Daichi Shigemizu

PathPred: an enzyme-catalyzed metabolic pathway prediction server

The KEGG RPAIR database is a collection of biochemical structure transformation patterns, called RDM patterns, and chemical structure alignments of substrate-product pairs (reactant pairs) in all known enzyme-catalyzed reactions taken from the Enzyme Nomenclature and the KEGG PATHWAY database. Here, we present PathPred (http://www.genome.jp/tools/pathpred/), a web-based server to predict plausible pathways of muti-step reactions starting from a query compound, based on the local RDM pattern match and the global chemical structure alignment against the reactant pair library. In this server, we focus on predicting pathways for microbial biodegradation of environmental compounds and biosynthesis of plant secondary metabolites, which correspond to characteristic RDM patterns in 947 and 1397 reactant pairs, respectively. The server provides transformed compounds and reference transformation patterns in each predicted reaction, and displays all predicted multi-step reaction pathways in a tree-shaped graph.

Whole-genome mutational landscape of liver cancers displaying biliary phenotype reveals hepatitis impact and molecular diversity

Intrahepatic cholangiocarcinoma and combined hepatocellular cholangiocarcinoma show varying degrees of biliary epithelial differentiation, which can be defined as liver cancer displaying biliary phenotype (LCB). LCB is second in the incidence for liver cancers with and without chronic hepatitis background and more aggressive than hepatocellular carcinoma (HCC). To gain insight into its molecular alterations, we performed whole-genome sequencing analysis on 30 LCBs. Here we show, the genome-wide substitution patterns of LCBs developed in chronic hepatitis livers overlapped with those of 60 HCCs, whereas those of hepatitis-negative LCBs diverged. The subsequent validation study on 68 LCBs identified recurrent mutations in TERT promoter, chromatin regulators (BAP1, PBRM1 and ARID2), a synapse organization gene (PCLO), IDH genes and KRAS. The frequencies of KRAS and IDHs mutations, which are associated with poor disease-free survival, were significantly higher in hepatitis-negative LCBs. This study reveals the strong impact of chronic hepatitis on the mutational landscape in liver cancer and the genetic diversity among LCBs.

High-Risk Ovarian Cancer Based on 126-Gene Expression Signature Is Uniquely Characterized by Downregulation of Antigen Presentation Pathway

Purpose: High-grade serous ovarian cancers are heterogeneous not only in terms of clinical outcome but also at the molecular level. Our aim was to establish a novel risk classification system based on a gene expression signature for predicting overall survival, leading to suggesting novel therapeutic strategies for high-risk patients. Experimental Design: In this large-scale cross-platform study of six microarray data sets consisting of 1,054 ovarian cancer patients, we developed a gene expression signature for predicting overall survival by applying elastic net and 10-fold cross-validation to a Japanese data set A (n = 260) and evaluated the signature in five other data sets. Subsequently, we investigated differences in the biological characteristics between high- and low-risk ovarian cancer groups. Results: An elastic net analysis identified a 126-gene expression signature for predicting overall survival in patients with ovarian cancer using the Japanese data set A (multivariate analysis, P = 4 × 10−20). We validated its predictive ability with five other data sets using multivariate analysis (Tothills data set, P = 1 × 10−5; Bonomes data set, P = 0.0033; Dressmans data set, P = 0.0016; TCGA data set, P = 0.0027; Japanese data set B, P = 0.021). Through gene ontology and pathway analyses, we identified a significant reduction in expression of immune-response–related genes, especially on the antigen presentation pathway, in high-risk ovarian cancer patients. Conclusions: This risk classification based on the 126-gene expression signature is an accurate predictor of clinical outcome in patients with advanced stage high-grade serous ovarian cancer and has the potential to develop new therapeutic strategies for high-grade serous ovarian cancer patients. Clin Cancer Res; 18(5); 1374–85. ©2012 AACR.

Novel Calmodulin Mutations Associated With Congenital Arrhythmia Susceptibility

Background—Genetic predisposition to life-threatening cardiac arrhythmias such as congenital long-QT syndrome (LQTS) and catecholaminergic polymorphic ventricular tachycardia (CPVT) represent treatable causes of sudden cardiac death in young adults and children. Recently, mutations in calmodulin (CALM1, CALM2) have been associated with severe forms of LQTS and CPVT, with life-threatening arrhythmias occurring very early in life. Additional mutation-positive cases are needed to discern genotype–phenotype correlations associated with calmodulin mutations. Methods and Results—We used conventional and next-generation sequencing approaches, including exome analysis, in genotype-negative LQTS probands. We identified 5 novel de novo missense mutations in CALM2 in 3 subjects with LQTS (p.N98S, p.N98I, p.D134H) and 2 subjects with clinical features of both LQTS and CPVT (p.D132E, p.Q136P). Age of onset of major symptoms (syncope or cardiac arrest) ranged from 1 to 9 years. Three of 5 probands had cardiac arrest and 1 of these subjects did not survive. The clinical severity among subjects in this series was generally less than that originally reported for CALM1 and CALM2 associated with recurrent cardiac arrest during infancy. Four of 5 probands responded to &bgr;-blocker therapy, whereas 1 subject with mutation p.Q136P died suddenly during exertion despite this treatment. Mutations affect conserved residues located within Ca2+-binding loops III (p.N98S, p.N98I) or IV (p.D132E, p.D134H, p.Q136P) and caused reduced Ca2+-binding affinity. Conclusions—CALM2 mutations can be associated with LQTS and with overlapping features of LQTS and CPVT.

