2025
63. Mitsumori R, Sawamura K, Yamakoshi K, Nakamura A, Arahata Y, Niida S, Shigemizu D, Ozaki K, and Shimoda N. Identification of diagnostic DNA methylation markers in the blood of Japanese Alzheimer's disease patients using methylation capture sequencing. Clin Epigenetics 2025 Jun 20;17(1):107. (News & Topics)
62. Fujita K, Kimura T, Yamakawa A, Niida S, Ozaki K, Sakurai T, Arai H, and Shigemizu D*. Genetic background and multidomain interventions in mild cognitive impairment. Alzheimers Res Ther. 2025 Jun 10;17(1):130. (プレスリリース）(毎日新聞)（GemMed)
61. Sakai T, Furutani M, Nakashima M, Ishibashi N, Maeda J, Oguri N, Miyamoto S, Miyauchi S, Okamura S, Okubo Y, Tokuyama T, Oda N, Mitsumori R, Niida S, Ozaki K, Shigemizu D*, and Nakano Y*. Genome-wide association study of atrial fibrillation recurrence after radiofrequency catheter ablation in a Japanese population. J Cardiovasc Electrophysiol 2025 Apr 28.
60. Furutani M, Kimura T, Fukunaga K, Suganuma M, Takemura M, Matsui Y, Satake S, Nakano Y, Mushiroda T, Niida S, Ozaki K, Hosoyama T*, and Shigemizu D*. Identification of a risk allele at SLC41A3 and a protective allele HLA-DPB1*02:01 associated with sarcopenia in Japanese. Gerontology 2025 Mar 18;376–387. (News & Topics)
59. Mitsumori R, Asanomi Y, Morizono T, Shigemizu D, Niida S, and Ozaki K. A genome-wide association study identifies a novel East Asian-specific locus for dementia with Lewy bodies in Japanese subjects. Mol Med. 2025 Mar 6;31(1):87. (プレスリリース)
58. Yamakawa A, Suganuma M, Mitsumori R, Niida S, Ozaki K, and Shigemizu D.* Alzheimer’s disease may develop from changes in the immune system, cell cycle, and protein processing following alterations in ribosome function. Sci Rep. 2025 Jan 30;15(1):3838. (News & Topics)
2024
57. Kimura T, Fujita K, Sakurai T, Niida S, Ozaki K, and Shigemizu D.* Whole-genome sequencing to identify rare variants in East Asian patients with dementia with Lewy bodies. npj Aging. 2024 Nov 21;10(1):52. (News & Topics)
56. Suganuma M, Furutani M, Hosoyama T, Mitsumori R, Otsuka R, Takemura M, Matsui Y, Nakano Y, Niida S, Ozaki K, Satake S, and Shigemizu D.* Identification of potential blood-based biomarkers for frailty by using an integrative approach. Gerontology. 2024;70(6):630-638. (News & Topics)
55. Asanomi Y, Kimura T, Shimoda N, Shigemizu D, Niida S, and Ozaki K. CRISPR/Cas9-mediated knock-in cells of the late-onset Alzheimer’s disease-risk variant, SHARPIN G186R, reveal reduced NF-κB pathway and accelerated Aβ secretion. J Hum Genet. 2024 May;69(5):171-176. (News & Topics)
54. Shigemizu D*, Fukunaga K, Yamakawa A, Suganuma M, Fujita K, Kimura T, Watanabe K, Mushiroda T, Sakurai T, Niida S, and Ozaki K. The HLA-DRB1*09:01-DQB1*03:03 haplotype is associated with the risk for late-onset Alzheimer’s disease in APOE ε4–negative Japanese adults. npj Aging. 2024 Jan 2;10(1):3. (プレスリリース)
53. Li J, Hosoyama T, Shigemizu D, Yasuoka M, Kinoshita K, Maeda K, Takemura M, Matsui Y, Arai H, and Satake S. Association between circulating levels of CXCL9 and CXCL10 and physical frailty in older adults. Gerontology. 2024;70(3):279-289.
