Genome-wide Association Study of Axial Length in Population-based Cohorts in Japan

Purpose

To elucidate the differences in ocular biometric parameters by generation and gender and to identify axial length (AL)-associated genetic variants in Japanese individuals, we analyzed Tohoku Medical Megabank Organization (ToMMo) Eye Study data.

Design

We designed the ToMMo Eye Study, examined AL variations, and conducted genome-wide association studies (GWASs).

Participants

In total, 33 483 participants aged > 18 years who were recruited into the community-based cohort (CommCohort) and the birth and three-generation cohort (BirThree Cohort) of the ToMMo Eye Study were examined.

Methods

Each participant was screened with an interview, ophthalmic examinations, and a microarray analysis. The GWASs were performed in 22 379 participants in the CommCohort (discovery stage) and 11 104 participants in the BirThree Cohort (replication stage). We evaluated the associations of single nucleotide polymorphisms (SNPs) with AL using a genome-wide significance threshold (5 × 10^-8) in each stage of the study and in the subsequent meta-analysis.

Main Outcome Measures

We identified the association of SNPs with AL and distributions of AL in right and left eyes and individuals of different sexes and ages.

Results

In the discovery stage, the mean AL of the right eye (23.99 mm) was significantly greater than that of the left eye (23.95 mm). This difference was reproducible across sexes and ages. The GWASs revealed 703 and 215 AL-associated SNPs with genome-wide significance in the discovery and validation stages, respectively, and many of the SNPs in the discovery stage were replicated in the validation stage. Validated SNPs and their associated loci were meta-analyzed for statistical significance (P < 5 × 10^-8). This study identified 1478 SNPs spread over 31 loci. Of the 31 loci, 5 are known AL loci, 15 are known refractive-error loci, 4 are known corneal-curvature loci, and 7 loci are newly identified loci that are not known to be associated with AL. Of note, some of them shared functional relationships with previously identified loci.

Conclusions

Our large-scale GWASs exploiting ToMMo Eye Study data identified 31 loci linked to variations in AL, 7 of which are newly reported in this article. The results revealed genetic heterogeneity and similarity in SNPs related to ethnic variations in AL.

Design and Progress of Oral Health Examinations in the Tohoku Medical Megabank Project

In order to assess the long-term impact of the Great East Japan Earthquake on the oral health of disaster victims and to evaluate gene-environmental interactions in the development of major oral diseases and oral-systemic associations, the oral part of two large-scale genome cohort studies by the Tohoku Medical Megabank Organization (ToMMo), including the Community-based cohort (CommCohort) study and the Birth and Three-Generation cohort (BirThree) study, have been conducted. The study population comprised 32,185 subjects, including 16,886 participants in the CommCohort study and 15,299 participants in the BirThree cohort study, recruited from 2013 to 2017. The oral studies consist of a questionnaire regarding oral hygiene behavior, clinical examinations by dentists, and oral plaque and saliva sampling for microbiome analyses, which were carried out at seven community support centers in Miyagi prefecture. The median age of all participants was 55.0 years, and 66.1% of participants were women. Almost all participants reported that they brushed their teeth more than once a day. The median number of present teeth was 27.0, and the decayed, missing and filled tooth number was 16.0, with a significant difference according to age and sex. The median periodontal pocket and clinical attachment level was 2.48 mm and 4.00 mm, respectively. Periodontal parameters increased significantly according to age, except for the accumulation of dental calculus. The oral part of these extensive cross-sectional studies provides a unique and important platform for future studies on oral health and diseases that elicit through interactions with systemic diseases, lifestyles, life events and genetic backgrounds, and contributes to researches clarifying the long-term effects of disasters on oral health.

Outlier detection for questionnaire data in biobanks

BACKGROUND

Biobanks increasingly collect, process and store omics with more conventional epidemiologic information necessitating considerable effort in data cleaning. An efficient outlier detection method that reduces manual labour is highly desirable.

METHOD

We develop an unsupervised machine-learning method for outlier detection, namely kurPCA, that uses principal component analysis combined with kurtosis to ascertain the existence of outliers. In addition, we propose a novel regression adjustment approach to improve detection, namely the regression adjustment for data by systematic missing patterns (RAMP).

RESULT

Application to epidemiological record data in a large-scale biobank (Tohoku Medical Megabank Organization, Japan) shows that a combination of kurPCA and RAMP effectively detects known errors or inconsistent patterns.

CONCLUSIONS

We confirm through the results of the simulation and the application that our methods showed good performance. The proposed methods are useful for many practical analysis scenarios.

Identification of a novel uterine leiomyoma GWAS locus in a Japanese population

Uterine leiomyoma is one of the most common gynaecologic benign tumours, but its genetic basis remains largely unknown. Six previous GWAS identified 33 genetic factors in total. Here, we performed a two-staged GWAS using 13,746 cases and 70,316 controls from the Japanese population, followed by a replication analysis using 3,483 cases and 4,795 controls. The analysis identified 9 significant loci, including a novel locus on 12q23.2 (rs17033114, P = 6.12 × 10^-25 with an OR of 1.177 (1.141-1.213), LINC00485). Subgroup analysis indicated that 5 loci (3q26.2, 5p15.33, 10q24.33, 11p15.5, 13q14.11) exhibited a statistically significant effect among multiple leiomyomas, and 2 loci (3q26.2, 10q24.33) exhibited a significant effect among submucous leiomyomas. Pleiotropic analysis indicated that all 9 loci were associated with at least one proliferative disease, suggesting the role of these loci in the common neoplastic pathway. Furthermore, the risk T allele of rs2251795 (3q26.2) was associated with longer telomere length in both normal and tumour tissues. Our findings elucidated the significance of genetic factors in the pathogenesis of leiomyoma.

