Daily Cardiology Research Analysis
Analyzed 61 papers and selected 3 impactful papers.
Summary
Multi-ancestry and multitrait genetic studies substantially advance understanding of aortic stenosis by identifying hundreds of loci, valve-specific TWAS genes, and clinically promising polygenic risk scores. Complementing this, a mechanistic study uncovers IDH2 lactylation as a driver of angiogenesis in diabetic myocardial infarction via Cav1–eNOS regulation, highlighting a modifiable pathway with therapeutic potential.
Research Themes
- Genetic architecture and risk prediction of aortic stenosis
- Mechanistic angiogenesis pathways in diabetic myocardial infarction
- AI-enabled imaging phenotypes integrated with genomics
Selected Articles
1. Genomic and transcriptomic analyses of aortic stenosis enhance therapeutic target discovery and disease prediction.
A multi-ancestry GWAS meta-analysis of 2.85 million individuals identified 244 risk loci (including X chromosome) for aortic stenosis, with valve-specific TWAS implicating 54 genes. Functional silencing of CMKLR1 and LTBP4 reduced mineralization in human valve cells, and a new polygenic risk score was developed, linking fatty acid and TGF-β pathways to disease biology and risk prediction.
Impact: This work maps the genetic architecture of AS at scale, prioritizes causal pathways via valve TWAS and functional assays, and provides a clinically actionable polygenic risk score.
Clinical Implications: Findings support risk stratification using polygenic scores and nominate therapeutic targets (for example, CMKLR1, TGF-β signaling) for drug development in AS, a disease lacking pharmacotherapy.
Key Findings
- Multi-ancestry GWAS meta-analysis (86,864 AS cases among 2,853,408 individuals) identified 241 autosomal and 3 X-chromosome risk loci.
- Valve TWAS discovered 54 genes whose genetically predicted expression influences AS risk.
- Silencing CMKLR1 and LTBP4 in human valvular interstitial cells substantially decreased mineralization, implicating PUFA and TGF-β pathways.
- A new polygenic risk score for AS was constructed.
Methodological Strengths
- Very large, multi-ancestry GWAS meta-analysis with sex- and ancestry-stratified analyses
- Integration of valve tissue eQTL-based TWAS and functional gene silencing to support causality
Limitations
- Observational genetic associations limit causal inference beyond tested genes
- Clinical utility of the polygenic score requires external validation across diverse populations and care settings
Future Directions: Prospective validation of the AS polygenic risk score, mechanistic dissection of prioritized genes (for example, CMKLR1, LTBP4), and target-based drug discovery and preclinical testing.
Aortic stenosis (AS) is a common valvular heart disease and has no pharmacological therapies. We performed a multi-ancestry genome-wide association meta-analysis of 86,864 AS cases among 2,853,408 individuals, discovering 241 autosomal independent risk loci and 3 X chromosome risk loci. We additionally performed sex-stratified and ancestry-stratified genome-wide association studies (GWASs), identifying an additional 5 sex-specific risk loci, 11 risk loci in European ancestry individuals and 1 risk locus in African ancestry individuals. We also performed a transcriptome-wide association study using expression quantitative trait loci from human aortic valves, discovering 54 new genes for which genetically predicted expression influences the risk of AS. We then generated a new polygenic risk score for AS. Finally, we performed gene silencing experiments targeting biologically relevant genes identified by our GWAS. Silencing of CMKLR1 and LTBP4 in human valvular interstitial cells substantially decreased mineralization, implicating a role for polyunsaturated fatty acids and transforming growth factor β signaling in AS.
2. Multitrait analyses identify genetic variants associated with aortic valve function and aortic stenosis risk.
Deep learning-derived MRI valve metrics in 59,571 UK Biobank participants enabled GWAS that, when integrated with AS GWAS via MTAG, revealed 166 loci including lipid genes (PCSK9, LDLR). A multitrait polygenic score strongly stratified AS risk in the All of Us cohort (HR 3.32 for top 5% vs others), demonstrating translational potential for prediction.
Impact: By fusing AI-derived imaging phenotypes with genetics, this study uncovers loci influencing valve function and delivers a high-performing AS polygenic score validated across cohorts.
Clinical Implications: Multitrait polygenic risk scores could inform earlier identification and monitoring of individuals at high risk for aortic stenosis, complementing imaging-based assessment and preventive strategies.
Key Findings
- Deep learning quantified aortic valve peak velocity, mean gradient, and valve area from MRI in 59,571 participants for GWAS.
- MTAG integrating valve trait GWAS with AS GWAS identified 166 distinct loci, including PCSK9 and LDLR.
