Asakura, Takanori

写真a

Affiliation

School of Medicine ( Shinanomachi )

Position

Assistant Professor (Non-tenured)/Research Associate (Non-tenured)/Instructor (Non-tenured)

Career 【 Display / hide 】

  • 2010.04
    -
    2012.03

    総合病院国保旭中央病院, 初期臨床研修医

  • 2012.04
    -
    2013.03

    Keio University, School of Medicine, Department of Internal Medicine

  • 2013.04
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    2014.03

    国立病院機構東京医療センター, 内科レジデント

  • 2014.04
    -
    2018.03

    Division of Pulmonary Medicine, Department of Medicine Keio University School of Medicine

  • 2016.04
    -
    2018.03

    日本学術振興会, 特別研究員(DC2)

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Academic Background 【 Display / hide 】

  • 2004.04
    -
    2010.03

    Keio University, School of Medicine

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Research Areas 【 Display / hide 】

  • Life Science / Respiratory medicine

  • Life Science / Infectious disease medicine

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Research Keywords 【 Display / hide 】

  • 呼吸器感染症

  • 気管支拡張症

  • 非結核性抗酸菌症

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Books 【 Display / hide 】

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Papers 【 Display / hide 】

  • Direct reprogramming of mouse fibroblasts into self-renewable alveolar epithelial-like cells.

    Atsuho Morita, Makoto Ishii, Takanori Asakura, Masaya Yotsukura, Ahmed E Hegab, Tatsuya Kusumoto, Ho Namkoong, Takunori Ogawa, Yuhki Nakatake, Mayumi Oda, Fumitake Saito, Hirofumi Kamata, Junko Hamamoto, Satoshi Okamori, Toshiki Ebisudani, Hiroyuki Yasuda, Shinya Sugimoto, Yuta Kuze, Masahide Seki, Yutaka Suzuki, Naoki Hasegawa, Hisao Asamura, Hideo Watanabe, Minoru Ko, Toshiro Sato, Masaki Ieda, Koichi Fukunaga

    NPJ Regenerative medicine 10 ( 1 ) 30 - 30 2025.12

    　View Summary

    Direct reprogramming is a breakthrough technology that can alter the fate of cells without the passage of stem cells. However, direct reprogramming of somatic cells into pulmonary alveolar epithelial cells has not yet been achieved. Here, we report the direct reprogramming of mouse tail tips and embryonic fibroblasts into induced pulmonary alveolar epithelial-like cells (iPULs) using four transcription factor-coding genes (Nkx2-1, Foxa1, Foxa2, and Gata6) and three-dimensional culture. The iPULs showed lamellar body-like structures and displayed key properties of pulmonary alveolar epithelial cells. Although the potential for iPULs to morphologically differentiate into alveolar epithelial type 1 cells was limited in vitro, the intratracheal administration of iPULs in a bleomycin-induced mouse model of pulmonary fibrosis led to their integration into the alveolar surface, where they formed both alveolar epithelial type 1 and type 2-like cells. Thus, reprogrammed fibroblasts may represent a new source of pulmonary alveolar epithelial cells for regenerative medicine.

  • Predicting coronavirus disease 2019 severity using explainable artificial intelligence techniques

    Takuya Ozawa, Shotaro Chubachi, Ho Namkoong, Shota Nemoto, Ryo Ikegami, Takanori Asakura, Hiromu Tanaka, Ho Lee, Takahiro Fukushima, Shuhei Azekawa, Shiro Otake, Kensuke Nakagawara, Mayuko Watase, Katsunori Masaki, Hirofumi Kamata, Norihiro Harada, Tetsuya Ueda, Soichiro Ueda, Takashi Ishiguro, Ken Arimura, Fukuki Saito, Takashi Yoshiyama, Yasushi Nakano, Yoshikazu Muto, Yusuke Suzuki, Ryuya Edahiro, Koji Murakami, Yasunori Sato, Yukinori Okada, Ryuji Koike, Makoto Ishii, Naoki Hasegawa, Yuko Kitagawa, Katsushi Tokunaga, Akinori Kimura, Satoru Miyano, Seishi Ogawa, Takanori Kanai, Koichi Fukunaga, Seiya Imoto

    Scientific Reports (Springer Science and Business Media LLC)  15 ( 1 ) 9459 - 9459 2025.12