Network-based analysis and characterization of adverse drug-drug interactions.

Co-administration of multiple drugs may cause adverse effects, which are usually known but sometimes unknown. Package inserts of prescription drugs are supposed to contain contraindications and warnings on adverse interactions, but such information is not necessarily complete. Therefore, it is becoming more important to provide health professionals with a comprehensive view on drug-drug interactions among all the drugs in use as well as a computational method to identify potential interactions, which may also be of practical value in society. Here we extracted 1,306,565 known drug-drug interactions from all the package inserts of prescription drugs marketed in Japan. They were reduced to 45,180 interactions involving 1352 drugs (active ingredients) identified by the D numbers in the KEGG DRUG database, of which 14,441 interactions involving 735 drugs were linked to the same drug-metabolizing enzymes and/or overlapping drug targets. The interactions with overlapping targets were further classified into three types: acting on the same target, acting on different but similar targets in the same protein family, and acting on different targets belonging to the same pathway. For the rest of the extracted interaction data, we attempted to characterize interaction patterns in terms of the drug groups defined by the Anatomical Therapeutic Chemical (ATC) classification system, where the high-resolution network at the D number level is progressively reduced to a low-resolution global network. Based on this study we have developed a drug-drug interaction retrieval system in the KEGG DRUG database, which may be used for both searching against known drug-drug interactions and predicting potential interactions.

Performance comparison of four commercial human whole-exome capture platforms

Whole exome sequencing (WXS) is widely used to identify causative genetic mutations of diseases. However, not only have several commercial human exome capture platforms been developed, but substantial updates have been released in the past few years. We report a performance comparison for the latest release of four commercial platforms, Roche/NimbleGen’s SeqCap EZ Human Exome Library v3.0, Illumina’s Nextera Rapid Capture Exome (v1.2), Agilent’s SureSelect XT Human All Exon v5 and Agilent’s SureSelect QXT, using the same DNA samples. Agilent XT showed the highest target enrichment efficiency and the best SNV and short indel detection sensitivity in coding regions with the least amount of sequencing. Agilent QXT had slightly inferior target enrichment than Agilent XT. Illumina, with additional sequencing, detected SNVs and short indels at the same quality as Agilent XT, and showed the best performance in coverage of medically interesting mutations. NimbleGen detected more SNVs and indels in untranslated regions than the others. We also found that the platforms, which enzymatically fragment the genomic DNA (gDNA), detected more homozygous SNVs than those using sonicated gDNA. We believe that our analysis will help investigators when selecting a suitable exome capture platform for their particular research.

A practical method to detect SNVs and indels from whole genome and exome sequencing data

The recent development of massively parallel sequencing technology has allowed the creation of comprehensive catalogs of genetic variation. However, due to the relatively high sequencing error rate for short read sequence data, sophisticated analysis methods are required to obtain high-quality variant calls. Here, we developed a probabilistic multinomial method for the detection of single nucleotide variants (SNVs) as well as short insertions and deletions (indels) in whole genome sequencing (WGS) and whole exome sequencing (WES) data for single sample calling. Evaluation with DNA genotyping arrays revealed a concordance rate of 99.98% for WGS calls and 99.99% for WES calls. Sanger sequencing of the discordant calls determined the false positive and false negative rates for the WGS (0.0068% and 0.17%) and WES (0.0036% and 0.0084%) datasets. Furthermore, short indels were identified with high accuracy (WGS: 94.7%, WES: 97.3%). We believe our method can contribute to the greater understanding of human diseases.

