Genome-wide association database developed in the Japanese Integrated Database Project

Spatiotemporal expression patterns of anxiety disorder-associated genes

Anxiety disorders (ADs) are the most common form of mental disorder that affects millions of individuals worldwide. Although physiological studies have revealed the neural circuits related to AD symptoms, how AD-associated genes are spatiotemporally expressed in the human brain still remains unclear. In this study, we integrated genome-wide association studies of four human AD subtypes-generalized anxiety disorder, social anxiety disorder, panic disorder, and obsessive-compulsive disorder-with spatial gene expression patterns. Our investigation uncovered a novel division among AD-associated genes, marked by significant and distinct expression enrichments in the cerebral nuclei, limbic, and midbrain regions. Each gene cluster was associated with specific anxiety-related behaviors, signaling pathways, region-specific gene networks, and cell types. Notably, we observed a significant negative correlation in the temporal expression patterns of these gene clusters during various developmental stages. Moreover, the specific brain regions enriched in each gene group aligned with neural circuits previously associated with negative decision-making and anxious temperament. These results suggest that the two distinct gene clusters may underlie separate neural systems involved in anxiety. As a result, our findings bridge the gap between genes and neural circuitry, shedding light on the mechanisms underlying AD-associated behaviors.

A data harmonization pipeline to leverage external controls and boost power in GWAS

The use of external controls in genome-wide association study (GWAS) can significantly increase the size and diversity of the control sample, enabling high-resolution ancestry matching and enhancing the power to detect association signals. However, the aggregation of controls from multiple sources is challenging due to batch effects, difficulty in identifying genotyping errors, and the use of different genotyping platforms. These obstacles have impeded the use of external controls in GWAS and can lead to spurious results if not carefully addressed. We propose a unified data harmonization pipeline that includes an iterative approach to quality control (QC) and imputation, implemented before and after merging cohorts and arrays. We apply this harmonization pipeline to aggregate 27 517 European control samples from 16 collections within dbGaP. We leverage these harmonized controls to conduct a GWAS of Crohn's disease. We demonstrate a boost in power over using the cohort samples alone, and that our procedure results in summary statistics free of any significant batch effects. This harmonization pipeline for aggregating genotype data from multiple sources can also serve other applications where individual level genotypes, rather than summary statistics, are required.

ADAMTS-12: Functions and Challenges for a Complex Metalloprotease

Nineteen members of the ADAMTS family of secreted zinc metalloproteinases are present in the human degradome. A wide range of different functions are being attributed to these enzymes and the number of their known substrates is considerably increasing in recent years. ADAMTSs can participate in processes such as fertility, inflammation, arthritis, neuronal and behavioral disorders, as well as cancer. Since its first annotation in 2001, ADAMTS-12 has been described to participate in different processes displayed by members of this family of proteinases. In this sense, ADAMTS-12 performs essential roles in modulation and recovery from inflammatory processes such as colitis, endotoxic sepsis and pancreatitis. ADAMTS-12 has also been involved in cancer development acting either as a tumor suppressor or as a pro-tumoral agent. Furthermore, participation of ADAMTS-12 in arthritis or in neuronal disorders has also been suggested through degradation of components of the extracellular matrix. In addition, ADAMTS-12 proteinase activity can also be modified by interaction with other proteins and thus, can be an alternative way of modulating ADAMTS-12 functions. In this review we revised the most relevant findings about ADAMTS-12 function on the 20th anniversary of its identification.

New Insights into ADAMTS Metalloproteases in the Central Nervous System

Components of the extracellular matrix (ECM) are key players in regulating cellular functions throughout the whole organism. In fact, ECM components not only participate in tissue organization but also contribute to processes such as cellular maintenance, proliferation, and migration, as well as to support for various signaling pathways. In the central nervous system (CNS), proteoglycans of the lectican family, such as versican, aggrecan, brevican, and neurocan, are important constituents of the ECM. In recent years, members of this family have been found to be involved in the maintenance of CNS homeostasis and to participate directly in processes such as the organization of perineural nets, the regulation of brain plasticity, CNS development, brain injury repair, axonal guidance, and even the altering of synaptic responses. ADAMTSs are a family of “A disintegrin and metalloproteinase with thrombospondin motifs” proteins that have been found to be involved in a multitude of processes through the degradation of lecticans and other proteoglycans. Recently, alterations in ADAMTS expression and activity have been found to be involved in neuronal disorders such as stroke, neurodegeneration, schizophrenia, and even Alzheimer’s disease, which in turn may suggest their potential use as therapeutic targets. Herein, we summarize the different roles of ADAMTSs in regulating CNS events through interactions and the degradation of ECM components (more specifically, the lectican family of proteoglycans).