    　View Summary

    Predictive models for determining coronavirus disease 2019 (COVID-19) severity have been established; however, the complexity of the interactions among factors limits the use of conventional statistical methods. This study aimed to establish a simple and accurate predictive model for COVID-19 severity using an explainable machine learning approach. A total of 3,301 patients ≥ 18 years diagnosed with COVID-19 between February 2020 and October 2022 were included. The discovery cohort comprised patients whose disease onset fell before October 1, 2020 (N = 1,023), and the validation cohort comprised the remaining patients (N = 2,278). Pointwise linear and logistic regression models were used to extract 41 features. Reinforcement learning was used to generate a simple model with high predictive accuracy. The primary evaluation was the area under the receiver operating characteristic curve (AUC). The predictive model achieved an AUC of ≥ 0.905 using four features: serum albumin levels, lactate dehydrogenase levels, age, and neutrophil count. The highest AUC value was 0.906 (sensitivity, 0.842; specificity, 0.811) in the discovery cohort and 0.861 (sensitivity, 0.804; specificity, 0.675) in the validation cohort. Simple and well-structured predictive models were established, which may aid in patient management and the selection of therapeutic interventions.

  • Impact of long COVID on the health-related quality of life of Japanese patients: A prospective nationwide cohort study.

    Kazuma Yagi, Masahiro Kondo, Hideki Terai, Takanori Asakura, Ryusei Kimura, Ryo Takemura, Hiromu Tanaka, Keiko Ohgino, Katsunori Masaki, Ho Namkoong, Shotaro Chubachi, Jun Miyata, Ichiro Kawada, Tatsuya Kaido, Shuko Mashimo, Keigo Kobayashi, Toshiyuki Hirano, Ho Lee, Kai Sugihara, Nao Omori, Mayuko Watase, Takao Mochimaru, Ryosuke Satomi, Yasushi Makino, Takashi Inoue, Koichi Sayama, Yoshitaka Oyamada, Makoto Ishii, Yasunori Sato, Koichi Fukunaga

    Respiratory investigation 63 ( 4 ) 610 - 616 2025.07

    ISSN  22125345

    　View Summary

    BACKGROUND: Various prolonged systemic symptoms, forming the long coronavirus disease (COVID), have been observed in patients who have recovered from the acute phase of COVID-19. Although previous studies have reported that COVID-19 impacts health-related quality of life (HRQoL), the associations of long COVID symptoms and clinical characteristics with HRQoL remain unclear. This study aimed to clarify these associations using nationwide Japanese epidemiological data. METHODS: A prospective nationwide cohort study was conducted on patients with COVID-19 between January 2020 and February 2021 at 26 participating medical institutions in Japan. Various long COVID symptoms and HRQoL scores at 3, 6, and 12 months following diagnosis were collected from 986 participants. Generalized estimating equations (GEE) were used to explore the association between HRQoL scores evaluated using the short form-8 (SF-8), long COVID symptoms, and baseline clinical characteristics. RESULTS: Patients who had one long COVID symptom showed a significantly lower physical component summary score (PCS) and mental component summary score (MCS) compared with those without any symptoms at all time points after diagnosis. GEE revealed that long COVID symptoms, including dyspnea, fatigue, headache, and muscle weakness, were significantly associated with worse PCS, whereas poor concentration, sleep disorders, fatigue, and headache were significantly associated with worse MCS. Severity-related baseline parameters for patients with COVID-19 were significantly associated with worse PCS scores, although these factors were not significantly associated with worse MCS scores. CONCLUSIONS: Long COVID symptoms were associated with lower physical and mental HRQoL. Severe outcomes of COVID-19 impacted PCS but not MCS.

