Circulation: Genomic and Precision Medicine最新文献

{"title":"Machine Learning Reveals the Contribution of Rare Genetic Variants and Enhances Risk Prediction for Coronary Artery Disease in the Japanese Population.","authors":"Hirotaka Ieki, Sai Zhang, Satoshi Koyama, Martin Kjellberg, Hiroki Yoshida, Ryo Kurosawa, Hiroshi Matsunaga, Kazuo Miyazawa, Nobuyuki Enzan, Changhoon Kim, Jeong-Sun Seo, Koichiro Higasa, Kouichi Ozaki, Yoshihiro Onouchi, Koichi Matsuda, Yoichiro Kamatani, Chikashi Terao, Fumihiko Matsuda, Michael P Snyder, Issei Komuro, Kaoru Ito","doi":"10.1161/CIRCGEN.125.005341","DOIUrl":"10.1161/CIRCGEN.125.005341","url":null,"abstract":"<p><strong>Background: </strong>GWASs (genome-wide association studies) have advanced our understanding of coronary artery disease (CAD) genetics and enabled the development of polygenic risk scores (PRSs) for estimating genetic risk based on common variant burden. However, GWASs have limitations in analyzing rare variants due to insufficient statistical power, thereby constraining PRS performance.</p><p><strong>Methods: </strong>We conducted whole-genome sequencing of 1752 Japanese patients with CAD and 3019 controls. A machine learning-based analytical framework was applied to identify and interpret rare genetic variants associated with CAD pathogenesis.</p><p><strong>Results: </strong>This approach identified 59 CAD-related genes, including known causal genes such as <i>LDLR</i> and those not previously captured by GWASs. A rare variant-based risk score derived from the framework demonstrated distinct clinical characteristics compared with a conventional common variant-based PRS. The rare variant-based risk score significantly discriminated CAD cases and predicted cardiovascular mortality in an independent cohort. Furthermore, combining the rare variant-based risk score with the traditional PRS improved CAD prediction compared with the PRS alone (area under the curve, 0.66 versus 0.61; <i>P</i>=0.007).</p><p><strong>Conclusions: </strong>These findings underscore the distinct and complementary value of the rare variant-based risk score compared with the conventional PRS, highlighting the enhanced predictive power achieved through their integration. This comprehensive approach proposes broader genetic profiling, offering substantial potential for improved clinical risk stratification and personalized prevention strategies.</p>","PeriodicalId":10326,"journal":{"name":"Circulation: Genomic and Precision Medicine","volume":" ","pages":"e005341"},"PeriodicalIF":6.1,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13310176/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148155521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metabolic Task Analysis Reveals Distinct Metabotypes in End-Stage Dilated Cardiomyopathy.","authors":"Bastien S C Nihant, Job A J Verdonschot, Sonia Bălan, Eva Thielecke, Joost J F P Luiken, Miranda Nabben, Stephane Heymans, Marian Breuer, Michiel E Adriaens","doi":"10.1161/CIRCGEN.125.005366","DOIUrl":"10.1161/CIRCGEN.125.005366","url":null,"abstract":"<p><strong>Background: </strong>Dilated cardiomyopathy (DCM) is associated with shifts in cardiac metabolism. However, those shifts vary widely across patients, likely reflecting the diverse underlying causes of the disease. Identifying metabolic subtypes, or metabotypes, in DCM patients could help tailor treatments to patient needs. Hence, having a practical approach to identify these metabotypes would be a significant advance toward precision medicine in DCM.</p><p><strong>Methods: </strong>We present a systems biology approach to uncover metabotypes directly from widely available transcriptomic data. We use in silico metabolic modeling methods that we have optimized for cardiac research to predict metabolic function activities from enzyme expression, followed by a hierarchical clustering approach. To demonstrate its power, we applied our method to publicly available cardiac data from end-stage DCM patients (N=164) and nonfailing controls (N=160).</p><p><strong>Results: </strong>We identified 2 distinct metabotypes in end-stage DCM patients. These metabotypes are characterized by unique metabolic changes, notably in calcium handling, amino acid oxidation, and the pentose phosphate pathway. Strikingly, 1 DCM metabotype showed greater metabolic divergence from healthy controls, suggesting a greater metabolic contribution to its underlying etiology-even though disease severity was similar between the 2 identified DCM metabotypes. Further transcriptome-wide analysis revealed immune-related differences between metabotypes, suggesting an underlying interplay between inflammation, the immune response, and metabolism.