DBTSS/DBKERO for integrated analysis of transcriptional regulation

DBTSS (Database of Transcriptional Start Sites)/DBKERO (Database of Kashiwa Encyclopedia for human genome mutations in Regulatory regions and their Omics contexts) is the database originally initiated with the information of transcriptional start sites and their upstream transcriptional regulatory regions. In recent years, we updated the database to assist users to elucidate biological relevance of the human genome variations or somatic mutations in cancers which may affect the transcriptional regulation. In this update, we facilitate interpretations of disease associated genomic variation, using the Japanese population as a model case. We enriched the genomic variation dataset consisting of the 13,368 individuals collected for various genome-wide association studies and the reference epigenome information in the surrounding regions using a total of 455 epigenome datasets (four tissue types from 67 healthy individuals) collected for the International Human Epigenome Consortium (IHEC). The data directly obtained from the clinical samples was associated with that obtained from various model systems, such as the drug perturbation datasets using cultured cancer cells. Furthermore, we incorporated the results obtained using the newly developed analytical methods, Nanopore/10x Genomics long-read sequencing of the human genome and single cell analyses. The database is made publicly accessible at the URL (http://dbtss.hgc.jp/).

Explaining the disease phenotype of intergenic SNP through predicted long range regulation

Thousands of disease-associated SNPs (daSNPs) are located in intergenic regions (IGR), making it difficult to understand their association with disease phenotypes. Recent analysis found that non-coding daSNPs were frequently located in or approximate to regulatory elements, inspiring us to try to explain the disease phenotypes of IGR daSNPs through nearby regulatory sequences. Hence, after locating the nearest distal regulatory element (DRE) to a given IGR daSNP, we applied a computational method named INTREPID to predict the target genes regulated by the DRE, and then investigated their functional relevance to the IGR daSNP's disease phenotypes. 36.8% of all IGR daSNP-disease phenotype associations investigated were possibly explainable through the predicted target genes, which were enriched with, were functionally relevant to, or consisted of the corresponding disease genes. This proportion could be further increased to 60.5% if the LD SNPs of daSNPs were also considered. Furthermore, the predicted SNP-target gene pairs were enriched with known eQTL/mQTL SNP-gene relationships. Overall, it's likely that IGR daSNPs may contribute to disease phenotypes by interfering with the regulatory function of their nearby DREs and causing abnormal expression of disease genes.

A Method to Exploit the Structure of Genetic Ancestry Space to Enhance Case-Control Studies

One goal of human genetics is to understand the genetic basis of disease, a challenge for diseases of complex inheritance because risk alleles are few relative to the vast set of benign variants. Risk variants are often sought by association studies in which allele frequencies in case subjects are contrasted with those from population-based samples used as control subjects. In an ideal world we would know population-level allele frequencies, releasing researchers to focus on case subjects. We argue this ideal is possible, at least theoretically, and we outline a path to achieving it in reality. If such a resource were to exist, it would yield ample savings and would facilitate the effective use of data repositories by removing administrative and technical barriers. We call this concept the Universal Control Repository Network (UNICORN), a means to perform association analyses without necessitating direct access to individual-level control data. Our approach to UNICORN uses existing genetic resources and various statistical tools to analyze these data, including hierarchical clustering with spectral analysis of ancestry; and empirical Bayesian analysis along with Gaussian spatial processes to estimate ancestry-specific allele frequencies. We demonstrate our approach using tens of thousands of control subjects from studies of Crohn disease, showing how it controls false positives, provides power similar to that achieved when all control data are directly accessible, and enhances power when control data are limiting or even imperfectly matched ancestrally. These results highlight how UNICORN can enable reliable, powerful, and convenient genetic association analyses without access to the individual-level data.

Ethical considerations of research policy for personal genome analysis: the approach of the Genome Science Project in Japan

As evidenced by high-throughput sequencers, genomic technologies have recently undergone radical advances. These technologies enable comprehensive sequencing of personal genomes considerably more efficiently and less expensively than heretofore. These developments present a challenge to the conventional framework of biomedical ethics; under these changing circumstances, each research project has to develop a pragmatic research policy. Based on the experience with a new large-scale project-the Genome Science Project-this article presents a novel approach to conducting a specific policy for personal genome research in the Japanese context. In creating an original informed-consent form template for the project, we present a two-tiered process: making the draft of the template following an analysis of national and international policies; refining the draft template in conjunction with genome project researchers for practical application. Through practical use of the template, we have gained valuable experience in addressing challenges in the ethical review process, such as the importance of sharing details of the latest developments in genomics with members of research ethics committees. We discuss certain limitations of the conventional concept of informed consent and its governance system and suggest the potential of an alternative process using information technology.