  • Sectm1a Depletion Promotes Neutrophil Recruitment during Pneumococcal Pneumonia

    Hiromu Tanaka, Hirofumi Kamata, Makoto Ishii, Takanori Asakura, Ho Namkoong, Kensuke Nakagawara, Atsuho Morita, Tatsuya Kusumoto, Shuhei Azekawa, Masanori Kaji, Genta Nagao, Naoki Fukunaga, Tomoyasu Nishimura, Keisuke Asakura, Naoki Hasegawa, Koichi Fukunaga

    American Journal of Respiratory Cell and Molecular Biology 73 ( 1 ) 60 - 72 2025.07

    ISSN  10441549

    　View Summary

    Airway epithelial cells (AECs) play an essential role in the immune response during bacterial pneumonia. Secreted and transmembrane 1a (Sectm1a) is specifically expressed in AECs during early Streptococcus pneumoniae (SP) infection. However, its function remains largely unexplored. Here, we aimed to clarify the function of Sectm1a during serotype 3 pneumococcal pneumonia primarily using an in vivo mouse model. Our findings showed that type Ⅰ interferons (IFNs) directly induced Sectm1a expression in AECs. Sectm1a depletion in an in vivo mouse model improved survival rate and enhanced the clearance of intrapulmonary bacterial burden at an early stage of SP infection. Correspondingly, Sectm1a depletion increased the count of intrapulmonary γδT cells, promoted IL-17A production by these cells, and enhanced intrapulmonary neutrophil responses against SP. Notably, IL-17A production in the isolated lung γδT cells was directly suppressed by Sectm1a ex vivo. Furthermore, Sectm1a depletion altered the migration and activation markers of γδT cells in vivo, indicating that the AEC-derived Sectm1a is associated with the phenotypes of γδT cells. These findings suggest that type Ⅰ IFNs may play an important role via AEC-derived Sectm1a in this model, and Sectm1a signaling modulates excessive neutrophil inflammation and influences bacterial clearance by directly altering γδT cell functions during pneumococcal pneumonia. In summary, this study demonstrates that the type Ⅰ IFN-Sectm1a pathway could be a potential target to modify the acute response to bacterial pneumonia.

  • STAT3-dependent Regulation of CFTR and Ciliogenesis Is Essential for Mucociliary Clearance and Innate Airway Defense in Hyper-IgE Syndrome.

    Ling Sun, Samantha A Walls, Hong Dang, Nancy L Quinney, Patrick R Sears, Taraneh Sadritabrizi, Koichi Hasegawa, Kenichi Okuda, Takanori Asakura, Xiuya Chang, Meiqi Zheng, Yu Mikami, Felicia U Dizmond, Daniela Danilova, Lynn Zhou, Anshulika Deshmukh, Deborah M Cholon, Giorgia Radicioni, Troy D Rogers, William J Kissner, Matthew R Markovetz, Tara N Guhr Lee, Mark I Gutay, Charles R Esther Jr, Michael Chua, Barbara R Grubb, Camille Ehre, Mehmet Kesimer, David B Hill, Lawrence E Ostrowski, Brian Button, Martina Gentzsch, Chevalia Robinson, Kenneth N Olivier, Alexandra F Freeman, Scott H Randell, Eszter Vladar, Wanda K O'Neal, Richard C Boucher Jr, Gang Chen

    American journal of respiratory and critical care medicine  2025.05

    　View Summary

    RATIONALE: Hyper IgE syndrome (STAT3-HIES), also known as Job's syndrome, is a rare immunodeficiency disease typically caused by dominant-negative STAT3 mutations. STAT3-HIES is characterized by chronic pulmonary infection and inflammation, suggesting impaired innate host defense. OBJECTIVES: To identify airway epithelial host defense defects caused by STAT3 mutations that, together with immune dysfunction, contribute to recurrent pulmonary infections in STAT3-HIES. METHODS: STAT3-HIES sputum was analyzed for biochemical and biophysical properties. STAT3-HIES excised lungs were harvested for histology; and bronchial brush samples were collected for RNA sequencing and in vitro culture. A STAT3-HIES-specific R382W mutation, expressed via lentivirus, and STAT3 knockout (CRISPR/Cas9), were studied in normal human bronchial epithelial cells under basal or inflammatory (IL1β)-stimulated conditions. Effects of STAT3 deficiency on transcriptomics, epithelial ion channel, secretory, antimicrobial, and ciliary functions were assessed. MEASUREMENTS AND MAIN RESULTS: STAT3-HIES sputum showed increased mucus concentration and viscoelasticity. STAT3-HIES excised lungs exhibited mucus obstruction and elevated IL1β expression. STAT3 mutations reduced CFTR mRNA and protein levels, impaired CFTR-dependent fluid and mucin secretion, suppressed antimicrobial peptide, cytokine, and chemokine expression, and acidified airway surface liquid at baseline and post-IL1β exposure. Notably, mutant STAT3 suppressed IL1R1 expression. Furthermore, STAT3 mutations impaired multiciliogenesis by blocking commitment to ciliated cell lineages through inhibition of HES6, leading to defective mucociliary transport. Administration of a γ-secretase inhibitor restored HES6 expression, improved ciliogenesis in STAT3 R382W mutant cells. CONCLUSIONS: STAT3 dysfunction leads to multi-component defects in airway epithelial innate defense, which, in conjunction with immune deficiency, contributes to chronic pulmonary infection in STAT3-HIES.

