Takashi Morizono

National Center for Geriatrics and Gerontology

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Tatsuhiko Tsunoda

The University of Tokyo

Michiaki Kubo

RIKEN Center for Integrative Medical Sciences

Naoyuki Kamatani

StaGen (Japan)

Kouichi Ozaki

National Center for Geriatrics and Gerontology

Atsushi Takahashi

Hakodate National Hospital

Yusuke Nakamura

The University of Tokyo

Daichi Shigemizu

National Center for Geriatrics and Gerontology

Yukinori Okada

Osaka University

Akinori Miyashita

Niigata University

Takeshi Ikeuchi

Niigata University

Cooperative Institutions

Molecular Biology Consortium

238

Instituto de Salud Carlos III

The University of Tokyo

Biomedical Research Networking Center on Neurodegenerative Diseases

Erasmus MC

University College London

Inserm

RIKEN Center for Integrative Medical Sciences

Boston University

Fundació ACE

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Genome-Wide Association Study of Peripheral Arterial Disease in a Japanese Population

PLoS ONE (2015)

Mitsuru Matsukura Kouichi Ozaki Atsushi Takahashi Yoshihiro Onouchi Takashi Morizono

Characteristics of peripheral arterial disease (PAD) are the occlusion or stenosis of multiple vessel sites caused mainly by atherosclerosis and chronic lower limb ischemia. To identify PAD susceptible loci, we conducted a genome-wide association study (GWAS) with 785 cases and 3,383 controls in a Japanese population using 431,666 single nucleotide polymorphisms (SNP). After staged analyses including a total of 3,164 cases and 20,134 controls, we identified 3 novel PAD susceptibility loci at IPO5/RAP2A, EDNRA and HDAC9 with genome wide significance (combined P = 6.8 x 10-14, 5.3 x 10-9 and 8.8 x 10-8, respectively). Fine-mapping at the IPO5/RAP2A locus revealed that rs9584669 conferred risk of PAD. Luciferase assay showed that the risk allele at this locus reduced expression levels of IPO5. To our knowledge, these are the first genetic risk factors for PAD.

Genome-wide Association Study

Genetic Association

10.1371/journal.pone.0139262

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Citations (43)

Reproducibility, Performance, and Clinical Utility of a Genetic Risk Prediction Model for Prostate Cancer in Japanese

PLoS ONE (2012)

Shusuke Akamatsu Atsushi Takahashi Ryo Takata Michiaki Kubo Takahiro Inoue

Prostate specific antigen (PSA) is widely used as a diagnostic biomarker for prostate cancer (PC). However, due to its low predictive performance, many patients without PC suffer from the harms of unnecessary prostate needle biopsies. The present study aims to evaluate the reproducibility and performance of a genetic risk prediction model in Japanese and estimate its utility as a diagnostic biomarker in a clinical scenario. We created a logistic regression model incorporating 16 SNPs that were significantly associated with PC in a genome-wide association study of Japanese population using 689 cases and 749 male controls. The model was validated by two independent sets of Japanese samples comprising 3,294 cases and 6,281 male controls. The areas under curve (AUC) of the model were 0.679, 0.655, and 0.661 for the samples used to create the model and those used for validation. The AUCs were not significantly altered in samples with PSA 1–10 ng/ml. 24.2% and 9.7% of the patients had odds ratio <0.5 (low risk) or >2 (high risk) in the model. Assuming the overall positive rate of prostate needle biopsies to be 20%, the positive biopsy rates were 10.7% and 42.4% for the low and high genetic risk groups respectively. Our genetic risk prediction model for PC was highly reproducible, and its predictive performance was not influenced by PSA. The model could have a potential to affect clinical decision when it is applied to patients with gray-zone PSA, which should be confirmed in future clinical studies.

Prostate biopsy

10.1371/journal.pone.0046454

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Citations (30)

Identification of a set of genes associated with response to interleukin-2 and interferon-α combination therapy for renal cell carcinoma through genome-wide gene expression profiling

Experimental and Therapeutic Medicine (2010)

Osamu Mizumori Hitoshi Zembutsu Yoichiro Kato Tatsuhiko Tsunoda Fuyuki Miya

Interleukin (IL)-2 and interferon (IFN)-α combination therapy for metastatic renal cell carcinoma (RCC) improves the prognosis for a subset of patients, while some patients suffer from severe adverse drug reactions with little benefit. To establish a method to predict responses to this combination therapy (approximately 30% response rate), the gene expression profiles of primary RCCs were analyzed using an oligoDNA microarray consisting of 38,500 genes or ESTs, after enrichment of the cancer cell population by laser microbeam microdissection. The analysis of 10 responders and 18 non-responders identified 24 genes that exhibited significant differential expression between the two groups. In addition, the patients whose tumors did not express HLA-DQA1 or HLA-DQB1 molecules demonstrated poor clinical response. Exclusion of patients with tumors lacking either of these two genes is likely to improve the response rate to IL-2 and IFN-α combination therapy from 30 to 67%, indicating that a simple pretreatment test provides useful information with which to subselect patients with renal cancer in order to improve the efficacy of this treatment and reduce unnecessary medical costs.