2023
52. Shigemizu D*, Akiyama S, Suganuma M, Furutani M, Yamakawa A, Nakano Y, Ozaki K, and Niida S. Classification and deep-learning-based prediction of Alzheimer disease subtypes by using genomic data. Transl Psychiatry. 2023 June 29;13:232.
51. Furutani M, Suganuma M, Akiyama S, Mitsumori R, Takemura M, Matsui Y, Satake S, Nakano Y, Niida S, Ozaki K, Hosoyama T, and Shigemizu D.* RNA-sequencing analysis identification of potential biomarkers for diagnosis of sarcopenia. J Gerontol A Biol Sci Med Sci. 2023 Jun 22;glad150. (プレスリリース)
2022
50. Shigemizu D*, Akiyama S, Mitsumori R, Niida S, and Ozaki K. Identification of potential blood biomarkers for early diagnosis of Alzheimer’s disease through immune landscape analysis. npj Aging. 2022 Nov 4;8(1):15.
49. Shigemizu D*, Asanomi Y, Akiyama S, Higaki S, Sakurai T, Ito K, Niida S, and Ozaki K. Network-based meta-analysis and the candidate gene association studies reveal novel ethnicity-specific variants in MFSD3 and MRPL43 associated with dementia with Lewy bodies. Am J Med Genet B Neuropsychiatr Genet. 2022 Jul;189(5):139-150. (プレスリリース, 脳のはなし)
48. Shigemizu D*, Asanomi Y, Akiyama S, Mitsumori R, Niida S, and Ozaki K. Whole-genome sequencing reveals novel ethnicity-specific rare variants associated with Alzheimer's disease. Mol Psychiatry. 2022 May;27(5):2554-2562. (プレスリリース)
2021
47. Asanomi Y, Shigemizu D, Akiyama S, Miyashita A, Mitsumori R, Hara N, Ikeuchi T, Niida S, and Ozaki K. A functional variant of SHARPIN confers increased risk of late-onset Alzheimer’s disease. J Hum Genet. 2021 Nov 5.
46. Akiyama S, Higaki S, Ochiya T, Ozaki K, Niida S*, and Shigemizu D.* JAMIR-eQTL: Japanese genome–wide identification of microRNA expression quantitative trait loci across dementia types. Database (Oxford). 2021 Nov 3;2021(2021):baab072.
45. Asanomi Y, Shigemizu D*, Akiyama S, Sakurai T, Ozaki K, Ochiya T, and Niida S*. Dementia subtype prediction models constructed by penalized regression methods for multiclass classification using serum microRNA expression data. Sci Rep. 2021 Oct 22;11(1):20947.
44. Fujimoto A, Wong JH, Yoshii Y, Akiyama S, Tanaka A, Yagi H, Shigemizu D, Nakagawa H, Mizokami M, and Shimada M. Whole-genome sequencing with long reads reveals complex structure and origin of structural variation in human genetic variations and somatic mutations in cancer. Genome Med. 2021 Apr 29;13(1):65.
43. Shigemizu D*, Mitsumori R, Akiyama S, Miyashita A, Morizono T, Higaki S, Asanomi Y, Hara N, Tamiya G, Kinoshita K, Ikeuchi T, Niida S, and Ozaki K. Ethnic and trans-ethnic genome-wide association studies identify new loci influencing Japanese Alzheimer’s disease risk. Transl Psychiatry. 2021 Mar 3;11(1):151. (プレスリリース)
2020
42. Shigemizu D*, Akiyama S, Higaki S, Sugimoto T, Sakurai T, Boroevich KA, Sharma A, Tsunoda T, Ochiya T, Niida S, and Ozaki K. Prognosis prediction model for conversion from mild cognitive impairment to Alzheimer’s disease created by integrative analysis of multi-omics data. Alzheimers Res Ther. 2020 Nov 10;12(1):145.
41. Mitsumori R, Sakaguchi K, Shigemizu D, Mori T, Akiyama S, Ozaki K, Niida S, and Shimoda N. Lower DNA methylation levels in CpG island shores of CR1, CLU, and PICALM in the blood of Japanese Alzheimer's disease patients. PLoS One. 2020 Sep 29;15(9):e0239196.