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Papers, etc., Registered in KOARA 【 Display / hide 】

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Reviews, Commentaries, etc. 【 Display / hide 】

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Research Projects of Competitive Funds, etc. 【 Display / hide 】

  • 大規模コホートを活用した肺非結核性抗酸菌症の発症機序解明と個別化医療の実現

    2025.07
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    2028.03

    令和7年度ゲノム医療実現バイオバンク利活用プログラム（ゲノム医療実現推進プラットフォーム・先端ゲノム研究開発）, Principal investigator

  • 肺非結核性抗酸菌症の末梢気道における粘液異常の解明と治療法開発

    2025.04
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    2028.03

    日本学術振興会, 科学研究費助成事業, 基盤研究(B), No Setting

  • 国際連携による気管支拡張症の解剖学的・分子生物学的特性の統合的理解

    2024.09
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    2028.03

    日本学術振興会, 科学研究費助成事業, 国際共同研究加速基金(海外連携研究), No Setting

  • Functional analysis of host disease susceptibility genes in patients with pulmonary non-tuberculous mycobacterial diseases to create a novel therapeutic strategy.

    2023.04
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    2026.03

    Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research, Grant-in-Aid for Scientific Research (B), No Setting

  • 新たな重症呼吸器症候群をきたす感染症に備えた気道部位特異的上皮細胞における分子基盤の創出

    2023.04
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    2024.03

    令和4年度 「新興・再興感染症に対する革新的医薬品等開発推進研究事業」, Principal investigator

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Awards 【 Display / hide 】

  • 北里柴三郎記念学術奨励賞

    2025.05, 日本感染症学会

  • 三四会奨励賞

    2024.06, 慶應義塾大学医学部三四会

  • Assembly on Pulmonary Infections & Tuberculosis Rising Star Award for Basic Scientific and/or Translational Research

    2024.05, American Thoracic Society

  • UJA特別賞

    朝倉 崇徳, 2024.04, 海外日本人研究者ネットワーク

  • 学会奨励賞

    朝倉 崇徳, 2024.04, 日本呼吸器学会

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Courses Taught 【 Display / hide 】

  • PHYSICAL ASSESSMENT AND DIAGNOSTIC IMAGING

    2025

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Courses Previously Taught 【 Display / hide 】

  • PHYSICAL ASSESSMENT AND DIAGNOSTIC IMAGING

    Keio University

    2025.04
    -
    2026.03

  • 薬学部OSCE評価者

    北里大学薬学部

    2024.12

  • 病態評価学

    北里大学薬学部

    2024.11
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    2024.12

  • フィジカルアセスメントと画像検査

    慶應義塾大学薬学部

    2024.07

  • フィジカルアセスメント実習

    北里大学薬学部

    2024.06
    -
    2024.07

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Social Activities 【 Display / hide 】

  • NPO法人非結核性抗酸菌症・気管支拡張症研究コンソーシアム事務局

    2025.04

  • 徹底解説！-最新版「成人肺非結核性抗酸菌症化学療法に関する見解

    日経メディカルOnline CMEデジタル

    2023.11
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    2023.12

  • 台東区保健所 結核診査会

    2018.04
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    2019.03
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Academic Activities 【 Display / hide 】

  • 第100回日本結核・非結核性抗酸菌症学会学術講演会 一般演題基礎研究1座長

    2025.06

  • 米国胸部疾患学会2025 Facilitator

    2025.05

  • 第186回日本結核・非結核性抗酸菌症学会/第261回日本呼吸器学会関東地方会セッションⅢ座長

    2024.09

  • 第99回日本結核・非結核性抗酸菌症学会学術講演会 一般演題19基礎研究1座長

    2024.06

  • NTM Host Research Consortium International Workshop Chairperson

    2022.01

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