Author
Katsushi Tokunaga
Other affiliations: Juntendo University, Gulf Coast Regional Blood Center, Nihon University ...read more
Bio: Katsushi Tokunaga is an academic researcher from University of Tokyo. The author has contributed to research in topics: Haplotype & Population. The author has an hindex of 77, co-authored 711 publications receiving 28016 citations. Previous affiliations of Katsushi Tokunaga include Juntendo University & Gulf Coast Regional Blood Center.
Papers published on a yearly basis
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Nagoya City University1, University of Tokyo2, Tokyo Medical and Dental University3, Hokkaido University4, Kyoto Prefectural University of Medicine5, Shinshu University6, Saitama Medical University7, Tottori University8, Kanazawa University9, Ehime University10, Hyogo College of Medicine11, Hitachi12, Yamaguchi University13
TL;DR: A genome-wide association study to null virological response (NVR) in the treatment of patients with hepatitis C virus (HCV) genotype 1 within a Japanese population is reported.
Abstract: Masashi Mizokami and colleagues report a genome-wide association study to hepatitis C treatment response in two Japanese cohorts. They report common variants at IL28B associated with sustained as well as null virologic response following pegylated interferon-alpha and ribavirin combined therapy.
2,097 citations
TL;DR: There is a retrotransposal insertion of tandemly repeated sequences within this candidate-gene interval in all FCMD chromosomes carrying the founder haplotype (87%).
Abstract: Fukuyama-type congenital muscular dystrophy (FCMD), one of the most common autosomal recessive disorders in Japan (incidence is 0.7-1.2 per 10,000 births), is characterized by congenital muscular dystrophy associated with brain malformation (micropolygria) due to a defect in the migration of neurons. We previously mapped the FCMD gene to a region of less than 100 kilobases which included the marker locus D9S2107 on chromosome 9q31. We have also described a haplotype that is shared by more than 80% of FCMD chromosomes, indicating that most chromosomes bearing the FCMD mutation could be derived from a single ancestor. Here we report that there is a retrotransposal insertion of tandemly repeated sequences within this candidate-gene interval in all FCMD chromosomes carrying the founder haplotype (87%). The inserted sequence is about 3 kilobases long and is located in the 3' untranslated region of a gene encoding a new 461-amino-acid protein. This gene is expressed in various tissues in normal individuals, but not in FCMD patients who carry the insertion. Two independent point mutations confirm that mutation of this gene is responsible for FCMD. The predicted protein, which we term fukutin, contains an amino-terminal signal sequence, which together with results from transfection experiments suggests that fukutin is a secreted protein. To our knowledge, FCMD is the first human disease to be caused by an ancient retrotransposal integration.
772 citations
Kobe University1, Gifu University2, University of Tokyo3, Ehime University4, Wakayama Medical University5, Lund University6, Osaka University7, Chinese Academy of Sciences8, Tohoku University9, University of Tokushima10, Kyoto Prefectural University of Medicine11, Kyoto University12, Shiga University of Medical Science13, New Generation University College14, Seoul National University15, The Chinese University of Hong Kong16, University of Helsinki17, Kyushu University18, National Cancer Research Institute19
TL;DR: The data implicate KCNQ1 as a diabetes susceptibility gene in groups of different ancestries as well as in two independent Japanese populations, and the risk allele of this polymorphism was associated with impairment of insulin secretion according to the homeostasis model assessment of β-cell function or the corrected insulin response.
Abstract: We carried out a multistage genome-wide association study of type 2 diabetes mellitus in Japanese individuals, with a total of 1,612 cases and 1,424 controls and 100,000 SNPs. The most significant association was obtained with SNPs in KCNQ1, and dense mapping within the gene revealed that rs2237892 in intron 15 showed the lowest P value (6.7 x 10(-13), odds ratio (OR) = 1.49). The association of KCNQ1 with type 2 diabetes was replicated in populations of Korean, Chinese and European ancestry as well as in two independent Japanese populations, and meta-analysis with a total of 19,930 individuals (9,569 cases and 10,361 controls) yielded a P value of 1.7 x 10(-42) (OR = 1.40; 95% CI = 1.34-1.47) for rs2237892. Among control subjects, the risk allele of this polymorphism was associated with impairment of insulin secretion according to the homeostasis model assessment of beta-cell function or the corrected insulin response. Our data thus implicate KCNQ1 as a diabetes susceptibility gene in groups of different ancestries.
