substrate concentration producing half of Vmax (S50 ), and intrinsic clearance (CL int ) as Vmax /S50 ] of AA ω-hydroxylation were determined for the wild type and 21 variants with enzyme activity. Compared with the wild type, two variants showed significantly decreased CL int values for AA ω-hydroxylation. The values for seven variants could not be determined because no enzymatic activity was detected at the highest substrate concentration used. Three-dimensional structural modeling was performed to determine the reason for reduced enzymatic activity of the CYP4F2 variants. Our findings contribute to a better understanding of CYP4F2 variant-associated diseases and possible future therapeutic strategies. SIGNIFICANCE STATEMENT: CYP4F2 is involved in the metabolism of arachidonic acid and vitamin K, and CYP4F2*3 polymorphisms have been associated with hypertension and variation in the effectiveness of the anticoagulant drug warfarin. This study presents a functional analysis of 28 CYP4F2 variants identified in Japanese subjects, demonstrating that seven gene polymorphisms cause loss of CYP4F2 function, and proposes structural changes that lead to altered function.

Establishment of the early prediction models of low-birth-weight reveals influential genetic and environmental factors: a prospective cohort study.

BACKGROUND: Low birth weight (LBW) is a leading cause of neonatal morbidity and mortality, and increases various disease risks across life stages. Prediction models of LBW have been developed before, but have limitations including small sample sizes, absence of genetic factors and no stratification of neonate into preterm and term birth groups. In this study, we challenged the development of early prediction models of LBW based on environmental and genetic factors in preterm and term birth groups, and clarified influential variables for LBW prediction. METHODS: We selected 22,711 neonates, their 21,581 mothers and 8,593 fathers from the Tohoku Medical Megabank Project Birth and Three-Generation cohort study. To establish early prediction models of LBW for preterm birth and term birth groups, we trained AI-based models using genetic and environmental factors of lifestyles. We then clarified influential environmental and genetic factors for predicting LBW in the term and preterm groups. RESULTS: We identified 2,327 (10.22%) LBW neonates consisting of 1,077 preterm births and 1,248 term births. Our early prediction models archived the area under curve 0.96 and 0.95 for term LBW and preterm LBW models, respectively. We revealed that environmental factors regarding eating habits and genetic features related to fetal growth were influential for predicting LBW in the term LBW model. On the other hand, we identified that genomic features related to toll-like receptor regulations and infection reactions are influential genetic factors for prediction in the preterm LBW model. CONCLUSIONS: We developed precise early prediction models of LBW based on lifestyle factors in the term birth group and genetic factors in the preterm birth group. Because of its accuracy and generalisability, our prediction model could contribute to risk assessment of LBW in the early stage of pregnancy and control LBW risk in the term birth group. Our prediction model could also contribute to precise prediction of LBW based on genetic factors in the preterm birth group. We then identified parental genetic and maternal environmental factors during pregnancy influencing LBW prediction, which are major targets for understanding the LBW to address serious burdens on newborns' health throughout life.

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

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.

Identification of predictive biomarkers for diagnosis and radiation sensitivity of uterine cervical cancer using wide-targeted metabolomics.

AIM: Uterine cervical cancer (UCC) is the fourth most common cancer in women, responsible for more than 300 000 deaths worldwide. Its early detection, by cervical cytology, and prevention, by vaccinating against human papilloma virus, greatly contribute to reducing cervical cancer mortality in women. However, penetration of the effective prevention of UCC in Japan remains low. Plasma metabolome analysis is widely used for biomarker discovery and the identification of cancer-specific metabolic pathways. Here, we aimed to identify predictive biomarkers for the diagnosis and radiation sensitivity of UCC using wide-targeted plasma metabolomics. METHODS: We analyzed 628 metabolites in plasma samples obtained from 45 patients with UCC using ultra-high-performance liquid chromatography with tandem mass spectrometry. RESULTS: The levels of 47 metabolites were significantly increased and those of 75 metabolites were significantly decreased in patients with UCC relative to healthy controls. Increased levels of arginine and ceramides, and decreased levels of tryptophan, ornithine, glycosylceramides, lysophosphatidylcholine, and phosphatidylcholine were characteristic of patients with UCC. Comparison of metabolite profiles in groups susceptible and non-susceptible to radiation therapy, a treatment for UCC, revealed marked variations in polyunsaturated fatty acid, nucleic acid, and arginine metabolism in the group not susceptible to treatment. CONCLUSIONS: Our findings suggest that the metabolite profile of patients with UCC may be an important indicator for distinguishing these patients from healthy cohorts, and may also be useful for predicting sensitivity to radiotherapy.