Study Profile of the Tohoku Medical Megabank Community-Based Cohort Study

Background

We established a community-based cohort study to assess the long-term impact of the Great East Japan Earthquake on disaster victims and gene-environment interactions on the incidence of major diseases, such as cancer and cardiovascular diseases.

Methods

We asked participants to join our cohort in the health check-up settings and assessment center based settings. Inclusion criteria were aged 20 years or over and living in Miyagi or Iwate Prefecture. We obtained information on lifestyle, effect of disaster, blood, and urine information (Type 1 survey), and some detailed measurements (Type 2 survey), such as carotid echography and calcaneal ultrasound bone mineral density. All participants agreed to measure genome information and to distribute their information widely.

Results

As a result, 87,865 gave their informed consent to join our study. Participation rate at health check-up site was about 70%. The participants in the Type 1 survey were more likely to have psychological distress than those in the Type 2 survey, and women were more likely to have psychological distress than men. Additionally, coastal residents were more likely to have higher degrees of psychological distress than inland residents, regardless of sex.

Conclusion

This cohort comprised a large sample size and it contains information on the natural disaster, genome information, and metabolome information. This cohort also had several detailed measurements. Using this cohort enabled us to clarify the long-term effect of the disaster and also to establish personalized prevention based on genome, metabolome, and other omics information.

A training and education program for genome medical research coordinators in the genome cohort study of the Tohoku Medical Megabank Organization

BACKGROUND

Genome cohort studies are used to analyze interactions between genetic and environmental factors, providing valuable information for personalized healthcare. Large-scale and long-term cohort studies require a number of specially trained personnel, of whom those involved in obtaining informed consent play a vital role, especially during the initial phase of such studies. The Japanese Society of Human Genetics (JSHG) previously established a certification system for genome medical research coordinators (GMRCs) responsible for obtaining written consent via face-to-face explanation. Meanwhile, in the Tohoku Medical Megabank Organization (ToMMo), GMRCs are expected to play important roles not only in obtaining informed consent and conducting various assessments, but also in communicating with participants throughout the long-term follow-up. Based on the JSHG program, we therefore developed a specific education and training program for ToMMo GMRCs consisting of 17 lectures, one practical training session on the informed consent procedure, and written and interview examinations. Re-education workshops aimed at self-improvement are also carried out following certification. In this study, we evaluated the education and training program in terms of overall understanding, usefulness, and satisfaction using an anonymous questionnaire.

METHODS

An anonymous questionnaire addressing each aspect of the education and training program (understanding, usefulness, and satisfaction) was distributed among 152 qualified ToMMo GMRCs. Responses were received from 94 participants (61.8%).

RESULTS

There was a significant association between the level of overall understanding of lectures and medical qualification (nurse or clinical laboratory technologist), but not with age or educational background. The level of understanding and overall usefulness were lower in sessions related to genetics and epidemiology than those dealing with ToMMo practices. In the re-education workshops, GMRCs showed a preference for and hoped to learn more about both background knowledge and research progress in the ToMMo.

CONCLUSIONS

The results of our questionnaire suggest that not all ToMMo GMRCs are able to understand everything during the initial education and training program, especially in terms of genomic medicine. Continuous re-education is therefore vital in improving knowledge, skills and motivation, and preparing GMRCs for a specialist role in community-based personalized healthcare.

Construction of JRG (Japanese reference genome) with single-molecule real-time sequencing

In recent genome analyses, population-specific reference panels have indicated important. However, reference panels based on short-read sequencing data do not sufficiently cover long insertions. Therefore, the nature of long insertions has not been well documented. Here, we assembled a Japanese genome using single-molecule real-time sequencing data and characterized insertions found in the assembled genome. We identified 3691 insertions ranging from 100 bps to ~10,000 bps in the assembled genome relative to the international reference sequence (GRCh38). To validate and characterize these insertions, we mapped short-reads from 1070 Japanese individuals and 728 individuals from eight other populations to insertions integrated into GRCh38. With this result, we constructed JRGv1 (Japanese Reference Genome version 1) by integrating the 903 verified insertions, totaling 1,086,173 bases, shared by at least two Japanese individuals into GRCh38. We also constructed decoyJRGv1 by concatenating 3559 verified insertions, totaling 2,536,870 bases, shared by at least two Japanese individuals or by six other assemblies. This assembly improved the alignment ratio by 0.4% on average. These results demonstrate the importance of refining the reference assembly and creating a population-specific reference genome. JRGv1 and decoyJRGv1 are available at the JRG website.

Researchers in Japan have assembled a Japanese reference genome, which includes sequences missing from the international reference genome, as well as others specific to East Asian populations. A team led by Masao Nagasaki and Masayuki Yamamoto sequenced a Japanese individual using a method, which produces longer sequences than previous technologies. Using this approach, they identified thousands of sequences spanning 2.5 million bases, which were absent in the international reference genome. Many of these were sequences able to move within the genome. They showed that the majority of these sequences are also present in early humans and chimpanzees, demonstrating that their absence from the current reference is due to deletions or limitations of earlier sequencing methodologies. In addition to providing a population-specific reference, these findings demonstrate the importance of continually improving the international reference genome.