</p><p><strong>Conclusions: </strong>Our results imply the presence of distinct metabotypes in end-stage DCM. Our systems biology approach offers an exciting opportunity to uncover novel insights into DCM, paving the way for a deeper understanding of its progression and heterogeneity.</p>","PeriodicalId":10326,"journal":{"name":"Circulation: Genomic and Precision Medicine","volume":" ","pages":"e005366"},"PeriodicalIF":6.1,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13489769/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148374767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rare <i>KDR</i> Variants Define a Distinct Genetic Contribution to Congenital Heart Disease.","authors":"Feria A Ladha, Paul Avillach, Alexander R Opotowsky, Aldweib Nael, Martina Brueckner, Wendy K Chung, James F Cnota, Bruce D Gelb, Matthew Lewis, Cong Liu, Amy E Roberts, Christine E Seidman, J G Seidman, Martin Tristani-Firouzi, Michael Wagner, Jane W Newburger, Yuri Kim, Sarah U Morton","doi":"10.1161/CIRCGEN.125.005659","DOIUrl":"10.1161/CIRCGEN.125.005659","url":null,"abstract":"","PeriodicalId":10326,"journal":{"name":"Circulation: Genomic and Precision Medicine","volume":" ","pages":"e005659"},"PeriodicalIF":6.1,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13143342/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147764019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cardiomyopathy-Associated Mutations in a Hotspot Region at the C-Terminal Part of Desmin Coil-2 Domain Impair the Intermediate Filament Assembly.","authors":"Jonas Reckmann, Hendrik Milting, Sabrina Voß, Marco T Radukic, Franziska Klag, Franziska Flottmann, Alexander Lütkemeyer, Joline Groß, Anna Gärtner, Sandra Landwehr, Dario Anselmetti, Annika Hoyer, Kristian M Müller, Jan Gummert, Volker Walhorn, Andreas Brodehl","doi":"10.1161/CIRCGEN.125.005653","DOIUrl":"10.1161/CIRCGEN.125.005653","url":null,"abstract":"<p><strong>Background: </strong>The <i>DES</i> gene encodes the IF (intermediate filament) protein desmin, which connects different multiprotein complexes, such as the cardiac desmosomes, and is highly important for the structural integrity of cardiomyocytes. Pathogenic <i>DES</i> mutations cause filament assembly defects leading to cardiomyopathies. However, most <i>DES</i> variants listed in genetic disease databases are currently classified as variants of unknown significance. Here, we characterized 21 different <i>DES</i> variants of unknown significance and 18 additional proline variants, localized in a highly conserved stretch at the C terminus of the desmin coil-2 subdomain.</p><p><strong>Methods: </strong>We inserted desmin variants via site-directed mutagenesis and investigated the filament assembly in transfected cell lines and cardiomyocytes derived from induced pluripotent stem cells by confocal microscopy. In addition, we purified recombinant wild-type and mutant desmin and analyzed the filament formation by atomic force microscopy. Coexpression with wild-type desmin delivered by adeno-associated virus was used to model the heterozygous status of cardiomyopathy patients.</p><p><strong>Results: </strong>Twelve <i>DES</i> variants of unknown significance formed cytoplasmic aggregates, which were likewise verified by atomic force microscopy. Of note, these 12 variants disturb the filament assembly even when coexpressed with wild-type desmin. Using a proline screen, we showed that proline residues localized at nearly each of the positions in this stretch cause filament assembly defects. By modeling the tetrameric structure of desmin, we demonstrated that specific heptad positions, as well as positions of intramolecular and intermolecular ion bridge sites, are particularly susceptible to mutations that promote desmin aggregation.</p><p><strong>Conclusions: </strong>In summary, our study demonstrated that the highly conserved stretch at the C terminus of the coil-2 subdomain is a hotspot region, where several pathogenic <i>DES</i> mutations cause an aberrant desmin aggregation. Based on our molecular data, we suggest reclassifying the aggregate-forming variants as likely pathogenic mutations rather than variants of unknown significance. Our study may have relevance for the genetic counseling of cardiomyopathy patients with similar <i>DES</i> variants.