40. Shigemizu D*, Mori T, Akiyama S, Higaki S, Watanabe H, Sakurai T, Niida S, and Ozaki K. Identification of potential biomarkers for early diagnosis of Alzheimer's disease through RNA sequencing analysis. Alzheimers Res Ther. 2020 Jul 16;12(1):87.(プレスリリース）
2019
39. Chandra A, Sharma A, Dehzangi A, Shigemizu D, and Tsunoda T. Bigram-PGK: phosphoglycerylation prediction using the technique of bigram probabilities of position specific scoring matrix. BMC Mol Cell Biol. 2019 Dec 20;20(Suppl 2):57.
38. Shigemizu D*, Akiyama S, Asanomi Y, Boroevich KA, Sharma A, Tsunoda T, Sakurai T, Ozaki K, Ochiya T, and Niida S. A comparison of machine learning classifiers for dementia with Lewy bodies using miRNA expression data. BMC Med Genomics. 2019 Oct 30;12(1):150.
37. Sharma A, Vans E, Shigemizu D, Boroevich KA, and Tsunoda T. DeepInsight: a methodology to transform a non-image data to an image for convolution neural network architecture. Sci Rep. 2019 Aug 6;9(1):11399.(プレスリリース)
36. Wong JH, Shigemizu D, Yoshii Y, Akiyama S, Tanaka A, Nakagawa H, Narumiya S, and Fujimoto A. Identification of intermediate-sized deletions and inference of their impact on gene expression in a human population. Genome Med. 2019 Jul 24;11(1):44.
35. Asanomi Y, Shigemizu D, Miyashita A, Mitsumori R, Mori T, Ito K, Niida S, Ikeuchi T, and Ozaki K. A rare functional variant of SHARPIN attenuates the inflammatory response and associates with increased risk of late-onset Alzheimer's disease. Mol Med. 2019 Jun 20;25(1):2. (プレスリリース)
34. Singh V, Sharma A, Chandra A, Dehzangi A, Shigemizu D, and Tsunoda T. Computational prediction of Lysine pupylation sites in prokaryotic proteins using position specific scoring matrix into bigram for feature extraction. Lect Notes in Artificial Intelligence. 2019 Part III, pp.488-500.
33. Vans E, Sharma A, Patil A, Shigemizu D, and Tsunoda T. Clustering of Small-Sample Single-Cell RNA-Seq data via Feature Clustering and Selection. Lect Notes in Artificial Intelligence. 2019 Part III, pp.445-456.
32. Shigemizu D*, Akiyama S, Asanomi Y, Boroevich KA, Sharma A, Tsunoda T, Matsukuma K, Ichikawa M, Sudo H, Takizawa S, Sakurai T, Ozaki K, Ochiya T, and Niida S. Risk prediction models for dementia constructed by supervised principal component analysis using miRNA expression data. Commun Biol. 2019 Feb.25;2:77.(プレスリリース)
31. Reddy HM, Sharma A, Dehzangi A, Shigemizu D, Chandra A, and Tsunoda T. GlyStruct: Glycation prediction using structural properties of amino acid residues. BMC Bioinformatics. 2019 19(Suppl 13):547.
2018
30. Yamaguchi-Kabata Y, Morihara T, Ohara T, Ninomiya T, Takahashi A, Akatsu H, Hashizume Y, Hayashi N, Shigemizu D, Boroevich KA, Ikeda M, Kubo M, Takeda M, and Tsunoda T. Integrated analysis of human genetic association study and mouse transcriptome suggests LBH and SHF genes as novel susceptible genes for amyloid-β accumulation in Alzheimer’s disease. Hum Genet. 2018 Jul. 137(6-7):521-533.
29. López Y, Kamola PJ, Sharma R, Shigemizu D, Tsunoda T, and Sharma A. Computational pipelines and workflows in Bioinformatics. Encyclopedia of Bioinformatics and Computational Biology. 2018 Sep 1, 20089;1-24.