Genome analyses for the Tohoku Medical Megabank Project towards establishment of personalized healthcare

Personalized healthcare (PHC) based on an individual's genetic make-up is one of the most advanced, yet feasible, forms of medical care. The Tohoku Medical Megabank (TMM) Project aims to combine population genomics, medical genetics and prospective cohort studies to develop a critical infrastructure for the establishment of PHC. To date, a TMM CommCohort (adult general population) and a TMM BirThree Cohort (birth+three-generation families) have conducted recruitments and baseline surveys. Genome analyses as part of the TMM Project will aid in the development of a high-fidelity whole-genome Japanese reference panel, in designing custom single-nucleotide polymorphism (SNP) arrays specific to Japanese, and in estimation of the biological significance of genetic variations through linked investigations of the cohorts. Whole-genome sequencing from >3,500 unrelated Japanese and establishment of a Japanese reference genome sequence from long-read data have been done. We next aim to obtain genotype data for all TMM cohort participants (>150,000) using our custom SNP arrays. These data will help identify disease-associated genomic signatures in the Japanese population, while genomic data from TMM BirThree Cohort participants will be used to improve the reference genome panel. Follow-up of the cohort participants will allow us to test the genetic markers and, consequently, contribute to the realization of PHC.

Respiratory resistance among adults in a population-based cohort study in Northern Japan

BACKGROUND

Forced oscillation technique (FOT) is a noninvasive method used to measure respiratory system resistance (Rrs) and reactance (Xrs) during quiet breathing, which has been extensively studied in clinical settings. The distribution of measured FOT values was previously assessed in a community-based cohort study. In this study, we aimed to confirm the distribution of measured FOT values in a different cohort in order to investigate the relationship between these values and patient clinical and biological data.

METHODS

We reviewed FOT data and relevant patient clinical and biological information collected from the Community-Based Cohort Study (CommCohort Study), carried out between 2013 to 2016 as a part of the Tohoku Medical Megabank project (TMM). In total, 16,231 adults were enrolled in the study (Male/Female: 4886/11,345).

RESULTS

Significant gender differences were observed in distributions of Rrs and Xrs values at 5 Hz (termed R5 and X5, respectively). R5 values in males were lower than those in females, while X5 values in males were slightly less negative. High R5 values were strongly associated with high BMI, short height, smoking status in males, high serum IgE level, and high peripheral blood eosinophil count.

CONCLUSION

The present distribution values and their relation to clinical and biological data should provide useful insights for clinical settings and serve as a helpful guide in implementing FOT. Forced oscillation technique, respiratory system resistance, respiratory system reactance, gender difference, obesity.

Genome-wide association study identifies gastric cancer susceptibility loci at 12q24.11-12 and 20q11.21

Gastric cancer is the third leading cause of cancer mortality in Japan and worldwide. Although previous studies identify various genetic variations associated with gastric cancer, host genetic factors are largely unidentified. To identify novel gastric cancer loci in the Japanese population, herein, we carried out a large‐scale genome‐wide association study using 6171 cases and 27 178 controls followed by three replication analyses. Analysis using a total of 11 507 cases and 38 904 controls identified two novel loci on 12q24.11‐12 (rs6490061, P = 3.20 × 10⁻⁸ with an odds ratio [OR] of 0.905) and 20q11.21 (rs2376549, P = 8.11 × 10⁻¹⁰ with an OR of 1.109). rs6490061 is located at intron 19 of the CUX2 gene, and its expression was suppressed by Helicobacter pylori infection. rs2376549 is included within the gene cluster of DEFB families that encode antibacterial peptides. We also found a significant association of rs7849280 in the ABO gene locus on 9q34.2 (P = 2.64 × 10⁻¹³ with an OR of 1.148). CUX2 and ABO expression in gastric mucosal tissues was significantly associated with rs6490061 and rs7849280 (P = 0.0153 and 8.00 × 10⁻¹¹), respectively. Our findings show the crucial roles of genetic variations in the pathogenesis of gastric cancer.

Omics research project on prospective cohort studies from the Tohoku Medical Megabank Project

Population-based prospective cohort studies are indispensable for modern medical research as they provide important knowledge on the influences of many kinds of genetic and environmental factors on the cause of disease. Although traditional cohort studies are mainly conducted using questionnaires and physical examinations, modern cohort studies incorporate omics and genomic approaches to obtain comprehensive physical information, including genetic information. Here, we report the design and midterm results of multi-omics analysis on population-based prospective cohort studies from the Tohoku Medical Megabank (TMM) Project. We have incorporated genomic and metabolomic studies in the TMM cohort study as both metabolome and genome analyses are suitable for high-throughput analysis of large-scale cohort samples. Moreover, an association study between the metabolome and genome show that metabolites are an important intermediate phenotype connecting genetic and lifestyle factors to physical and pathologic phenotypes. We apply our metabolome and genome analyses to large-scale cohort samples in the following studies.