Lessons from Genome-Wide Search for Disease-Related Genes with Special Reference to HLA-Disease Associations

The relationships between diseases and genetic factors are by no means uniform. Single-gene diseases are caused primarily by rare mutations of specific genes. Although each single-gene disease has a low prevalence, there are an estimated 5000 or more such diseases in the world. In contrast, multifactorial diseases are diseases in which both genetic and environmental factors are involved in onset. These include a variety of diseases, such as diabetes and autoimmune diseases, and onset is caused by a range of various environmental factors together with a number of genetic factors. With the astonishing advances in genome analysis technology in recent years and the accumulation of data on human genome variation, there has been a rapid progress in research involving genome-wide searches for genes related to diseases. Many of these studies have led to the recognition of the importance of the human leucocyte antigen (HLA) gene complex. Here, the current state and future challenges of genome-wide exploratory research into variations that are associated with disease susceptibilities and drug/therapy responses are described, mainly with reference to our own experience in this field.

Meta-analysis of genome-wide association studies for panic disorder in the Japanese population

Panic disorder (PD) is a moderately heritable anxiety disorder whose pathogenesis is not well understood. Due to the lack of power in previous association studies, genes that are truly associated with PD might not be detected. In this study, we conducted a genome-wide association study (GWAS) in two independent data sets using the Affymetrix Mapping 500K Array or Genome-Wide Human SNP Array 6.0. We obtained imputed genotypes for each GWAS and performed a meta-analysis of two GWAS data sets (718 cases and 1717 controls). For follow-up, 12 single-nucleotide polymorphisms (SNPs) were tested in 329 cases and 861 controls. Gene ontology enrichment and candidate gene analyses were conducted using the GWAS or meta-analysis results. We also applied the polygenic score analysis to our two GWAS samples to test the hypothesis of polygenic components contributing to PD. Although genome-wide significant SNPs were not detected in either of the GWAS nor the meta-analysis, suggestive associations were observed in several loci such as BDKRB2 (P=1.3 × 10(-5), odds ratio=1.31). Among previous candidate genes, supportive evidence for association of NPY5R with PD was obtained (gene-wise corrected P=6.4 × 10(-4)). Polygenic scores calculated from weakly associated SNPs (P<0.3 and 0.4) in the discovery sample were significantly associated with PD status in the target sample in both directions (sample I to sample II and vice versa) (P<0.05). Our findings suggest that large sets of common variants of small effects collectively account for risk of PD.

Lack of an association between E-selectin gene polymorphisms and risk of Kawasaki disease

BACKGROUND

Coronary artery lesions (CAL) are a serious complication of Kawasaki disease (KD). The increased serum E-selectin level during the acute phase of KD and the association of E-selectin gene (SELE) polymorphisms with the prevalence of coronary artery disease in adults suggest a possible association between SELE polymorphisms and the development of CAL in KD patients.

METHODS

The subjects consisted of 177 KD patients, including 59 with and 118 without CAL, and 305 healthy controls. Two single nucleotide polymorphisms (SNP) of SELE, 98G>T (rs1805193) and Ser128Arg (rs5361), were genotyped by direct sequencing and the high-resolution melting curve method, respectively. The allele distributions were assessed using the chi-squared test.

RESULTS

There were no significant differences in the T allele frequency at 98G>T between KD patients and controls (1.4% vs 1.0%, P = 0.55) or between KD patients with and without CAL (1.7% vs 1.3%, P = 0.77). Similarly, there were no differences in the distribution of the C allele (128Arg) at Ser128Arg between KD patients and controls (4.5% vs 3.4%, P = 0.40) or between KD patients with and without CAL (4.2% vs 4.7%, P = 0.86).

CONCLUSION

Although no association was detected between these SELE polymorphisms and the prevalence of KD or the development of CAL, this may have been due to the study limitations, including a low frequency of the minor alleles and a small sample size. A larger-scale association study is needed in order for a definitive conclusion to be made as to whether these SNP are associated with susceptibility to KD or not.