28. Nishino J, Kochi Y, Shigemizu D, Kato M, Ikari K, Ochi H, Noma H, Matsui K, Morizono T, Boroevich KA, Tsunoda T, and Matsui S. Empirical Bayes estimation of semi-parametric hierarchical mixture models for unbiasedcharacterization of polygenic disease architectures. Front Genet. 2018 Apr 24, 9:115.
27. Shigemizu D*, Miya F, Akiyama S, Okuda S, Boroevich KA, Fujimoto A, Nakagawa H, Ozaki K, Niida S, Kanemura Y, Okamoto N, Saitoh S, Kato M, Yamasaki M, Matsunaga T, Mutai H, Kosaki K, and Tsunoda T. IMSindel: An accurate intermediate-size indel detection tool incorporating de novo assembly and gapped global-local alignment with split read analysis. Sci Rep. 2018 Apr 4;8(1):5608. (プレスリリース)
2017
26. Shigemizu D, Iwase T, Yoshimoto M, Suzuki Y, Miya F, Boroevich KA, Katagiri T, Zembutsu H, and Tsunoda T. The prediction models for postoperative overall survival and disease-free survival in patients with breast cancer. Cancer Med. 2017 Jul;6(7):1627-1638.
25. Sharma A, Boroevich KA, Shigemizu D, Kamatani Y, Kubo M, and Tsunoda T. Hierarchical Maximum Likelihood Clustering Approach. IEEE Trans Biomed Eng. 2017 Jan;64(1):112-122.
2016
24. Ichikawa M, Aiba T, Ohno S, Shigemizu D, Ozawa J, Sonoda K, Fukuyama M, Itoh H, Miyamoto Y, Kubo M, Tsunoda T, Makiyama T, Tanaka T, Shimizu W, and Horie M. Phenotypic Variability of ANK2 Mutations in Patients with Inherited Primary Arrhythmia Syndromes. Circ J. 2016 Nov 25;80(12):2435-2442.
23. Sharma A, Shigemizu D, Boroevich KA, Lopez Y, Kamatani Y, Kubo M, and Tsunoda T. Stepwise Iterative Maximum Likelihood Clustering Approach. BMC Bioinformatics. 2016 Aug 24;17(1):319.
22. Yagihara N, Watanabe H, Barnett P, Duboscq-Bidot L, Thomas AC, Yang P, Ohno S, Hasegawa K, Kuwano R, Chate S, Redon R, Schott JJ, Probst V, Koopmann TT, Bezzina CR, Wilde AAM, Nakano Y, Aiba T, Miyamoto Y, Kamakura S, Darbar D, Donahue BS, Shigemizu D, Tanaka T, Tsunoda T, Suda M, Sato A, Minamino T, Endo N, Shimizu W, Horie M, Roden DM, and Makita N. Variants in the SCN5A promoter associated with various arrhythmia phenotypes. J Am Heart Assoc. 2016 Sep 13;5(9):e003644.
21. Morishita M, Muramatsu T, Suto Y, Hirai M, Konishi T, Shigemizu D, Tsunoda T, Moriyama K, and Inazawa J. Chromothripsis-like chromosomal rearrangements induced byionizing radiation using proton microbeam irradiation system. Oncotarget. 2016 Mar 1;7(9):10182-92.
2015
20. Aiba T, Shigemizu D, Nakagawa H, Ozaki K, Miya F, Satake W, Toda T, Miyamoto Y, Fujimoto A, Suzuki Y, Kubo M, Tsunoda T, Kusano K, Yasuda S, Ogawa H, Tanaka T, and Shimizu W. Calmodulin interacting genes as a novel candidate for pathogenesis of long-QT syndrome. Circulation. 2015 132(Suppl 3) A12257.