Security controls in an integrated Biobank to protect privacy in data sharing: rationale and study design

Background

With the goal of realizing genome-based personalized healthcare, we have developed a biobank that integrates personal health, genome, and omics data along with biospecimens donated by volunteers of 150,000. Such a large-scale of data integration involves obvious risks of privacy violation. The research use of personal genome and health information is a topic of global discussion with regard to the protection of privacy while promoting scientific advancement. The present paper reports on our plans, current attempts, and accomplishments in addressing security problems involved in data sharing to ensure donor privacy while promoting scientific advancement.

Methods

Biospecimens and data have been collected in prospective cohort studies with the comprehensive agreement. The sample size of 150,000 participants was required for multiple researches including genome-wide screening of gene by environment interactions, haplotype phasing, and parametric linkage analysis.

Results

We established the TohokuMedicalMegabank (TMM) data sharing policy: a privacy protection rule that requires physical, personnel, and technological safeguards against privacy violation regarding the use and sharing of data. The proposed policy refers to that of NCBI and that of the Sanger Institute. The proposed policy classifies shared data according to the strength of re-identification risks. Local committees organized by TMM evaluate re-identification risk and assign a security category to a dataset. Every dataset is stored in an assigned segment of a supercomputer in accordance with its security category. A security manager should be designated to handle all security problems at individual data use locations. The proposed policy requires closed networks and IP-VPN remote connections.

Conclusion

The mission of the biobank is to distribute biological resources most productively. This mission motivated us to collect biospecimens and health data and simultaneously analyze genome/omics data in-house. The biobank also has the mission of improving the quality and quantity of the contents of the biobank. This motivated us to request users to share the results of their research as feedback to the biobank. The TMM data sharing policy has tackled every security problem originating with the missions. We believe our current implementation to be the best way to protect privacy in data sharing.

Electronic supplementary material

The online version of this article (doi:10.1186/s12911-017-0494-5) contains supplementary material, which is available to authorized users.

The structural origin of metabolic quantitative diversity

Relationship between structural variants of enzymes and metabolic phenotypes in human population was investigated based on the association study of metabolite quantitative traits with whole genome sequence data for 512 individuals from a population cohort. We identified five significant associations between metabolites and non-synonymous variants. Four of these non-synonymous variants are located in enzymes involved in metabolic disorders, and structural analyses of these moderate non-synonymous variants demonstrate that they are located in peripheral regions of the catalytic sites or related regulatory domains. In contrast, two individuals with larger changes of metabolite levels were also identified, and these individuals retained rare variants, which caused non-synonymous variants located near the catalytic site. These results are the first demonstrations that variant frequency, structural location, and effect for phenotype correlate with each other in human population, and imply that metabolic individuality and susceptibility for diseases may be elicited from the moderate variants and much more deleterious but rare variants.

The Tohoku Medical Megabank Project: Design and Mission

The Great East Japan Earthquake (GEJE) and resulting tsunami of March 11, 2011 gave rise to devastating damage on the Pacific coast of the Tohoku region. The Tohoku Medical Megabank Project (TMM), which is being conducted by Tohoku University Tohoku Medical Megabank Organization (ToMMo) and Iwate Medical University Iwate Tohoku Medical Megabank Organization (IMM), has been launched to realize creative reconstruction and to solve medical problems in the aftermath of this disaster. We started two prospective cohort studies in Miyagi and Iwate Prefectures: a population-based adult cohort study, the TMM Community-Based Cohort Study (TMM CommCohort Study), which will recruit 80 000 participants, and a birth and three-generation cohort study, the TMM Birth and Three-Generation Cohort Study (TMM BirThree Cohort Study), which will recruit 70 000 participants, including fetuses and their parents, siblings, grandparents, and extended family members. The TMM CommCohort Study will recruit participants from 2013 to 2016 and follow them for at least 5 years. The TMM BirThree Cohort Study will recruit participants from 2013 to 2017 and follow them for at least 4 years. For children, the ToMMo Child Health Study, which adopted a cross-sectional design, was also started in November 2012 in Miyagi Prefecture. An integrated biobank will be constructed based on the two prospective cohort studies, and ToMMo and IMM will investigate the chronic medical impacts of the GEJE. The integrated biobank of TMM consists of health and clinical information, biospecimens, and genome and omics data. The biobank aims to establish a firm basis for personalized healthcare and medicine, mainly for diseases aggravated by the GEJE in the two prefectures. Biospecimens and related information in the biobank will be distributed to the research community. TMM itself will also undertake genomic and omics research. The aims of the genomic studies are: 1) to construct an integrated biobank; 2) to return genomic research results to the participants of the cohort studies, which will lead to the implementation of personalized healthcare and medicine in the affected areas in the near future; and 3) to contribute the development of personalized healthcare and medicine worldwide. Through the activities of TMM, we will clarify how to approach prolonged healthcare problems in areas damaged by large-scale disasters and how useful genomic information is for disease prevention.

Development of an Ontology for Periodontitis

BACKGROUND

In the clinical dentists and periodontal researchers' community, there is an obvious demand for a systems model capable of linking the clinical presentation of periodontitis to underlying molecular knowledge. A computer-readable representation of processes on disease development will give periodontal researchers opportunities to elucidate pathways and mechanisms of periodontitis. An ontology for periodontitis can be a model for integration of large variety of factors relating to a complex disease such as chronic inflammation in different organs accompanied by bone remodeling and immune system disorders, which has recently been referred to as osteoimmunology.

