Kornej, J., Börschel, C. S., Benjamin, E. J. & Schnabel, R. B. Epidemiology of atrial fibrillation in the 21st century: novel methods and new insights. Circ. Res. 127, 4–20 (2020).
Michaud, G. F. & Stevenson, W. G. Atrial fibrillation. N. Engl. J. Med. 384, 353–361 (2021).
Dobrev, D., Heijman, J., Hiram, R., Li, N. & Nattel, S. Inflammatory signalling in atrial cardiomyocytes: a novel unifying principle in atrial fibrillation pathophysiology. Nat. Rev. Cardiol. 20, 145–167 (2023).
Hulsmans, M. et al. Recruited macrophages elicit atrial fibrillation. Science 381, 231–239 (2023).
Lund, S. A., Giachelli, C. M. & Scatena, M. The role of osteopontin in inflammatory processes. J. Cell. Commun. Signal. 3, 311–322 (2009).
Harada, M. & Nattel, S. Implications of inflammation and fibrosis in atrial fibrillation pathophysiology. Card. Electrophysiol. Clin. 13, 25–35 (2021).
Ahn, I., Kang, C. S. & Han, J. Where should siRNAs go: applicable organs for siRNA drugs. Exp. Mol. Med. 55, 1283–1292 (2023).
Kulkarni, J. A. et al. The current landscape of nucleic acid therapeutics. Nat. Nanotechnol. 16, 630–643 (2021).
Dong, Y., Siegwart, D. J. & Anderson, D. G. Strategies, design, and chemistry in siRNA delivery systems. Adv. Drug. Deliv. Rev. 144, 133–147 (2019).
Dugal-Tessier, J., Thirumalairajan, S. & Jain, N. Antibody-oligonucleotide conjugates: a twist to antibody-drug conjugates. J. Clin. Med. 10, 838 (2021).
Cuellar, T. L. et al. Systematic evaluation of antibody-mediated siRNA delivery using an industrial platform of THIOMAB-siRNA conjugates. Nucleic Acids Res. 43, 1189–1203 (2015).
Malecova, B. et al. Targeted tissue delivery of RNA therapeutics using antibody-oligonucleotide conjugates (AOCs). Nucleic Acids Res. 51, 5901–5910 (2023).
Deczkowska, A., Weiner, A. & Amit, I. The physiology, pathology, and potential therapeutic applications of the TREM2 signaling pathway. Cell 181, 1207–1217 (2020).
Wang, S. et al. Anti-human TREM2 induces microglia proliferation and reduces pathology in an Alzheimer’s disease model. J. Exp. Med. 217, e20200785 (2020).
Epelman, S., Lavine, K. J. & Randolph, G. J. Origin and functions of tissue macrophages. Immunity 41, 21–35 (2014).
Le Grand, B. L., Hatem, S., Deroubaix, E., Couétil, J. P. & Coraboeuf, E. Depressed transient outward and calcium currents in dilated human atria. Cardiovasc. Res. 28, 548–556 (1994).
Iwasaki, Y.-k., Nishida, K., Kato, T. & Nattel, S. Atrial fibrillation pathophysiology: implications for management. Circulation 124, 2264–2274 (2011).
Ramachandran, P. et al. Resolving the fibrotic niche of human liver cirrhosis at single-cell level. Nature 575, 512–518 (2019).
Kanemaru, K. et al. Spatially resolved multiomics of human cardiac niches. Nature 619, 801–810 (2023).
Leuschner, F. et al. Therapeutic siRNA silencing in inflammatory monocytes in mice. Nat. Biotechnol. 29, 1005–1010 (2011).
Huang, X. et al. Synthesis of siRNA nanoparticles to silence plaque-destabilizing gene in atherosclerotic lesional macrophages. Nat. Protoc. 17, 748–780 (2022).
Remmerie, A. et al. Osteopontin expression identifies a subset of recruited macrophages distinct from Kupffer cells in the fatty liver. Immunity 53, 641–657.e14 (2020).
Morse, C. et al. Proliferating SPP1/MERTK-expressing macrophages in idiopathic pulmonary fibrosis. Eur. Respir. J. 54, 1802441 (2019).
Gao, X. et al. Osteopontin links myeloid activation and disease progression in systemic sclerosis. Cell Rep. Med. 1, 100140 (2020).
Steinbrenner, I. et al. Association of osteopontin with kidney function and kidney failure in chronic kidney disease patients: the GCKD study. Nephrol. Dial. Transplant. 38, 1430–1438 (2023).
Merino, J. L. et al. Practical compendium of antiarrhythmic drugs: a clinical consensus statement of the European Heart Rhythm Association of the European Society of Cardiology. Europace 27, euaf076 (2025).
Deftereos, S. et al. Colchicine for prevention of early atrial fibrillation recurrence after pulmonary vein isolation: a randomized controlled study. J. Am. Coll. Cardiol. 60, 1790–1796 (2012).
Deftereos, S. et al. Colchicine for prevention of atrial fibrillation recurrence after pulmonary vein isolation: mid-term efficacy and effect on quality of life. Heart Rhythm. 11, 620–628 (2014).
Krisai, P. et al. Canakinumab after electrical cardioversion in patients with persistent atrial fibrillation: a pilot randomized trial. Circ. Arrhythm. Electrophysiol. 13, e008197 (2020).
Ridker, P. M. et al. Antiinflammatory therapy with canakinumab for atherosclerotic disease. N. Engl. J. Med. 377, 1119–1131 (2017).