</p>","PeriodicalId":10326,"journal":{"name":"Circulation: Genomic and Precision Medicine","volume":" ","pages":"e005653"},"PeriodicalIF":6.1,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148359663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance of Polygenic Risk Scores for Atherosclerotic Cardiovascular Disease in the <i>All of Us</i> Program.","authors":"Johanna L Smith, Kristjan Norland, Marwan E Hamed, Yue Yu, Jie Na, Ozan Dikilitas, Daniel J Schaid, Iftikhar J Kullo","doi":"10.1161/CIRCGEN.125.005382","DOIUrl":"10.1161/CIRCGEN.125.005382","url":null,"abstract":"<p><strong>Background: </strong>Performance and transferability of contemporary polygenic risk scores (PRS) for atherosclerotic cardiovascular disease phenotypes may vary across PRS methods, training data, and trait ascertainment.</p><p><strong>Methods: </strong>We aimed to investigate the performance and transferability of contemporary PRS for atherosclerotic cardiovascular disease subtypes: coronary heart disease (CHD), abdominal aortic aneurysm (AAA), ischemic stroke (IS), and peripheral artery disease (PAD), using the <i>All of Us</i> Workbench, which consists of a large, diverse cohort with whole-genome sequence data. We also developed and evaluated a multi-trait PRS for each subtype. Performance of PRS for 4 atherosclerotic cardiovascular disease subtypes was compared across genetic similarity groups in 245 388 <i>All of Us</i> participants. Groups genetically similar to European, African, admixed American, and remaining groups (combined as other) were used to assess PRS for CHD, IS, AAA, PAD, and multi-trait.</p><p><strong>Results: </strong>PRS for CHD and AAA performed better than IS and PAD. For CHD, CHD_PGS003725 performed the best (hazard ratio per SD increase [95% CI]), across genetic ancestry groups, European, and African (1.72 [1.67-1.78], 1.23 [1.17-1.29]), with CHD_PGS004696 being best for admixed American (1.91 [1.70-2.15]), and CHD_PGS003356 for other (1.75 [1.58-1.95]). The best performing PRS for AAA was AAA_Multi for European, other, and admixed American (1.71 [1.52-1.92], 1.59 [1.07-2.37], 1.50 [0.90-2.52]) and AAA_PGS003972 for African (1.39 [1.19-1.63]). For IS, IS_Multi performed best for other and European (1.49 [1.17-1.89], 1.33 [1.25-1.42]), and IS_PGS000039 performed best in admixed American and African (1.17 [1.07-1.27], 1.09 [1.04-1.15]). For PAD, PAD_Multi performed best for all groups (other, 1.51 [1.19-1.92]; European, 1.32 [1.24-1.41]; admixed American, 1.23 [1.05-1.45]; and African, 1.18 [1.04-1.34]).</p><p><strong>Conclusions: </strong>Multi-trait and multi-ancestry PRS performed better than individual trait and/or single ancestry PRS for each atherosclerotic cardiovascular disease phenotype across ancestrally diverse and admixed individuals, with minimal change including adjustment for conventional risk factors.</p>","PeriodicalId":10326,"journal":{"name":"Circulation: Genomic and Precision Medicine","volume":" ","pages":"e005382"},"PeriodicalIF":6.1,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13288946/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148197566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial Intelligence and Machine Learning Approaches for Cardiovascular Genomics: A State-of-the-Art Review.","authors":"Federica De Paoli, Giovanna Nicora, Kristian Galanti, Corinthia S Gonzales, Francesca Mangili, Damian Smedley, Raja Appuswamy, Yuka Imamura Kawasawa, Virend K Somers, Ivan Limongelli, Mohamad AlKhayat, Bing Si, Fabrizio Ricci, Susanna Zucca, C Anwar A Chahal","doi":"10.1161/CIRCGEN.125.005447","DOIUrl":"https://doi.org/10.1161/CIRCGEN.125.005447","url":null,"abstract":"<p><p>The advent of high-throughput sequencing technologies has revolutionized cardiovascular genetics, generating vast amounts of data. A major challenge in the genomic era is the efficient and accurate identification of causative genetic variants associated with cardiovascular disease. Artificial intelligence (AI)-driven computational approaches offer a powerful solution by enabling the automation of variant classification, improving consistency and reproducibility, and enhancing predictive accuracy. These methods may guide not only variant classification, variant effect prediction, and