METHODS

Terms characteristic of descriptions related to the onset and progression of periodontitis were manually extracted from 194 review articles and PubMed abstracts by experts in periodontology. We specified all the relations between the extracted terms and constructed them into an ontology for periodontitis. We also investigated matching between classes of our ontology and that of Gene Ontology Biological Process.

RESULTS

We developed an ontology for periodontitis called Periodontitis-Ontology (PeriO). The pathological progression of periodontitis is caused by complex, multi-factor interrelationships. PeriO consists of all the required concepts to represent the pathological progression and clinical treatment of periodontitis. The pathological processes were formalized with reference to Basic Formal Ontology and Relation Ontology, which accounts for participants in the processes realized by biological objects such as molecules and cells. We investigated the peculiarity of biological processes observed in pathological progression and medical treatments for the disease in comparison with Gene Ontology Biological Process (GO-BP) annotations. The results indicated that peculiarities of Perio existed in 1) granularity and context dependency of both the conceptualizations, and 2) causality intrinsic to the pathological processes. PeriO defines more specific concepts than GO-BP, and thus can be added as descendants of GO-BP leaf nodes. PeriO defines causal relationships between the process concepts, which are not shown in GO-BP. The difference can be explained by the goal of conceptualization: PeriO focuses on mechanisms of the pathogenic progress, while GO-BP focuses on cataloguing all of the biological processes observed in experiments. The goal of conceptualization in PeriO may reflect the domain knowledge where a consequence in the causal relationships is a primary interest. We believe the peculiarities can be shared among other diseases when comparing processes in disease against GO-BP.

CONCLUSIONS

This is the first open biomedical ontology of periodontitis capable of providing a foundation for an ontology-based model of aspects of molecular biology and pathological processes related to periodontitis, as well as its relations with systemic diseases. PeriO is available at http://bio-omix.tmd.ac.jp/periodontitis/.

Identification of collaborative activities with oxidative phosphorylation in bipolar disorder

Bipolar disorder (BD) is a psychiatric disease considered to polygenic with multiple factors in genetics, each of which is not dominant but collaborative during pathogenic progression. We describe a method that estimates the collaborative contribution to the disease between a certain well-studied pathway and the other candidate pathway using Gene Set Enrichment Analysis (GSEA). We describe a modified GSEA (improved derivation) to identify genes that are significantly and differentially expressed between disease and non-disease states and that are consistently co-expressed with a target pathway which is deeply related to disease etiology. The modified GSEA uses available gene expression data to identify molecular mechanism (ubiquitin-proteasome and inflammatory response) associated with the disease. We believe that this approach could reveal hidden relations between a certain well-studied pathway and the other candidate pathway known in literature.

ABBREVIATIONS

ATP5I - ATP synthase H+ transporting mitochondrial F0 complex subunit E, ATP5J - ATP synthase H+ transporting mitochondrial F0 complex subunit F6, BAD - Bcl-2-associated death promoter, BAX - Bcl-2-associated x protein, Bcl-2 - B-cell lymphoma 2, BDNF - brain derived neurotrophic factor, COX5B - Cytochrome c oxidase subunit Vb, COX7A2 - cytochrome c oxidase subunit VIIa polypeptide 2, DLK - dual leucine zipper-bearing kinase, GABA - Gamma aminobutyric acid, IL-8 - Interleukin 8, NDUFA1 - NADH dehydrogenase 1 alpha subcomplex 1, NDUFB2 - NADH dehydrogenase1 beta subcomplex 2, NDUFS4 - NADH dehydrogenase Fe-S protein 4, NGF - nerve growth factor, PPP2R5C - protein phosphatase 2 regulatory subunit B gamma, PSMA3 - proteasome subunit alpha type 3, PSMA7 - proteasome subunit alpha type 7, PSMB1 - proteasome subunit beta type 1, PSMB6 - proteasome subunit beta type 6, PSMB7 - proteasome subunit beta type 7, PSMC2 - proteasome 26S subunit ATPase 2, PSMC5 - proteasome 26S subunit ATPase 5, SLC6A4 - solute carrier family 6 member 4, TNFa - tumor necrosis factor a, UBE2A - ubiquitinconjugating enzyme E2A, UCRC - ubiquinol-cytochrome c reductase complex, UFC1 - ubiquitin-fold modifier conjugating enzyme 1, UQCRQ - ubiquinol-cytochrome c reductase complex III subunit VII, USP14 - ubiquitin specific protease 14.

Structural classification of steroid-binding sites on proteins by coarse-grained atomic environment and its correlation with their biological function

Steroid hormone is extensively used for transmitting variety of biological signals in organisms. Natural steroid hormone is synthesized from cholesterol in adrenal cortex and in sexual gland in vertebrates. Appropriately dosed synthetic steroid hormones can be used for medication. Despite their positive effects as medicine, they sometimes cause significant side effects due to their wide range of actions, and the studies for discovering the mechanisms of side effects were carried out aiming to reduce the side effects. The fundamental cause of the side effects seems to be interactions between the steroid and a non-target protein. To understand the possible range of interaction of steroid molecule, we gathered all the three-dimensional structures of protein-steroid complex determined by X-ray crystallography, compared the atomic environments of the steroid-binding sites in proteins and classified the pattern of steroid binding. Protein Data Bank contained 871 structures of steroid-protein complexes in 382 entries. For this study, we selected 832 steroid binding proteins. Using a newly developed method to describe the atomic environments of these steroid molecules and their function, we were able to separate the environments into six patterns. This classification had a potential to predict the function of function-unknown proteins with a co-crystallized steroid molecule. We speculated that the proteins grouped into the same pattern of nuclear receptors were the candidates of non-targeted proteins causing a side effect by a therapeutic prescription of steroid hormone.