Gene chip analysis

10.3892/etm.2010.148

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Citations (6)

The Construction of Risk Prediction Models Using GWAS Data and Its Application to a Type 2 Diabetes Prospective Cohort

PLoS ONE (2014)

Daichi Shigemizu Testuo Abe Takashi Morizono Todd A. Johnson Keith A. Boroevich

Recent genome-wide association studies (GWAS) have identified several novel single nucleotide polymorphisms (SNPs) associated with type 2 diabetes (T2D). Various models using clinical and/or genetic risk factors have been developed for T2D risk prediction. However, analysis considering algorithms for genetic risk factor detection and regression methods for model construction in combination with interactions of risk factors has not been investigated. Here, using genotype data of 7,360 Japanese individuals, we investigated risk prediction models, considering the algorithms, regression methods and interactions. The best model identified was based on a Bayes factor approach and the lasso method. Using nine SNPs and clinical factors, this method achieved an area under a receiver operating characteristic curve (AUC) of 0.8057 on an independent test set. With the addition of a pair of interaction factors, the model was further improved (p-value 0.0011, AUC 0.8085). Application of our model to prospective cohort data showed significantly better outcome in disease-free survival, according to the log-rank trend test comparing Kaplan-Meier survival curves (p--value 2:09 x 10(-11)). While the major contribution was from clinical factors rather than the genetic factors, consideration of genetic risk factors contributed to an observable, though small, increase in predictive ability. This is the first report to apply risk prediction models constructed from GWAS data to a T2D prospective cohort. Our study shows our model to be effective in prospective prediction and has the potential to contribute to practical clinical use in T2D.

Genome-wide Association Study

Lasso

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Predictive modelling

10.1371/journal.pone.0092549

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Citations (34)

A second generation human haplotype map of over 3.1 million SNPs

Nature (2007)

Kelly A. Frazer Dennis G. Ballinger David R. Cox David A. Hinds Laura L. Stuvé

International HapMap Project

Linkage Disequilibrium

Imputation (statistics)

Genetic Association

Tag SNP

SNP genotyping

10.1038/nature06258

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Citations (4,453)

Multiancestry analysis of the HLA locus in Alzheimer’s and Parkinson’s diseases uncovers a shared adaptive immune response mediated by HLA-DRB1*04 subtypes

Proceedings of the National Academy of Sciences (2023)

Yann Le Guen Guo Luo Aditya Ambati Vincent Damotte Iris E. Jansen

Across multiancestry groups, we analyzed Human Leukocyte Antigen (HLA) associations in over 176,000 individuals with Parkinson's disease (PD) and Alzheimer's disease (AD) versus controls. We demonstrate that the two diseases share the same protective association at the HLA locus. HLA-specific fine-mapping showed that hierarchical protective effects of

10.1073/pnas.2302720120

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Citations (16)

A combination of targeted enrichment methodologies for whole-exome sequencing reveals novel pathogenic mutations

Scientific Reports (2015)

Fuyuki Miya Mitsuhiro Kato Tadashi Shiohama Nobuhiko Okamoto Shinji Saitoh

Abstract Whole-exome sequencing (WES) is a useful method to identify disease-causing mutations, however, often no candidate mutations are identified using commonly available targeted probe sets. In a recent analysis, we also could not find candidate mutations for 20.9% (9/43) of our pedigrees with congenital neurological disorder using pre-designed capture probes (SureSelect V4 or V5). One possible cause for this lack of candidates is that standard WES cannot sequence all protein-coding sequences (CDS) due to capture probe design and regions of low coverage, which account for approximately 10% of all CDS regions. In this study, we combined a selective circularization-based target enrichment method (HaloPlex) with a hybrid capture method (SureSelect V5; WES) and achieved a more complete coverage of CDS regions (~97% of all CDS). We applied this approach to 7 (SureSelect V5) out of 9 pedigrees with no candidates through standard WES analysis and identified novel pathogenic mutations in one pedigree. The application of this effective combination of targeted enrichment methodologies can be expected to aid in the identification of novel pathogenic mutations previously missed by standard WES analysis.