clinical prioritization, but also open the door to data-driven precision medicine, enabling more accurate and individualized diagnoses and targeted therapeutic strategies tailored to each patient's unique genetic and clinical profile. This state-of-the-art review provides a structured overview of AI methodologies applied to cardiovascular genomics, beginning with rule-based expert systems that encode standardized guidelines for consistent variant interpretation. Next, we examine machine learning approaches capable of identifying complex patterns in annotated multimodal clinical and multi-omic datasets. The role of deep learning algorithms is highlighted for their ability to extract features from high-dimensional, unstructured data relevant to cardiovascular disease. In addition, the potential of generative AI is explored, including applications in synthetic data generation, variant impact prediction, and automated summarization of biomedical literature. Despite advances, several challenges remain, including data heterogeneity, the need for explainable AI models to elucidate the decision mechanisms, and the complexity linked to the integration of AI-based tools into clinical workflows. Addressing these issues requires interdisciplinary collaboration among clinicians, geneticists, data scientists, and bioinformaticians to ensure the effective translation of AI-generated insights into clinical practice. This review aims to provide a comprehensive perspective on the evolving role of AI in cardiovascular genomics and its implications for advancing precision medicine.</p>","PeriodicalId":10326,"journal":{"name":"Circulation: Genomic and Precision Medicine","volume":"19 4","pages":"e005447"},"PeriodicalIF":6.1,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148789019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long-Term Efficacy and Safety of GLP-1R Agonist and SGLT2 Inhibitor Therapy in the General Population: A Mendelian Randomization Study.","authors":"Subbaramireddy Remala, Liming Liang, Amil M Shah, Leo F Buckley","doi":"10.1161/CIRCGEN.125.005535","DOIUrl":"10.1161/CIRCGEN.125.005535","url":null,"abstract":"<p><strong>Background: </strong>SGLT2 (sodium-glucose cotransporter-2) inhibitors and GLP-1R (glucagon-like peptide-1 receptor) agonists reduce the risk of major adverse cardiovascular and kidney events in individuals with various cardiometabolic conditions. The long-term efficacy and safety of these therapies, especially in low- and moderate-risk populations, remain uncertain.</p><p><strong>Methods: </strong>We conducted a biobank-scale analysis using genetic instruments derived from naturally occurring genetic variations in the genes encoding the targets of SGLT2 inhibitors (SLC5A2) and GLP-1R agonists (GLP1R) that are associated with glycated hemoglobin levels. This Mendelian randomization study utilized data from the All of Us Research Program, which includes whole genome sequencing and electronic health records of 633 547 participants.</p><p><strong>Results: </strong>Higher SGLT2 inhibitor genetic instrument scores were associated with a lower risk of heart failure (odds ratio [OR], 0.97 [95% CI, 0.96-0.99]) and chronic kidney disease (OR, 0.98 [95% CI, 0.96-0.99]). Higher GLP-1R agonist genetic instrument scores were linked to reduced risks of heart failure (OR, 0.97 [95% CI, 0.96-0.99]), chronic kidney disease (OR, 0.96 [95% CI, 0.95-0.98]), and coronary artery disease (OR, 0.98 [95% CI, 0.96-0.99]). We did not detect associations between the GLP-1R agonist instrument and multiple endocrine neoplasia or medullary thyroid carcinoma. PheWAS (Phenome-Wide Association Study) identified associations between the SGLT2 inhibitor and GLP-1R agonist genetic instruments and a lower risk of diabetes, but no other phenotypes.</p><p><strong>Conclusions: </strong>This study demonstrates the utility of biobank-scale health data for pharmacology research and suggests that, if feasible to implement in routine practice, long-term, primary prevention with an SGLT2 inhibitor or GLP-1R agonist would safely lower the risk of major adverse cardiovascular and kidney events in low- to moderate-risk adults.