High levels of chromosomal instability facilitate the tumor growth and sphere formation.

Most cancer cells show chromosomal instability (CIN), a condition in which chromosome missegregation occurs at high rates. Growing evidence suggests that CIN is not just a consequence of, but a driving force for, oncogenic transformation, although the relationship between CIN and tumorigenesis has not been fully elucidated. Here we found that conventional two-dimensional (2D) culture of HeLa cells, a cervical cancer-derived cell line, was a heterogenous population containing cells with different CIN levels. Although cells with high-CIN levels (high-CIN cells) grew more slowly compared with cells with low-CIN levels (low-CIN cells) in 2D monolayer culture, they formed tumors in nude mice and larger spheres in three-dimensional (3D) culture, which was more representative of the in vivo environment. The duration of mitosis was longer in high-CIN cells, reflecting their higher mitotic defects. Single-cell genome sequencing revealed that high-CIN cells exhibited a higher karyotype heterogeneity compared with low-CIN cells. Intriguingly, the karyotype heterogeneity was reduced in the spheres formed by high-CIN cells, suggesting that cells with growth advantages were selected, although genomic copy number changes specific for spheres were not identified. When we examined gene expression profiles, genes related to the K-ras signaling were upregulated, while those related to the unfolded protein response were downregulated in high-CIN cells in 3D culture compared with 2D culture, suggesting the relevance of these genes for their survival. Our data suggested that, although CIN is disadvantageous in monolayer culture, it promotes the selection of cells with growth advantages under in vivo environments, which may lead to tumorigenesis.

ATTED-II v11: A Plant Gene Coexpression Database Using a Sample Balancing Technique by Subagging of Principal Components.

ATTED-II (https://atted.jp) is a gene coexpression database for nine plant species based on publicly available RNAseq and microarray data. One of the challenges in constructing condition-independent coexpression data based on publicly available gene expression data is managing the inherent sampling bias. Here, we report ATTED-II version 11, wherein we adopted a coexpression calculation methodology to balance the samples using principal component analysis and ensemble calculation. This approach has two advantages. First, omitting principal components with low contribution rates reduces the main contributors of noise. Second, balancing large differences in contribution rates enables considering various sample conditions entirely. In addition, based on RNAseq- and microarray-based coexpression data, we provide species-representative, integrated coexpression information to enhance the efficiency of interspecies comparison of the coexpression data. These coexpression data are provided as a standardized z-score to facilitate integrated analysis with different data sources. We believe that with these improvements, ATTED-II is more valuable and powerful for supporting interspecies comparative studies and integrated analyses using heterogeneous data.

The return of individual genomic results to research participants: design and pilot study of Tohoku Medical Megabank Project.

Certain large genome cohort studies attempt to return the individual genomic results to the participants; however, the implementation process and psychosocial impacts remain largely unknown. The Tohoku Medical Megabank Project has conducted large genome cohort studies of general residents. To implement the disclosure of individual genomic results, we extracted the potential challenges and obstacles. Major challenges include the determination of genes/disorders based on the current medical system in Japan, the storage of results, prevention of misunderstanding, and collaboration of medical professionals. To overcome these challenges, we plan to conduct multilayer pilot studies, which deal with different disorders/genes. We finally chose familial hypercholesterolemia (FH) as a target disease for the first pilot study. Of the 665 eligible candidates, 33.5% were interested in the pilot study and provided consent after an educational "genetics workshop" on the basic genetics and medical facts of FH. The genetics professionals disclosed the results to the participants. All positive participants were referred to medical care, and a serial questionnaire revealed no significant psychosocial distress after the disclosure. Return of genomic results to research participants was implemented using a well-prepared protocol. To further elucidate the impact of different disorders, we will perform multilayer pilot studies with different disorders, including actionable pharmacogenomics and hereditary tumor syndromes.