Pedigree chart

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Identification

Exome

10.1038/srep09331

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Citations (15)

Protective association of HLA-DRB1*04 subtypes in neurodegenerative diseases implicates acetylated Tau PHF6 sequences

medRxiv (Cold Spring Harbor Laboratory) (2021)

Yann Le Guen Guo Luo Aditya Ambati Vincent Damotte Iris E. Jansen

Abstract Using genome-wide association data, we analyzed Human Leukocyte Antigen (HLA) associations in over 176,000 individuals with Parkinson’s (PD) or Alzheimer’s (AD) disease versus controls across ancestry groups. A shared genetic association was observed across diseases at rs601945 (PD: odds ratio (OR)=0.84; 95% confidence interval, [0.80; 0.88]; p=2.2×10 −13 ; AD: OR=0.91[0.89; 0.93]; p=1.8×10 −22 ), and with a protective HLA association recently reported in amyotrophic lateral sclerosis (ALS). Hierarchical protective effects of HLA-DRB1 *04 subtypes best accounted for the association, strongest with HLA-DRB1 *04:04 and HLA-DRB1 *04:07, intermediary with HLA-DRB1 *04:01 and HLA-DRB1 *04:03, and absent for HLA-DRB1 *04:05. The same signal was associated with decreased neurofibrillary tangles (but not neuritic plaque density) in postmortem brains and was more strongly associated with Tau levels than Aβ42 levels in the cerebrospinal fluid. Finally, protective HLA-DRB1 *04 subtypes strongly bound the aggregation-prone Tau PHF6 sequence, but only when acetylated at K311, a modification central to aggregation. An HLA-DRB1 *04-mediated adaptive immune response, potentially against Tau, decreases PD, AD and ALS risk, offering the possibility of new therapeutic avenues.

Genetic Association

Tau protein

10.1101/2021.12.26.21268354

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Citations (3)

Artifactually Low Serum Urea Caused by Antibodies to Bacteria Urease

Clinical Chemistry (2000)

Iwao Higashi Takashi Morizono

Bacterial or jack bean urease is used for determining urea in serum or urine (1). We encountered a clinical serum sample with an abnormally low urea value as measured with a reagent containing bacterial urease, but with a normal urea as measured with a urea reagent containing jack bean urease. We believed that the low urea value was caused by an inhibitor of bacterial urease activity, potentially an immunoglobulin. Although enzyme-binding human immunoglobulins have been reported for lactate dehydrogenase, alkaline phosphatase, and amylase (2)(3), no cases have been reported of immunoglobulin against non-human urease. To investigate the possible presence of immunoglobulins that bind bacterial urease, we used an ELISA method to react bacterial urease with serum from the patient; we measured the urea after serum IgG was removed by adsorption to protein A. Serum samples obtained on admission and discharge were stored at −20 °C until use. Urea and immunoglobulin were measured with a Hitachi model 7150 analyzer. The urea measurement methods (Iatron) were (a) a colorimetric jack bean urease method with indophenol, (b) a jack bean urease method with glutamate dehydrogenase (GLDH) for ultraviolet detection of generated ammonia, and (c) a bacterial urease method with GLDH. The method (Iatron) for immunoglobulin (IgG, IgA, and IgM) was a turbidimetric immunoassay. The serum was centrifuged in an ultrafiltration unit (Amicon Centrifree) at 1500 g for 10 …

10.1093/clinchem/46.2.297

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Citations (1)

Empirical Bayes estimation of semi-parametric hierarchical mixture models for unbiased characterization of polygenic disease architectures

bioRxiv (Cold Spring Harbor Laboratory) (2016)

Jo Nishino Yuta Kochi Daichi Shigemizu Mamoru Kato Katsunori Ikari

Abstract Genome-wide association studies (GWAS) suggest that the genetic architecture of complex diseases consists of unexpectedly numerous variants with small effect sizes. However, the polygenic architectures of many diseases have not been well characterized due to lack of simple and fast methods for unbiased estimation of the underlying proportion of disease-associated variants and their effect-size distribution. Applying empirical Bayes estimation of semi-parametric hierarchical mixture models to GWAS summary statistics, we confirmed that schizophrenia was extremely polygenic (∼ 40% risk variants of independent genome-wide SNPs, most within odds ratio (OR)=1.03), whereas rheumatoid arthritis was less polygenic (∼ 4 to 8% risk variants, significant portion reaching OR=1.05 to 1.1). For rheumatoid arthritis, stratified estimations revealed that expression quantitative loci in blood explained large genetic variance, and low- and high-frequency derived alleles were prone to be risk and protective, respectively, suggesting a predominance of deleterious-risk and advantageous-protective mutation. Despite genetic correlation, effect-size distributions for schizophrenia and bipolar disorder differed across allele frequency. These analyses distinguished disease polygenic architectures and provided clues for etiological differences in complex diseases.

Genome-wide Association Study

Genetic architecture

Genetic Association

10.1101/080945

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Citations (2)