Communications Biology (Dec 2024)
Left atrial single-cell transcriptomics reveals amphiregulin as a surrogate marker for atrial fibrillation
- Yuya Suzuki,
- Takuo Emoto,
- Shunsuke Sato,
- Takeshi Yoshida,
- Mitsuhiko Shoda,
- Hiromi Endoh,
- Manabu Nagao,
- Tomoyo Hamana,
- Taishi Inoue,
- Tomohiro Hayashi,
- Eriko Nitta,
- Hiroki Konishi,
- Kunihiko Kiuchi,
- Mitsuru Takami,
- Kimitake Imamura,
- Masayuki Taniguchi,
- Masatoshi Inoue,
- Toshihiro Nakamura,
- Yusuke Sonoda,
- Hiroyuki Takahara,
- Kazutaka Nakasone,
- Kyoko Yamamoto,
- Kenichi Tani,
- Hidehiro Iwai,
- Yusuke Nakanishi,
- Shogo Yonehara,
- Atsushi Murakami,
- Ryuji Toh,
- Takenao Ohkawa,
- Tomoyuki Furuyashiki,
- Ryo Nitta,
- Tomoya Yamashita,
- Ken-ichi Hirata,
- Koji Fukuzawa
Affiliations
- Yuya Suzuki
- Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine
- Takuo Emoto
- Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine
- Shunsuke Sato
- Division of Cardiovascular Surgery, Department of Surgery, Yodogawa Christian Hospital
- Takeshi Yoshida
- Department of Information and Intelligence Engineering, Kobe University
- Mitsuhiko Shoda
- Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine
- Hiromi Endoh
- Division of Structural Medicine and Anatomy, Department of Physiology and Cell Biology, Kobe University Graduate School of Medicine
- Manabu Nagao
- Division of Evidence-Based Laboratory Medicine, Kobe University Graduate School of Medicine
- Tomoyo Hamana
- Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine
- Taishi Inoue
- Division of Cardiovascular Surgery, Department of Surgery, Kobe University Graduate School of Medicine
- Tomohiro Hayashi
- Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine
- Eriko Nitta
- Division of Structural Medicine and Anatomy, Department of Physiology and Cell Biology, Kobe University Graduate School of Medicine
- Hiroki Konishi
- Division of Cardiovascular Medicine, Department of Internal Medicine, Yodogawa Christian Hospital
- Kunihiko Kiuchi
- Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine
- Mitsuru Takami
- Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine
- Kimitake Imamura
- Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine
- Masayuki Taniguchi
- Division of Pharmacology, Kobe University Graduate School of Medicine
- Masatoshi Inoue
- Department of Information and Intelligence Engineering, Kobe University
- Toshihiro Nakamura
- Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine
- Yusuke Sonoda
- Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine
- Hiroyuki Takahara
- Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine
- Kazutaka Nakasone
- Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine
- Kyoko Yamamoto
- Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine
- Kenichi Tani
- Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine
- Hidehiro Iwai
- Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine
- Yusuke Nakanishi
- Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine
- Shogo Yonehara
- Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine
- Atsushi Murakami
- Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine
- Ryuji Toh
- Division of Evidence-Based Laboratory Medicine, Kobe University Graduate School of Medicine
- Takenao Ohkawa
- Department of Information and Intelligence Engineering, Kobe University
- Tomoyuki Furuyashiki
- Division of Pharmacology, Kobe University Graduate School of Medicine
- Ryo Nitta
- Division of Structural Medicine and Anatomy, Department of Physiology and Cell Biology, Kobe University Graduate School of Medicine
- Tomoya Yamashita
- Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine
- Ken-ichi Hirata
- Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine
- Koji Fukuzawa
- Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine
- DOI
- https://doi.org/10.1038/s42003-024-07308-w
- Journal volume & issue
-
Vol. 7,
no. 1
pp. 1 – 13
Abstract
Abstract Atrial fibrillation (AF) is strongly associated with strokes, heart failure, and increased mortality. This study aims to identify the monocyte–macrophage heterogeneity and interactions of these cells with non-immune cells, and to identify functional biomarkers in patients with AF. Therefore, we assess the single cell landscape of left atria (LA), using a combination of single cell and nucleus RNA-seq. Myeloid cells in LA tissue are categorized into five macrophage clusters, three monocyte clusters, and others. Cell-Chat analysis revealed that monocytes and IL1B+ macrophages send epidermal growth factor (EGF) signals to fibroblasts. Amphiregulin (AREG) is the most upregulated gene in monocytes and IL1B+ macrophages in the AF group, compared with healthy controls from other groups. Serum AREG levels are higher in patients with persistent AF. These data suggested that EGF signaling pathway could be a therapeutic target for AF and serum AREG levels provide an effective biomarker for predicting persistent AF.