Ligand-activated PPARα-dependent DNA demethylation regulates the fatty acid β-oxidation genes in the postnatal liver

The metabolic function of the liver changes sequentially during early life in mammals to adapt to the marked changes in nutritional environment. Accordingly, hepatic fatty acid β-oxidation is activated after birth to produce energy from breast milk lipids. However, how it is induced during the neonatal period is poorly understood. Here we show DNA demethylation and increased mRNA expression of the fatty acid β-oxidation genes in the postnatal mouse liver. The DNA demethylation does not occur in the fetal mouse liver under the physiologic condition, suggesting that it is specific to the neonatal period. Analysis of mice deficient in the nuclear receptor peroxisome proliferator-activated receptor α (PPARα) and maternal administration of a PPARα ligand during the gestation and lactation periods reveal that the DNA demethylation is PPARα dependent. We also find that DNA methylation of the fatty acid β-oxidation genes are reduced in the adult human liver relative to the fetal liver. This study represents the first demonstration that the ligand-activated PPARα-dependent DNA demethylation regulates the hepatic fatty acid β-oxidation genes during the neonatal period, thereby highlighting the role of a lipid-sensing nuclear receptor in the gene- and life-stage-specific DNA demethylation of a particular metabolic pathway.

PGC-1α-mediated branched-chain amino acid metabolism in the skeletal muscle

Peroxisome proliferator-activated receptor (PPAR) γ coactivator 1α (PGC-1α) is a coactivator of various nuclear receptors and other transcription factors, which is involved in the regulation of energy metabolism, thermogenesis, and other biological processes that control phenotypic characteristics of various organ systems including skeletal muscle. PGC-1α in skeletal muscle is considered to be involved in contractile protein function, mitochondrial function, metabolic regulation, intracellular signaling, and transcriptional responses. Branched-chain amino acid (BCAA) metabolism mainly occurs in skeletal muscle mitochondria, and enzymes related to BCAA metabolism are increased by exercise. Using murine skeletal muscle overexpressing PGC-1α and cultured cells, we investigated whether PGC-1α stimulates BCAA metabolism by increasing the expression of enzymes involved in BCAA metabolism. Transgenic mice overexpressing PGC-1α specifically in the skeletal muscle had increased the expression of branched-chain aminotransferase (BCAT) 2, branched-chain α-keto acid dehydrogenase (BCKDH), which catabolize BCAA. The expression of BCKDH kinase (BCKDK), which phosphorylates BCKDH and suppresses its enzymatic activity, was unchanged. The amount of BCAA in the skeletal muscle was significantly decreased in the transgenic mice compared with that in the wild-type mice. The amount of glutamic acid, a metabolite of BCAA catabolism, was increased in the transgenic mice, suggesting the activation of muscle BCAA metabolism by PGC-1α. In C2C12 cells, the overexpression of PGC-1α significantly increased the expression of BCAT2 and BCKDH but not BCKDK. Thus, PGC-1α in the skeletal muscle is considered to significantly contribute to BCAA metabolism.

Activating transcription factor 4 links metabolic stress to interleukin-6 expression in macrophages

Chronic inflammation is a molecular element of the metabolic syndrome and type 2 diabetes. Saturated fatty acids (SFAs) are considered to be an important proinflammatory factor. However, it is still incompletely understood how SFAs induce proinflammatory cytokine expression. Hereby we report that activating transcription factor (ATF) 4, a transcription factor that is induced downstream of metabolic stresses including endoplasmic reticulum (ER) stress, plays critical roles in SFA-induced interleukin-6 (Il6) expression. DNA microarray analysis using primary macrophages revealed that the ATF4 pathway is activated by SFAs. Haploinsufficiency and short hairpin RNA-based knockdown of ATF4 in macrophages markedly inhibited SFA- and metabolic stress-induced Il6 expression. Conversely, pharmacological activation of the ATF4 pathway and overexpression of ATF4 resulted in enhanced Il6 expression. Moreover, ATF4 acts in synergy with the Toll-like receptor-4 signaling pathway, which is known to be activated by SFAs. At a molecular level, we found that ATF4 exerts its proinflammatory effects through at least two different mechanisms: ATF4 is involved in SFA-induced nuclear factor-κB activation; and ATF4 directly activates the Il6 promoter. These findings provide evidence suggesting that ATF4 links metabolic stress and Il6 expression in macrophages.