19. Shigemizu D, Momozawa Y, Abe T, Morizono T, Boroevich KA, Takata S, Ashikawa K, Kubo M, and Tsunoda T. Performance of comparison of four commercial human whole-exome capture platforms. Sci Rep. 2015 Aug 3;5:12742. (プレスリリース)
18. Shigemizu D, Aiba T, Nakagawa H, Ozaki K, Miya F, Satake W, Toda T, Miyamoto Y, Fujimoto A, Suzuki Y, Kubo M, Tsunoda T, Shimizu W, and Tanaka T. Exome analyses of long QT syndrome reveal candidate pathogenic mutations in calmodulin-interacting gene. PLoS One. 2015 10(7), e0130329. (プレスリリース)
17. Miya F, Kato M, Shiohama T, Okamoto N, Saitoh S, Yamasaki M, Shigemizu D, Abe T, Morizono T, Boroevich KA, Kosaki K, Kanemura Y, and Tsunoda T. A combination of targeted enrichment methodologies for whole-exome sequencing reveals novel pathogenic mutations. Sci Rep. 2015 Mar 19;5:9331.
16. Fujimoto A, Furuta M, Shiraishi Y, Gotoh K, Kawakami Y, Arihiko K, Nakamura T, Ueno M, Ariizumi S, Nguyen H, Shigemizu D, Abe T, Boroevich KA, Nakano K, Sasaki A, Kitada R, Maejima K, Yamamoto Y, Tanaka H, Shibuya T, Shibata T, Ojima H, Shimada K, Hayami S, Shigekawa Y, Aikata H, Ohdan H, Marubashi S, Yamada T, Kubo M, Hirano S, Ishikawa O, Yamamoto M, Yamaue H, Yamaue H, Chayama K, Miyano S, Tsunoda T, and Nakagawa H. Whole-genome mutational landscape of liver cancers displaying biliary phenotype reveals hepatitis impact and molecular diversity. Nat Commun. 2015 Jan 30;6:6120.
2014
15. Hirokawa M, Morita H, Tajima T, Takahashi A, Ashikawa K, Miya F, Shigemizu D, Ozaki K, Sakata Y, Nakatani D, Suna S, Imai Y, Tanaka T, Tsunoda T, Matsuda K, Kadowaki T, Nakamura Y, Nagai Y, Komuro I, and Kubo M. A genome-wide association study identifies PLCL2 and AP3D1-DOT1L-SF3A2 as new susceptibility loci for myocardial infarction in Japanese. Eur J Hum Genet. 2014 Mar;23(3):374-380.
14. Aiba T, Ishibashi K, Wada M, Nakajima I, Miyamoto K, Okamura H, Noda T, Shigemizu D, Satake W, Toda T, Kusano K, Kamakura S, Yasuda S, Sekine A, Miyamoto Y, Tanaka T, Ogawa S, and Shimizu W. Clinical Significance of Whole Exome Analysis Using Next Generation Sequencing in the Genotype-negative Long-QT Syndrome. Circulation. 2014 130(Suppl 2) A13817.
13. Makita N, Yagihara N, Crotti L, Johnson CN, Beckmann BM, Roh MS, Shigemizu D, Lichtner P, Ishikawa T, Aiba T, Homfray T, Behr ER, Klug D, Denjoy I, Mastantuono E, Theisen D, Tsunoda T, Satake W, Toda T, Nakagawa H, Tsuji Y, Tsuchiya T, Yamamoto H, Miyamoto Y, Endo N, Kimura A, Ozaki K, Motomura H, Suda K, Tanaka T, Schwartz PJ, Meitinger T, Kääb S, Guicheney P, Shimizu W, Bhuiyan ZA, Watanabe H, Chazin WJ, and George AL. Novel Calmodulin (CALM2) Mutations Associated with Congenital Arrhythmia Susceptibility. Circ Cardiovasc Genet. 2014 Aug;7(4):466-474.
12. Shigemizu D, Abe T, Morizono T, Johnson TA, Boroevich KA, Hirakawa Y, Ninomiya T, Kiyohara Y, Kubo M, Nakamura Y, Maeda S, and Tsunoda T. The Construction of Risk Prediction Models Using GWAS Data and Its Application to a Type 2 Diabetes Prospective Cohort. PLoS One. 2014 9(3), e92549.