- The MTAG-derived AS polygenic score predicted AS in All of Us (HR 3.32 for top 5% vs others).
Methodological Strengths
- Integration of AI-derived imaging phenotypes with large-scale genomics
- External validation of polygenic scoring in an independent national cohort
Limitations
- Discovery dataset primarily from UK Biobank, potentially limiting ancestry diversity
- Imaging-derived phenotypes may introduce measurement biases; PRS calibration is needed across health systems
Future Directions: Expand validation in non-European ancestries, test clinical impact of AS PRS-guided surveillance, and dissect lipid and valve biology at implicated loci.
The genetic influences on normal aortic valve function and their impact on aortic stenosis risk are of substantial interest. We used deep learning to measure peak velocity, mean gradient and aortic valve area from magnetic resonance imaging and conducted genome-wide association studies (GWAS) in 59,571 participants in the UK Biobank. Incorporating the aortic valve measurement GWAS with aortic stenosis GWAS using multitrait analysis of GWAS (MTAG), we identified 166 distinct loci (134 with aortic valve traits, 134 with aortic stenosis and 166 unique loci across all GWAS), including PCSK9 and LDLR. The MTAG aortic stenosis PGS was associated with aortic stenosis in All of Us (hazard ratio (HR) = 3.32 for top 5% versus all others, P = 8.8 × 10
3. IDH2 lactylation promotes angiogenesis in murine diabetic myocardial infarction via blocking Cav1-eNOS interaction.
Using LC–MS/MS, the study identifies IDH2 K272 lactylation in diabetic MI, which enhances Cav1 binding, disrupts Cav1–eNOS interaction, activates eNOS, and promotes endothelial angiogenesis under high glucose and hypoxia. Endothelial K272R knock-in mice exhibit impaired angiogenesis and worse remodeling; ACAT1 and HDAC1 modulate IDH2 lactylation with lactate via MCT1. Empagliflozin enhanced IDH2 lactylation and mitigated injury.
Impact: This mechanistic discovery links metabolic lactylation to endothelial eNOS signaling and angiogenesis in diabetic MI, nominating a tractable enzymatic pathway for therapeutic intervention.
Clinical Implications: Targeting the IDH2 lactylation axis (for example, ACAT1/HDAC1 or lactate transport) may enhance post-MI angiogenesis in diabetes; findings also suggest a potential mechanistic contributor to benefits of SGLT2 inhibitors.
Key Findings
- IDH2 is lactylated at K272 in diabetic MI, enhancing Cav1 binding and disrupting Cav1–eNOS interaction to activate eNOS and promote angiogenesis.
- Endothelial cell-specific IDH2-K272R knock-in mice show impaired angiogenesis, worse cardiac function, and adverse remodeling.
- ACAT1 and HDAC1 act as lactyltransferase and delactylase using lactate delivered by MCT1; empagliflozin enhanced IDH2 lactylation and mitigated injury.
Methodological Strengths
- Proteome-wide lactylation mapping with LC–MS/MS and targeted mechanistic assays
- In vivo endothelial-specific knock-in model establishing causality for IDH2 K272 lactylation
Limitations
- Preclinical study in male mice; human translatability and sex differences remain to be established
- Pharmacologic modulation (for example, empagliflozin) may have pleiotropic effects beyond lactylation
Future Directions: Validate IDH2 lactylation signatures in human diabetic MI tissues, test selective ACAT1/HDAC1 modulators, and evaluate therapeutic efficacy in large-animal diabetic MI models.
Compensatory angiogenesis is critical for preserving left ventricular function after myocardial infarction; however, this process is severely impaired in diabetes, exacerbating adverse outcomes in diabetic myocardial infarction (DMI). This study employed liquid chromatography-tandem mass spectrometry to identify lactylated proteins in the infarct border zone of DMI male mouse hearts. Our findings revealed that IDH2 is lactylated at lysine 272, enhancing its binding to Cav1 while inhibiting the Cav1-eNOS interaction. This modification promotes eNOS activity and facilitates the proliferation, migration, and angiogenesis of cardiac microvascular endothelial cells under high glucose and hypoxic conditions. In endothelial cell-specific IDH2-K272R knock-in male mice, the loss of K272 lactylation impairs cardiac function and exacerbates pathological remodeling due to disrupted angiogenesis. Additionally, ACAT1 and HDAC1 act as lactyltransferase and delactylase, respectively, utilizing intracellular lactate transported via MCT1 as a substrate for IDH2 lactylation. Furthermore, pharmacologic enhancement of IDH2 lactylation, as demonstrated by empagliflozin mitigating post-DMI injury, supports its potential as a therapeutic target for DMI.