KAREBrowser: SNP database of Korea Association REsource Project

The International HapMap Project and the Human Genome Diversity Project (HGDP) provide plentiful resources on human genome information to the public. However, this kind of information is limited because of the small sample size in both databases. A Genome-Wide Association Study has been conducted with 8,842 Korean subjects as a part of the Korea Association Resource (KARE) project. In an effort to build a publicly available browsing system for genome data resulted from large scale KARE GWAS, we developed the KARE browser. This browser provides users with a large amount of single nucleotide polymorphisms (SNPs) information comprising 1.5 million SNPs from population-based cohorts of 8,842 samples. KAREBrowser was based on the generic genome browser (GBrowse), a webbased application tool developed for users to navigate and visualize the genomic features and annotations in an interactive manner. All SNP information and related functions are available at the web site http://ksnp.cdc. go.kr/karebrowser/.

Genetic variations in the ADAMTS12 gene are associated with schizophrenia in Puerto Rican patients of Spanish descent

ADAMTS12 belongs to the family of metalloproteinases that mediate a communication between specific cell types and play a key role in the regulation of normal tissue development, remodeling, and degradation. Members of this family have been implicated in neurodegenerative and neuroinflammatory, as well as in muscular-skeletal, cardiovascular, respiratory and renal diseases, and cancer. Several metalloproteinases have been associated with schizophrenia. In our previous study of the pedigree from a genetic isolate of Spanish origin in Puerto Rico, we identified a schizophrenia susceptibility locus on chromosome 5p13 containing ADAMTS12. This gene, therefore, is not only a functional but also a positional candidate gene for susceptibility to the disorder. In order to examine possible involvement of ADAMTS12 in schizophrenia, we performed mutation analysis of the coding, 5'- and 3'-untranslated, and putative promoter regions of the gene in affected members of the pedigree and identified 18 sequence variants segregated with schizophrenia. We then tested these variants in 135 unrelated Puerto Rican schizophrenia patients of Spanish origin and 203 controls and identified the intronic variant rs256792 (P = 0.0035; OR = 1.59; 95% CI = 1.16-2.17) and the two-SNP haplotype rs256603-rs256792 (P = 0.0023; OR = 1.62; 95% CI = 1.19-2.21) associated with the disorder. The association remained significant after correction for multiple testing. Our data support the hypothesis that genetic variations in ADAMTS12 influence the risk of schizophrenia.

A systems genetics approach provides a bridge from discovered genetic variants to biological pathways in rheumatoid arthritis

Genome-wide association studies (GWAS) have yielded novel genetic loci underlying common diseases. We propose a systems genetics approach to utilize these discoveries for better understanding of the genetic architecture of rheumatoid arthritis (RA). Current evidence of genetic associations with RA was sought through PubMed and the NHGRI GWAS catalog. The associations of 15 single nucleotide polymorphisms and HLA-DRB1 alleles were confirmed in 1,287 cases and 1,500 controls of Japanese subjects. Among these, HLA-DRB1 alleles and eight SNPs showed significant associations and all but one of the variants had the same direction of effect as identified in the previous studies, indicating that the genetic risk factors underlying RA are shared across populations. By receiver operating characteristic curve analysis, the area under the curve (AUC) for the genetic risk score based on the selected variants was 68.4%. For seropositive RA patients only, the AUC improved to 70.9%, indicating good but suboptimal predictive ability. A simulation study shows that more than 200 additional loci with similar effect size as recent GWAS findings or 20 rare variants with intermediate effects are needed to achieve AUC = 80.0%. We performed the random walk with restart (RWR) algorithm to prioritize genes for future mapping studies. The performance of the algorithm was confirmed by leave-one-out cross-validation. The RWR algorithm pointed to ZAP70 in the first rank, in which mutation causes RA-like autoimmune arthritis in mice. By applying the hierarchical clustering method to a subnetwork comprising RA-associated genes and top-ranked genes by the RWR, we found three functional modules relevant to RA etiology: "leukocyte activation and differentiation", "pattern-recognition receptor signaling pathway", and "chemokines and their receptors".These results suggest that the systems genetics approach is useful to find directions of future mapping strategies to illuminate biological pathways.

Comparative analysis of copy number variation detection methods and database construction

Background

Array-based detection of copy number variations (CNVs) is widely used for identifying disease-specific genetic variations. However, the accuracy of CNV detection is not sufficient and results differ depending on the detection programs used and their parameters. In this study, we evaluated five widely used CNV detection programs, Birdsuite (mainly consisting of the Birdseye and Canary modules), Birdseye (part of Birdsuite), PennCNV, CGHseg, and DNAcopy from the viewpoint of performance on the Affymetrix platform using HapMap data and other experimental data. Furthermore, we identified CNVs of 180 healthy Japanese individuals using parameters that showed the best performance in the HapMap data and investigated their characteristics.