Deftereos, S. G. et al. Colchicine in cardiovascular disease: in-depth review. Circulation 145, 61–78 (2022).
Ahmed, A. S. et al. Prophylactic colchicine after radiofrequency ablation of atrial fibrillation: the PAPERS study. JACC Clin. Electrophysiol. 9, 1060–1066 (2023).
Rurik, J. G., Aghajanian, H. & Epstein, J. A. Immune cells and immunotherapy for cardiac injury and repair. Circ. Res. 128, 1766–1779 (2021).
Momin, N. Balancing safety and efficacy: tuning the biodistribution and pharmacokinetics of cytokine immunotherapies. Curr. Opin. Biotechnol. 84, 102994 (2023).
Hiram, R. et al. An inflammation resolution-promoting intervention prevents atrial fibrillation due to left-ventricular dysfunction. Cardiovasc. Res. 120, 345–359 (2023).
Liu, S. et al. Translational two-pore PBPK model to characterize whole-body disposition of different-size endogenous and exogenous proteins. J. Pharmacokinet. Pharmacodyn. 51, 449–476 (2024).
Harkos, C. et al. Using mathematical modelling and AI to improve delivery and efficacy of therapies in cancer. Nat. Rev. Cancer 25, 324–340 (2025).
Ayyar, V. S. & Song, D. Mechanistic pharmacokinetics and pharmacodynamics of GalNAc-siRNA: translational model involving competitive receptor-mediated disposition and RISC-dependent gene silencing applied to givosiran. J. Pharm. Sci. 113, 176–190 (2024).
Ray, K. K. et al. Effect of inclisiran on lipids in primary prevention: the ORION-11 trial. Eur. Heart J. 43, 5047–5057 (2022).
Collins, A. R. et al. Osteopontin modulates angiotensin II-induced fibrosis in the intact murine heart. J. Am. Coll. Cardiol. 43, 1698–1705 (2004).
Yamazoe, M. et al. B cells promote atrial fibrillation via autoantibodies. Nat. Cardiovasc. Res. 4, 1381–1396 (2025).
Fischer, C. et al. Long-term functional and structural preservation of precision-cut human myocardium under continuous electromechanical stimulation in vitro. Nat. Commun. 10, 117 (2019).
Egli, M. & Manoharan, M. Re-engineering RNA molecules into therapeutic agents. Acc. Chem. Res. 52, 1036–1047 (2019).
Parmar, R. et al. 5’-(E)-Vinylphosphonate: a stable phosphate mimic can improve the RNAi activity of siRNA-GalNAc conjugates. ChemBioChem 17, 985–989 (2016).
Äärelä, A., Räsänen, K., Holm, P., Salo, H. & Virta, P. Synthesis of site-specific antibody-[60]fullerene-oligonucleotide conjugates for cellular targeting. ACS Appl. Bio. Mater. 6, 3189–3198 (2023).
Patro, R., Duggal, G., Love, M. I., Irizarry, R. A. & Kingsford, C. Salmon provides fast and bias-aware quantification of transcript expression. Nat. Methods 14, 417–419 (2017).
Soneson, C., Love, M. I. & Robinson, M. D. Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences. F1000Res 4, 1521 (2015).
Fleming, S. J. et al. Unsupervised removal of systematic background noise from droplet-based single-cell experiments using CellBender. Nat. Methods 20, 1323–1335 (2023).
Germain, P. L., Lun, A., Garcia Meixide, C., Macnair, W. & Robinson, M. D. Doublet identification in single-cell sequencing data using scDblFinder. F1000Res 10, 979 (2021).
Butler, A., Hoffman, P., Smibert, P., Papalexi, E. & Satija, R. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat. Biotechnol. 36, 411–420 (2018).
Stuart, T. et al. Comprehensive integration of single-cell data. Cell 177, 1888–1902.e21 (2019).
Hao, Y. et al. Dictionary learning for integrative, multimodal and scalable single-cell analysis. Nat. Biotechnol. 42, 293–304 (2024).
Hafemeister, C. & Satija, R. Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression. Genome Biol. 20, 296 (2019).
Choudhary, S. & Satija, R. Comparison and evaluation of statistical error models for scRNA-seq. Genome Biol. 23, 27 (2022).
Chen, Y., Chen, L., Lun, A. T. L., Baldoni, P. L. & Smyth, G. K. edgeR v4: powerful differential analysis of sequencing data with expanded functionality and improved support for small counts and larger datasets. Nucleic Acids Res. 53, gkaf018 (2025).
Lun, A. T. L. & Marioni, J. C. Overcoming confounding plate effects in differential expression analyses of single-cell RNA-seq data. Biostatistics 18, 451–464 (2017).
Mootha, V. K. et al. PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat. Genet. 34, 267–273 (2003).
Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005).
Liberzon, A. et al. The Molecular Signatures Database (MSigDB) hallmark gene set collection. Cell Syst. 1, 417–425 (2015).
Castanza, A. S. et al. Extending support for mouse data in the Molecular Signatures Database (MSigDB). Nat. Methods 20, 1619–1620 (2023).
Jin, S., Plikus, M. V. & Nie, Q. CellChat for systematic analysis of cell-cell communication from single-cell transcriptomics. Nat. Protoc. 20, 180–219 (2025).
Frangogiannis, N. G. Cardiac fibrosis. Cardiovasc. Res. 117, 1450–1488 (2021).

















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