</p>","PeriodicalId":10326,"journal":{"name":"Circulation: Genomic and Precision Medicine","volume":" ","pages":"e005535"},"PeriodicalIF":6.1,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13120722/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147764306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Novel RYR2-A4510T Variant Presenting Both as Autosomal Dominant and Autosomal Recessive Catecholaminergic Polymorphic Ventricular Tachycardia.","authors":"Auke T Bergeman, Peter Lauffer, Johanna C Herkert, Frederik M A van den Heuvel, Sally-Ann B Clur, Alexa M C Vermeer, Alexander J A Groffen, Jan D H Jongbloed, Ingrid P C Krapels, Christian Schroer, Sabine C M Eijsbouts, Paul G A Volders, Vincent van der Pas, Shanshan Tian, Hai-Lei Zhu, Ruiwu Wang, John Paul Estillore, Arthur A M Wilde, Christian van der Werf, S R Wayne Chen, Saskia N van der Crabben","doi":"10.1161/CIRCGEN.125.005625","DOIUrl":"10.1161/CIRCGEN.125.005625","url":null,"abstract":"","PeriodicalId":10326,"journal":{"name":"Circulation: Genomic and Precision Medicine","volume":" ","pages":"e005625"},"PeriodicalIF":6.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147644189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Targeting PPAR-γ Reduces Fibrosis and Arrhythmogenic Remodeling in DSG2-Linked Arrhythmogenic Cardiomyopathy.","authors":"Yung-Hsin Yeh, Yu-Shien Ko, Yi-Hsin Chan, Ying-Ju Lai, Gwo-Jyh Chang, Chi-Jen Chang, Lung-An Hsu","doi":"10.1161/CIRCGEN.125.005434","DOIUrl":"10.1161/CIRCGEN.125.005434","url":null,"abstract":"<p><strong>Background: </strong>Arrhythmogenic cardiomyopathy is an inherited disorder characterized by fibro-fatty myocardial replacement and ventricular arrhythmias. Although desmosomal mutations such as desmoglein-2 (<i>DSG2</i>) are well-established causes, the pathogenic mechanisms of specific missense variants remain incompletely defined.</p><p><strong>Methods: </strong>We generated a physiologically relevant <i>Dsg2</i>^{<i>F536C/F536C</i>} knock-in mouse model using CRISPR/Cas9 to mimic the human <i>DSG2</i> p.Phe531Cys mutation. Comprehensive phenotyping included histopathology, immunostaining, transcriptomic profiling, in vitro cardiomyocyte and fibroblast assays, in vivo imaging and ECG analysis, and ex vivo optical mapping. Therapeutic potential was assessed using the PPAR-γ (peroxisome proliferator-activated receptor gamma) antagonist GW9662.</p><p><strong>Results: </strong><i>Dsg2</i>^{<i>F536C/F536C</i>} mice developed progressive cardiac hypertrophy, interstitial fibrosis, lipid accumulation, and inducible ventricular arrhythmias following isoproterenol infusion and programmed electrical stimulation. These changes led to severe cardiac dysfunction and reduced survival. Mechanistically, the mutation caused reduced DSG2 and nuclear accumulation of β-catenin and PPAR-γ, promoting triacylglycerol biosynthesis, oxidative stress, cardiomyocyte death, and calcium-handling abnormalities. We also identified activation of epicardial epithelial-to-mesenchymal transition and paracrine fibroblast activation via IL-6 (interleukin-6) and PDGF-BB (platelet-derived growth factor-BB) as key contributors to fibrotic remodeling. Optical mapping revealed prolonged and heterogeneous action potential duration, with both reentrant and focal ectopic mechanisms of ventricular tachycardia. Treatment with GW9662 attenuated lipid accumulation, fibrosis, reactive oxygen species production, and arrhythmogenic susceptibility.</p><p><strong>Conclusions: </strong>The <i>Dsg2</i>^{<i>F536C/F536C</i>} knock-in mouse is a genotype-specific arrhythmogenic cardiomyopathy model that links desmosomal dysfunction to metabolic remodeling, epicardial epithelial-to-mesenchymal transition, and electrophysiological instability. PPAR-γ inhibition ameliorated structural and arrhythmogenic remodeling, supporting PPAR-γ as a potential therapeutic target and advancing precision strategies for desmosome-related cardiomyopathies.</p>","PeriodicalId":10326,"journal":{"name":"Circulation: Genomic and Precision Medicine","volume":" ","pages":"e005434"},"PeriodicalIF":6.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147688494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic Testing in Congenital Heart Disease: From Microarray to Genome Sequencing.","authors":"Clara Sandmann, Sarah U Morton","doi":"10.1161/CIRCGEN.126.005794","DOIUrl":"10.1161/CIRCGEN.126.005794","url":null,"abstract":"","PeriodicalId":10326,"journal":{"name":"Circulation: Genomic and Precision Medicine","volume":" ","pages":"e005794"},"PeriodicalIF":6.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147980608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}