726 citations
University of Malaya1, Central Food Technological Research Institute2, Thailand National Science and Technology Development Agency3, Mahidol University4, Korea Research Institute of Bioscience and Biotechnology5, University of the Philippines6, Academia Sinica7, Agency for Science, Technology and Research8, Peking Union Medical College9, National Institute of Advanced Industrial Science and Technology10, Universiti Sains Malaysia11, Chinese National Human Genome Center12, Tokai University13, Fudan University14, Chiang Mai University15, Thermo Fisher Scientific16, Soongsil University17, Eulji University18, University of Tokyo19, National University of Singapore20, Indian Statistical Institute21, Eijkman Institute for Molecular Biology22, Nanyang Technological University23, University of the Ryukyus24, Health Sciences University of Hokkaido25, Monash University Malaysia Campus26, National Institutes of Health27
TL;DR: The results suggest that there may have been a single major migration of people into Asia and a subsequent south-to-north migration across the continent, and that genetic ancestry is strongly correlated with linguistic affiliations as well as geography.
Abstract: Asia harbors substantial cultural and linguistic diversity, but the geographic structure of genetic variation across the continent remains enigmatic. Here we report a large-scale survey of autosomal variation from a broad geographic sample of Asian human populations. Our results show that genetic ancestry is strongly correlated with linguistic affiliations as well as geography. Most populations show relatedness within ethnic/linguistic groups, despite prevalent gene flow among populations. More than 90% of East Asian (EA) haplotypes could be found in either Southeast Asian (SEA) or Central-South Asian (CSA) populations and show clinal structure with haplotype diversity decreasing from south to north. Furthermore, 50% of EA haplotypes were found in SEA only and 5% were found in CSA only, indicating that SEA was a major geographic source of EA populations.
545 citations
TL;DR: In this paper, a hypoxia-inducible factor-2alpha (HIF-2α) encoded by EPAS1 was identified as the most potent transactivator of COL10A1, which was essential for endochondral ossification of cultured chondrocytes and embryonic skeletal growth in mice.
Abstract: Chondrocyte hypertrophy followed by cartilage matrix degradation and vascular invasion, characterized by expression of type X collagen (COL10A1), matrix metalloproteinase-13 (MMP-13) and vascular endothelial growth factor (VEGF), respectively, are central steps of endochondral ossification during normal skeletal growth and osteoarthritis development. A COL10A1 promoter assay identified hypoxia-inducible factor-2alpha (HIF-2alpha, encoded by EPAS1) as the most potent transactivator of COL10A1. HIF-2alpha enhanced promoter activities of COL10A1, MMP13 and VEGFA through specific binding to the respective hypoxia-responsive elements. HIF-2alpha, independently of oxygen-dependent hydroxylation, was essential for endochondral ossification of cultured chondrocytes and embryonic skeletal growth in mice. HIF-2alpha expression was higher in osteoarthritic cartilages versus nondiseased cartilages of mice and humans. Epas1-heterozygous deficient mice showed resistance to osteoarthritis development, and a functional single nucleotide polymorphism (SNP) in the human EPAS1 gene was associated with knee osteoarthritis in a Japanese population. The EPAS1 promoter assay identified RELA, a nuclear factor-kappaB (NF-kappaB) family member, as a potent inducer of HIF-2alpha expression. Hence, HIF-2alpha is a central transactivator that targets several crucial genes for endochondral ossification and may represent a therapeutic target for osteoarthritis.
470 citations
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TL;DR: Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function, with tissue-specific developmental regulation, and with the hemostasis and immune systems are indicated.
Abstract: A 2.91-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method. The 14.8-billion bp DNA sequence was generated over 9 months from 27,271,853 high-quality sequence reads (5.11-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals. Two assembly strategies-a whole-genome assembly and a regional chromosome assembly-were used, each combining sequence data from Celera and the publicly funded genome effort. The public data were shredded into 550-bp segments to create a 2.9-fold coverage of those genome regions that had been sequenced, without including biases inherent in the cloning and assembly procedure used by the publicly funded group. This brought the effective coverage in the assemblies to eightfold, reducing the number and size of gaps in the final assembly over what would be obtained with 5.11-fold coverage. The two assembly strategies yielded very similar results that largely agree with independent mapping data. The assemblies effectively cover the euchromatic regions of the human chromosomes. More than 90% of the genome is in scaffold assemblies of 100,000 bp or more, and 25% of the genome is in scaffolds of 10 million bp or larger. Analysis of the genome sequence revealed 26,588 protein-encoding transcripts for which there was strong corroborating evidence and an additional approximately 12,000 computationally derived genes with mouse matches or other weak supporting evidence. Although gene-dense clusters are obvious, almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence. Only 1.1% of the genome is spanned by exons, whereas 24% is in introns, with 75% of the genome being intergenic DNA. Duplications of segmental blocks, ranging in size up to chromosomal lengths, are abundant throughout the genome and reveal a complex evolutionary history. Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function, with tissue-specific developmental regulation, and with the hemostasis and immune systems. DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 2.1 million single-nucleotide polymorphisms (SNPs). A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average, but there was marked heterogeneity in the level of polymorphism across the genome. Less than 1% of all SNPs resulted in variation in proteins, but the task of determining which SNPs have functional consequences remains an open challenge.