Results

The results indicate that Hidden Markov model-based programs PennCNV and Birdseye (part of Birdsuite), or Birdsuite show better detection performance than other programs when the high reproducibility rates of the same individuals and the low Mendelian inconsistencies are considered. Furthermore, when rates of overlap with other experimental results were taken into account, Birdsuite showed the best performance from the view point of sensitivity but was expected to include many false negatives and some false positives. The results of 180 healthy Japanese demonstrate that the ratio containing repeat sequences, not only segmental repeats but also long interspersed nuclear element (LINE) sequences both in the start and end regions of the CNVs, is higher in CNVs that are commonly detected among multiple individuals than that in randomly selected regions, and the conservation score based on primates is lower in these regions than in randomly selected regions. Similar tendencies were observed in HapMap data and other experimental data.

Conclusions

Our results suggest that not only segmental repeats but also interspersed repeats, especially LINE sequences, are deeply involved in CNVs, particularly in common CNV formations.

The detected CNVs are stored in the CNV repository database newly constructed by the "Japanese integrated database project" for sharing data among researchers. http://gwas.lifesciencedb.jp/cgi-bin/cnvdb/cnv_top.cgi

Using ancestry matching to combine family-based and unrelated samples for genome-wide association studies

We propose a method to analyze family-based samples together with unrelated cases and controls. The method builds on the idea of matched case-control analysis using conditional logistic regression (CLR). For each trio within the family, a case (the proband) and matched pseudo-controls are constructed, based upon the transmitted and untransmitted alleles. Unrelated controls, matched by genetic ancestry, supplement the sample of pseudo-controls; likewise unrelated cases are also paired with genetically matched controls. Within each matched stratum, the case genotype is contrasted with control/pseudo-control genotypes via CLR, using a method we call matched-CLR (mCLR). Eigenanalysis of numerous SNP genotypes provides a tool for mapping genetic ancestry. The result of such an analysis can be thought of as a multidimensional map, or eigenmap, in which the relative genetic similarities and differences amongst individuals is encoded in the map. Once constructed, new individuals can be projected onto the ancestry map based on their genotypes. Successful differentiation of individuals of distinct ancestry depends on having a diverse, yet representative sample from which to construct the ancestry map. Once samples are well-matched, mCLR yields comparable power to competing methods while ensuring excellent control over Type I error.

Meta-analysis of genome-wide association scans for genetic susceptibility to endometriosis in Japanese population

To identify susceptibility genes for endometriosis in Japanese women, genome-wide association (GWA) analysis was performed using two case-control cohorts genotyped with the Affymetrix Mapping 500K Array or Genome-Wide Human SNP Array 6.0. In each of the two array cohorts, stringent quality control (QC) filters were applied to newly obtained genotype data, together with previously analyzed data from the Japanese Integrated Database Project. After QC-based filtering of samples and single nucleotide polymorphisms (SNPs) in each cohort, 282 838 SNPs in both genotyping platforms were tested for association with endometriosis using a meta-analysis of the two GWA studies with 696 patients with endometriosis and 825 controls. The meta-analysis revealed that a common susceptibility locus conferring a large effect on the disease risk was unlikely. On the other hand, an excess of SNPs with P-values <10(-4) (36 vs 28 SNPs expected by chance) was observed in the meta-analysis. Of note, four of the top five SNPs with P-values <10(-5) were located in and around IL1A (interleukin 1α), which might be a functional candidate gene for endometriosis. Further studies with larger case-control cohorts will be necessary to elucidate the genetic risk factors.

PhysiomeSpace: digital library service for biomedical data

Every research laboratory has a wealth of biomedical data locked up, which, if shared with other experts, could dramatically improve biomedical and healthcare research. With the PhysiomeSpace service, it is now possible with a few clicks to share with selected users biomedical data in an easy, controlled and safe way. The digital library service is managed using a client-server approach. The client application is used to import, fuse and enrich the data information according to the PhysiomeSpace resource ontology and upload/download the data to the library. The server services are hosted on the Biomed Town community portal, where through a web interface, the user can complete the metadata curation and share and/or publish the data resources. A search service capitalizes on the domain ontology and on the enrichment of metadata for each resource, providing a powerful discovery environment. Once the users have found the data resources they are interested in, they can add them to their basket, following a metaphor popular in e-commerce web sites. When all the necessary resources have been selected, the user can download the basket contents into the client application. The digital library service is now in beta and open to the biomedical research community.