2013
11. Makita N, Yagihara N, Crotti L, Johnson CN, Beckermann BM, Shigemizu D, Watanabe H, Ishikawa T, Aiba T, Mastantuono E, Tsunoda T, Nakagawa H, Tsuji Y, Tsuchiya T, Yamamoto H, Miyamoto Y, Endo N, Kimura A, Ozaki K, Motomura H, Suda K, Tanaka T, Schwartz PJ, Meitinge T, Kaeaeb S, Shimizu W, Chazin W, and George AL. CALM2 Mutations Associated With Atypical Juvenile Long QT Syndrome. Circulation. 2013 128(22) A13371.
10. Imamura M, Shigemizu D, Tsunoda T, Iwata M, Maegawa H, Watada H, Hirose H, Tanaka Y, Tobe K, Kaku K, Kashiwagi A, Kawamori R, and Maeda S. Assessing the Clinical Utility of a Genetic Risk Score Constructed Using 49 Susceptibility Alleles for Type 2 Diabetes in a Japanese Population. J Clin Endocrinol Metab. 2013 98(10), E1667-E1673.
9. Shigemizu D, Fujimoto A, Akiyama S, Abe T, Nakano K, Boroevich KA, Yamamoto Y, Furuta M, Kubo M, Nakagawa H, and Tsunoda T. A practical method to detect SNVs and indels from whole genome and exome sequencing data. Sci Rep. 2013 3:2161. (natureasia.com注目の論文)
2012
8. Nguyen HH, Takata R, Akamatsu S, Shigemizu D, Tsunoda T, Furihata M, Takahashi A, Kubo M, Kamatani N, Ogawa O, Fujioka T, Nakamura Y, and Nakagawa H. IRX4 at 5p15 suppresses prostate cancer growth through the interaction with vitamin D receptor, conferring prostate cancer susceptibility. Hum Mol Genet. 2012 21(9), 2076-2085.
7. Yoshihara K, Tsunoda T, Shigemizu D, Fujiwara H, Hatae M, Fujiwara H, Masuzaki H, Katabuchi H, Kawakami Y, Okamoto A, Nogawa T, Matsumura N, Udagawa Y, Saito T, Itamochi H, Takano M, Miyagi E, Sudo T, Ushijima K, Iwase H, Seki H, Terao Y, Enomoto T, Mikami M, Akazawa K, Tsuda H, Moriya T, Tajima T, Inoue I, and Tanaka K. High-risk ovarian cancer based on 126-gene expression signature is uniquely characterized by downregulation of antigen presentation pathway. Clin Cancer Res. 2012 18(5), 1374-1385.
6. Shigemizu D, Hu Z, Hung JH, Huang CL, Wang Y, and DeLisi C. Using functional signatures to identify repositioned drugs for breast, myelogenous leukemia and prostate cancer. PLoS Comput Biol. 2012 8(2), e1002347.
2011
5. Takarabe M, Shigemizu D, Kotera M, Goto S, and Kanehisa M. Network-based analysis and characterization of adverse drug–drug interactions. J Chem Inf Model. 2011 51(11), 2977-2985.
2010
4. Moriya Y, Shigemizu D, Hattori M, Tokimatsu T, Kotera M, Goto G, and Kanehisa M. PathPred: an enzyme-catalyzed metabolic pathway prediction server. Nucleic Acids Res. 2010 38(suppl 2), W138-W143.
3. Takarabe M, Shigemizu D, Kotera M, Goto S, and Kanehisa M. Characterization and classification of adverse drug interactions. Genome Inform. 2010 22, 167-175.
2009
2. Shigemizu D, Araki M, Okuda S, Goto S, and Kanehisa M. Extraction and analysis of chemical modification patterns in drug development. J Chem Inf Model. 2009 49(4), 1122-1129.
2004
1. Shigemizu D, and Maruyama O. Searching for regulatory elements of alternative splicing events using phylogenetic footprinting. Algorithms in Bioinformatics Lecture Notes in Computer Science. 2004 Vol. 3240,147-158.