Analysis of DNA methylation change induced by Dnmt3b in mouse hepatocytes

DNA methylation is a key epigenetic contributor to gene regulation in mammals. We have recently found that in the mouse liver, the promoter region of glycerol-3-phosphate acyltransferase 1, a rate-limiting enzyme of de novo lipogenesis, is regulated by DNA methylation, which is mediated by Dnmt3b, an enzyme required for the initiation of de novo methylation. In this study, using primary cultures of mouse hepatocytes with adenoviral overexpression of Dnmt3b, we characterized Dnmt3b-dependent DNA methylation on a genome-wide basis. A genome-wide DNA methylation analysis, called microarray-based integrated analysis of methylation by isoschizomers, identified 108 genes with Dnmt3b dependent DNA methylation. In DNA expression array analysis, expression of some genes with Dnmt3b-dependent DNA methylation was suppressed. Studies with primary mouse hepatocytes overexpressing Dnmt3b or Dnmt3a revealed that many genes with Dnmt3b-dependent methylation are not methylated by Dnmt3a, whereas those methylated by Dnmt3a are mostly methylated by Dnmt3b. Bioinformatic analysis showed that the CANAGCTG and CCGGWNCSC (N denotes A, T, G, or C; W denotes A or T; and S denotes C or G) sequences are enriched in genes methylated by overexpression of Dnmt3b and Dnmt3a, respectively. We also observed a large number of genes with Dnmt3b-dependent DNA methylation in primary cultures of mouse hepatocytes with adenoviral overexpression of Dnmt3, suggesting that Dnmt3b is an important DNA methyltransferase in primary mouse hepatocytes, targets specific genes, and potentially plays a role in vivo.

CELLPEDIA: a repository for human cell information for cell studies and differentiation analyses

CELLPEDIA is a repository database for current knowledge about human cells. It contains various types of information, such as cell morphologies, gene expression and literature references. The major role of CELLPEDIA is to provide a digital dictionary of human cells for the biomedical field, including support for the characterization of artificially generated cells in regenerative medicine. CELLPEDIA features (i) its own cell classification scheme, in which whole human cells are classified by their physical locations in addition to conventional taxonomy; and (ii) cell differentiation pathways compiled from biomedical textbooks and journal papers. Currently, human differentiated cells and stem cells are classified into 2260 and 66 cell taxonomy keys, respectively, from which 934 parent-child relationships reported in cell differentiation or transdifferentiation pathways are retrievable. As far as we know, this is the first attempt to develop a digital cell bank to function as a public resource for the accumulation of current knowledge about human cells. The CELLPEDIA homepage is freely accessible except for the data submission pages that require authentication (please send a password request to cell-info@cbrc.jp). Database URL: http://cellpedia.cbrc.jp/

Increased systemic glucose tolerance with increased muscle glucose uptake in transgenic mice overexpressing RXRγ in skeletal muscle

Background

Retinoid X receptor (RXR) γ is a nuclear receptor-type transcription factor expressed mostly in skeletal muscle, and regulated by nutritional conditions. Previously, we established transgenic mice overexpressing RXRγ in skeletal muscle (RXRγ mice), which showed lower blood glucose than the control mice. Here we investigated their glucose metabolism.

Methodology/Principal Findings

RXRγ mice were subjected to glucose and insulin tolerance tests, and glucose transporter expression levels, hyperinsulinemic-euglycemic clamp and glucose uptake were analyzed. Microarray and bioinformatics analyses were done. The glucose tolerance test revealed higher glucose disposal in RXRγ mice than in control mice, but insulin tolerance test revealed no difference in the insulin-induced hypoglycemic response. In the hyperinsulinemic-euglycemic clamp study, the basal glucose disposal rate was higher in RXRγ mice than in control mice, indicating an insulin-independent increase in glucose uptake. There was no difference in the rate of glucose infusion needed to maintain euglycemia (glucose infusion rate) between the RXRγ and control mice, which is consistent with the result of the insulin tolerance test. Skeletal muscle from RXRγ mice showed increased Glut1 expression, with increased glucose uptake, in an insulin-independent manner. Moreover, we performed in vivo luciferase reporter analysis using Glut1 promoter (Glut1-Luc). Combination of RXRγ and PPARδ resulted in an increase in Glut1-Luc activity in skeletal muscle in vivo. Microarray data showed that RXRγ overexpression increased a diverse set of genes, including glucose metabolism genes, whose promoter contained putative PPAR-binding motifs.

Conclusions/Significance

Systemic glucose metabolism was increased in transgenic mice overexpressing RXRγ. The enhanced glucose tolerance in RXRγ mice may be mediated at least in part by increased Glut1 in skeletal muscle. These results show the importance of skeletal muscle gene regulation in systemic glucose metabolism. Increasing RXRγ expression may be a novel therapeutic strategy against type 2 diabetes.

On experiences of i2b2 (Informatics for integrating biology and the bedside) database with Japanese clinical patients' data

Informatics for Integrating Biology and the Bedside (i2b2) is a database system to facilitate sharing and reuse of clinical patients' data collected in individual hospitals. The i2b2 provides an ontology based object-oriented database system with highly simple and flexible database schema which enables us to integrate clinical patients' data from different laboratories and different hospitals. 392 patients' data including carcinoma and non-carcinoma specimens from cancer patients are transported from the Integrated Clinical Omics Database (iCOD) to the i2b2 database for a feasibility study to check applicability of i2b2 ontology and database schema on Japanese clinical patients' data. No modification is required for the i2b2 data model to deal with Japanese characters. Some modification of ontology is required to integrate biomedical information extracted from the cancer patients' data. We believe that the i2b2 system will be practical infrastructure to integrate Japanese clinical databases if appropriate disease ontology for Japanese patients is provided.