12,098 citations
Journal Article•
TL;DR: It is suggested that the natural selection against large insertion/deletion is so weak that a large amount of variation is maintained in a population.
11,521 citations
TL;DR: A unified analytic framework to discover and genotype variation among multiple samples simultaneously that achieves sensitive and specific results across five sequencing technologies and three distinct, canonical experimental designs is presented.
Abstract: Recent advances in sequencing technology make it possible to comprehensively catalogue genetic variation in population samples, creating a foundation for understanding human disease, ancestry and evolution. The amounts of raw data produced are prodigious and many computational steps are required to translate this output into high-quality variant calls. We present a unified analytic framework to discover and genotype variation among multiple samples simultaneously that achieves sensitive and specific results across five sequencing technologies and three distinct, canonical experimental designs. Our process includes (1) initial read mapping; (2) local realignment around indels; (3) base quality score recalibration; (4) SNP discovery and genotyping to find all potential variants; and (5) machine learning to separate true segregating variation from machine artifacts common to next-generation sequencing technologies. We discuss the application of these tools, instantiated in the Genome Analysis Toolkit (GATK), to deep whole-genome, whole-exome capture, and multi-sample low-pass (~4×) 1000 Genomes Project datasets.
10,056 citations
National Institutes of Health1, University of Chicago2, Duke University3, Harvard University4, University of Oxford5, GlaxoSmithKline6, Johns Hopkins University7, Yale University8, deCODE genetics9, Howard Hughes Medical Institute10, Princeton University11, Washington University in St. Louis12, University of California, Berkeley13, Stanford University14, University of Michigan15, Cornell University16, University of Washington17, University of Queensland18, Vanderbilt University19, North Carolina State University20, QIMR Berghofer Medical Research Institute21
TL;DR: This paper examined potential sources of missing heritability and proposed research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.
Abstract: Genome-wide association studies have identified hundreds of genetic variants associated with complex human diseases and traits, and have provided valuable insights into their genetic architecture. Most variants identified so far confer relatively small increments in risk, and explain only a small proportion of familial clustering, leading many to question how the remaining, 'missing' heritability can be explained. Here we examine potential sources of missing heritability and propose research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.
7,797 citations
TL;DR: March 5, 2019 e1 WRITING GROUP MEMBERS Emelia J. Virani, MD, PhD, FAHA, Chair Elect On behalf of the American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee.
Abstract: March 5, 2019 e1 WRITING GROUP MEMBERS Emelia J. Benjamin, MD, ScM, FAHA, Chair Paul Muntner, PhD, MHS, FAHA, Vice Chair Alvaro Alonso, MD, PhD, FAHA Marcio S. Bittencourt, MD, PhD, MPH Clifton W. Callaway, MD, FAHA April P. Carson, PhD, MSPH, FAHA Alanna M. Chamberlain, PhD Alexander R. Chang, MD, MS Susan Cheng, MD, MMSc, MPH, FAHA Sandeep R. Das, MD, MPH, MBA, FAHA Francesca N. Delling, MD, MPH Luc Djousse, MD, ScD, MPH Mitchell S.V. Elkind, MD, MS, FAHA Jane F. Ferguson, PhD, FAHA Myriam Fornage, PhD, FAHA Lori Chaffin Jordan, MD, PhD, FAHA Sadiya S. Khan, MD, MSc Brett M. Kissela, MD, MS Kristen L. Knutson, PhD Tak W. Kwan, MD, FAHA Daniel T. Lackland, DrPH, FAHA Tené T. Lewis, PhD Judith H. Lichtman, PhD, MPH, FAHA Chris T. Longenecker, MD Matthew Shane Loop, PhD Pamela L. Lutsey, PhD, MPH, FAHA Seth S. Martin, MD, MHS, FAHA Kunihiro Matsushita, MD, PhD, FAHA Andrew E. Moran, MD, MPH, FAHA Michael E. Mussolino, PhD, FAHA Martin O’Flaherty, MD, MSc, PhD Ambarish Pandey, MD, MSCS Amanda M. Perak, MD, MS Wayne D. Rosamond, PhD, MS, FAHA Gregory A. Roth, MD, MPH, FAHA Uchechukwu K.A. Sampson, MD, MBA, MPH, FAHA Gary M. Satou, MD, FAHA Emily B. Schroeder, MD, PhD, FAHA Svati H. Shah, MD, MHS, FAHA Nicole L. Spartano, PhD Andrew Stokes, PhD David L. Tirschwell, MD, MS, MSc, FAHA Connie W. Tsao, MD, MPH, Vice Chair Elect Mintu P. Turakhia, MD, MAS, FAHA Lisa B. VanWagner, MD, MSc, FAST John T. Wilkins, MD, MS, FAHA Sally S. Wong, PhD, RD, CDN, FAHA Salim S. Virani, MD, PhD, FAHA, Chair Elect On behalf of the American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee
5,739 citations