{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T09:17:05Z","timestamp":1788254225872,"version":"build-2803163510"},"reference-count":132,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cells"],"abstract":"<jats:p>Heart failure with preserved ejection fraction (HFpEF) is a substantial global health burden and the greatest unmet medical need for cardiovascular diseases. It is marked by pronounced clinical heterogeneity and complex multi-system pathophysiology with limited therapeutic options. Progress in developing effective therapeutics is constrained by the inadequacy of experimental models to fully recapitulate the multifactorial nature of the disease. Recent evidence underscores the significant involvement of inflammatory, oxidative, and mitochondrial pathways in the pathogenesis of HFpEF, with non-coding RNAs and epigenetic regulation serving as crucial modulators and prospective therapeutic targets. This review maps the HFpEF target landscape, while critically assessing the mechanistic contributions, translational fidelity, and limitations of existing in vivo and in vitro models. Further, advances are noted among the in vitro technologies, including human cardiac organoids and engineered heart tissues integrated with high-throughput multi-omics and computational modeling, enabling in-depth examination of HFpEF mechanisms. Finally, we underscore the necessity of integrative, systems-level approaches and multi-marker strategies to enhance translational relevance, improve risk stratification, and accelerate development of mechanism-based therapies. Collectively, this review supports phenotypic-guided and mechanism-informed therapeutic development for HFpEF, and provides a roadmap for next generation model development and therapeutic innovation.<\/jats:p>","DOI":"10.3390\/cells15171588","type":"journal-article","created":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T08:31:13Z","timestamp":1788251473000},"page":"1588","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Molecular Pathways, Target Landscape, and Translational Models in Heart Failure with Preserved Ejection Fraction"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1599-4020","authenticated-orcid":false,"given":"Haleema","family":"Qamar","sequence":"first","affiliation":[{"name":"Data AI and Genome Sciences (DAGS), Merck & Co., Inc., Cambridge, MA 02141, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Janmeet S.","family":"Saini","sequence":"additional","affiliation":[{"name":"Data AI and Genome Sciences (DAGS), Merck & Co., Inc., Cambridge, MA 02141, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sylwia Marta","family":"Figarska","sequence":"additional","affiliation":[{"name":"Data AI and Genome Sciences (DAGS), Merck & Co., Inc., Cambridge, MA 02141, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emmanuel S.","family":"Buys","sequence":"additional","affiliation":[{"name":"Cardiometabolic Disease (CMD), Merck & Co., Inc., South San Francisco, CA 94080, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vilas","family":"Wagh","sequence":"additional","affiliation":[{"name":"Data AI and Genome Sciences (DAGS), Merck & Co., Inc., Cambridge, MA 02141, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Stoicescu, L., Cri\u015fan, D., Morgovan, C., Avram, L., and Ghibu, S. 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