Ontology based standardization of petri net modeling for signaling pathways

Taking account of the great availability of Petri nets in modeling and analyzing large complicated signaling networks, semantics of Petri nets is in need of systematization for the purpose of consistency and reusability of the models. This paper reports on standardization of units of Petri nets on the basis of an ontology that gives an intrinsic definition to the process of signaling in signaling pathways.

Development of a database and ontology for pathogenic pathways in periodontitis

It is getting familiar that pathway information greatly contributes to elucidate the molecular basis of human disease with large-scale biological data. We developed a pathway database for molecular pathology in periodontitis named 'Pathogenic Pathway Database for Periodontitis'. Periodontitis is an inflammation disease in periodontal tissue and associated with an increased health risk of angina, myocardial infarction, and fetal cardiovascular events. Despite accumulation of biomedical research on periodontitis pathology at the molecular level, there has been no systematization for biological pathways in periodontitis. We checked 185 reference papers and extracted causal relationships among molecules as well as pathways representing molecular etiology. We also built an ontology that systematizes conceptual terms associated with the pathways. Besides pathways, our ontology provides cellular and tissue specific contextual information that is required to represent pathology at the cellular and tissue specific levels. We implemented in our database an integrated viewer for the association between pathways and ontology. Pathogenic Pathway Database for Periodontitis is freely available at http://bio-omix.tmd.ac.jp/disease/perio/.

Ontology based standardization of Petri net modeling for signaling pathways

Taking account of the great availability of Petri nets in modeling and analyzing large complicated signaling networks, semantics of Petri nets is in need of systematization for the purpose of consistency and reusability of the models. This paper reports on standardization of units of Petri nets on the basis of an ontology that gives an intrinsic definition to the process of signaling in signaling pathways.

Ontological integration of data models for cell signaling pathways by defining a factor of causality called 'signal'

Databases have collected masses of information concerning cell signaling pathways that includes information on pathways, molecular interactions as well as molecular complexes. However we have no general data model to represent comprehensive properties of cell signaling pathways, so that this type of information has been represented by two different data models that we call 'binary relation' and 'state transition'. The disagreement between the existing models derives from lack of consensus about a factor of causality in reactions in cell signaling pathways, which is often called 'signal'. We developed an ontology named CSNO (Cell Signaling Networks Ontology) based on device ontology. As device ontology is a research product of knowledge engineering, CSNO is the first application of it to biological knowledge. CSNO defines the factor of causality called 'signal', offers an integrative viewpoint for the two different data models, explicates intrinsic distinctions between signaling and metabolic pathways, and eliminates ambiguity from representation of complex molecules.

Cell signaling networks ontology

Although databases for cell signaling pathways include numbers of reaction data of the pathways, the reaction data cannot be used yet to deduce biological functions from them. For the deduction, we need systematic and consistent interpretation of biological functions of reactions in cell signaling pathways in the context of "information transmission". To address this issue, we have developed a functional ontology for cell signaling pathways, Cell Signaling Network Ontology (CSN-Ontology), which provides framework for the functional interpretation presenting some important concepts as information, selectivity, movability, and signaling rules including passage of time.

A pathway finding system for the cell signaling networks database

We report on a knowledge-based pathway-finding system that builds on the cell-signaling networks database, CSNDB, which we developed previously. This new system, PaF-CSNDB, uses a general inference engine to apply rules for finding and coupling pathways between or around specific biomolecules from the CSNDB database. We show how PaF-CSNDB finds relationships in a large but fragmented collection of cell-signaling knowledge by filtering out and composing together those sections of pathways specified from an extensive and complex set of binary or pair-wise cell-signaling reactions.

Modeling of signaling pathways for endocrine disruptors

The so called endocrine disruptors have become an important working hypothesis for a wide range of toxicology researchers. This hypothesis has also attracted those who have worked on designer estrogens or selective estrogen receptor modulators. Already numbers of substances have been identified as such chemicals, but there remain a large number of chemicals waiting to be tested for their endocrine modulating capabilities. Because of the time and costs required for wet lab tests, it is unrealistic to apply these kinds of tests to all such suspicious or probable chemicals. Thus some theoretical methods must be developed for this purpose. However the conventional QSAR (quantitative structure activity relationships) approach is of limited relevance to this problem, because these methods do not take detailed mechanisms of molecular interactions in biological systems into account. Thus we have developed a database complex system that enables one to trace molecular interactions triggered by interaction of receptors with xenobiotic chemicals. The main components of this database complex are a potential endocrine disruptor database, a receptor database, a cell signaling networks database, a transcription factor database, and an affinity binding database based on modes of actions.

A database for cell signaling networks

We developed a data and knowledge base for cellular signal transduction in human cells, to make this rapidly growing information available. The database includes all the biological properties of cellular signal transduction, including biological reactions that transfer cellular signals and molecular attributes characterized by sequences, structures, and functions. Since the database is based on the object-oriented technique, highly flexible methods of data definition and modification are necessary to handle this diverse and complex biological information. The database includes attractive graphical representations of signaling cascades and the three-dimensional structure of molecules. The database is a novel application of ACEDB, which was the database originally developed to store the C. elegans genome. The database can be accessed through the Internet at http://geo.nihs.go.jp/csndb.html.