IRX4 at 5p15 Suppresses Prostate Cancer Growth through the Interaction with Vitamin D Receptor, Conferring Prostate Cancer Susceptibility

Recent genome-wide association studies (GWAS) identified a number of prostate cancer (PC) susceptibility loci, but most of their functional significances are not elucidated. Through our previous GWAS for PC in a Japanese population and subsequent resequencing and fine mapping, we here identified that IRX4 (Iroquois homeobox 4), coding Iroquois homeobox 4, is a causative gene of the PC susceptibility locus (rs12653946) at chromosome 5p15. IRX4 is expressed specifically in the prostate and heart, and quantitative expression analysis revealed a significant association between the genotype of rs12653946 and IRX4 expression in normal prostate tissues. Knockdown of IRX4 in PC cells enhanced their growth and IRX4 overexpression in PC cells suppressed their growth, indicating the functional association of IRX4 with PC and its tumor suppressive effect. Immunoprecipitation confirmed its protein-protein interaction to vitamin D receptor (VDR), and we found a significant interaction between IRX4 and VDR in their reciprocal transcriptional regulation. These findings indicate that the PC-susceptibility locus represented by rs12653946 at 5p15 is likely to regulate IRX4 expression in prostate which could suppress PC growth by interacting with the VDR pathway, conferring to PC susceptibility.

A genome-wide association study identifies PLCL2 and AP3D1-DOT1L-SF3A2 as new susceptibility loci for myocardial infarction in Japanese

Despite considerable progress in preventive and therapeutic strategies, myocardial infarction (MI) is one of the leading causes of death throughout the world. A total of 55 susceptibility genes have been identified mostly in European genome-wide association studies (GWAS). Nevertheless, large-scale GWAS from other population could possibly find additional susceptibility loci. To identify as many MI susceptibility loci as possible, we performed a large-scale genomic analysis in Japanese population. To identify MI susceptibility loci in Japanese, we conducted a GWAS using 1666 cases and 3198 controls using the Illumina Human610-Quad BeadChip and HumanHap550v3 Genotyping BeadChip. We performed replication studies using a total of 11 412 cases and 28 397 controls in the Japanese population. Our study identified two novel susceptibility loci for MI: PLCL2 on chromosome 3p24.3 (rs4618210:A>G, P=2.60 × 10−9, odds ratio (OR)=0.91) and AP3D1-DOT1L-SF3A2 on chromosome 19p13.3 (rs3803915:A>C, P=3.84 × 10−9, OR=0.89). Besides, a total of 14 previously reported MI susceptibility loci were replicated in our study. In particular, we validated a strong association on chromosome 12q24 (rs3782886:A>G: P=1.14 × 10−14, OR=1.46). Following pathway analysis using 265 genes related to MI or coronary artery disease, we found that these loci might be involved in the pathogenesis of MI via the promotion of atherosclerosis. In the present large-scale genomic analysis, we identified PLCL2 and AP3D1-DOT1L-SF3A2 as new susceptibility loci for MI in the Japanese population. Our findings will add novel findings for MI susceptibility loci.

Assessing the Clinical Utility of a Genetic Risk Score Constructed Using 49 Susceptibility Alleles for Type 2 Diabetes in a Japanese Population

CONTEXT Genome-wide association studies (GWASs) have identified over 60 susceptibility loci for type 2 diabetes (T2D). Although the ability of previous genetic information (∼40 loci) to discriminate between susceptible and nonsusceptible individuals is limited, the added benefit of updated genetic information has not been evaluated. OBJECTIVE We assessed the clinical utility of GWAS-derived T2D susceptibility variants in a Japanese population. DESIGN AND SETTING We conducted a cross-sectional case-control study. PARTICIPANTS T2D cases (n = 2613) and controls (n = 1786) with complete genotype data for 49 single-nucleotide polymorphisms (SNPs) were selected for analyses. OUTCOME MEASURES We constructed genetic risk scores (GRSs) by summing the susceptibility alleles of 49 SNP loci for T2D (GRS-49) or 10 SNP loci with genome-wide significant association in previous Japanese studies (GRS-10) and examined the association of the GRSs with the disease by receiver operating characteristic analyses using a logistic regression model. RESULTS The GRS-49 was significantly associated with T2D (P = 8.75 × 10(-45)). The area under the curve (AUC) for GRS-49 alone (model 1) and for age, sex, and body mass index (model 2) was 0.624 and 0.743, respectively. Addition of the GRS-49 to model 2 resulted in a small but significant increase in the AUC (ΔAUC = 0.03, P = 7.99 × 10(-15)). Receiver operating characteristic AUC was greater for GRS-49 than for GRS-10 (0.624 vs 0.603, P = .019), whereas the odds ratio per risk allele was smaller for GRS-49 than for GRS-10 (GRS-49, 1.13, 95% confidence interval 1.11-1.15; GRS-10, 1.26, 95% confidence interval = 1.22-1.31, P = 7.31 × 10(-10)). The GRS-49 was significantly associated with age at diagnosis in 1591 cases (β = -0.199, P = .0069) and with fasting plasma glucose in 804 controls (β = 0.009, P = 0.021). CONCLUSIONS Updated genetic information slightly improves disease prediction ability but is not sufficiently robust for translation into clinical practice.