Stefan Bekiranov

Introduction: Coronary artery disease (CAD) is a leading cause of death and disability worldwide. Although genome-wide association studies (GWAS) have identified over 300 loci associated with CAD risk, the molecular mechanisms linking these variants to disease and subclinical atherosclerosis are not fully understood. Methods: We performed integration of multi-ancestry CAD GWAS with transcriptomic data from the Multi-Ethnic Study of Atherosclerosis (MESA) obtained through the Trans-Omics for Precision Medicine (TOPMed) program. For integration, we applied Bayesian colocalization analysis with and without statistical fine-mapping to identify genes whose expression levels colocalize with CAD-associated loci. We further applied causal weighted gene co-expression network analysis (cWGCNA) to identify gene co-expression modules and key driver genes associated with subclinical atherosclerosis traits in MESA. Results: We identified 108 genes showing evidence of colocalization with CAD loci, including 24 shared between the two colocalization approaches and 48 novel genes not previously reported in CAD GWAS. Follow-up replication and validation analyses prioritized 5 novel (CCDC30, ZEB1-AS1, ZPR1, PLEKHJ1 and AC018816.3) and 8 previously reported genes (DHDDS, DDX59, LNPEP, DAGLA, ZKSCAN1, LIPA, OPRL1 and EIF2B2) with putative roles in both CAD and subclinical atherosclerosis. cWGCNA identified five gene modules significantly associated with subclinical atherosclerosis in MESA. Additionally, three key driver genes (ATG9B, PRAM1 and ZBTB46) identified by cWGCNA were also identified as CAD-colocalized genes. Discussion: Our integrative analysis highlights key genetic drivers and regulatory networks underlying CAD and subclinical atherosclerosis. These findings underscore the value of incorporating statistical fine-mapping in colocalization studies and demonstrate the utility of combining colocalization with co-expression network analysis to prioritize functional genes and pathways.

Background and ObjectivesCervical artery dissection (CeAD) is a common cause of stroke in young adults. While the pathogenesis of CeAD remains poorly understood, clinical and genetic associations s...

Heart attacks and strokes are late-stage complications of rupture of unstable atherosclerotic plaques. Stable plaques contain stabilizing matrix-producing fibrotic cells, largely smooth muscle cell (SMC)-derived. The molecular drivers of SMC phenotypic transitions to beneficial fibrotic or destabilizing inflammatory and calcifying phenotypes are unclear. Since atherosclerosis develops over decades, there is extensive interest in identifying dietary alterations that enhance plaque stability. We demonstrate that SMC acquire a fibrotic phenotype dependent on glutamine-derived metabolites supporting both catabolism and collagen synthesis. Moreover, dietary glutamine restriction decreases mortality of mice susceptible to atherosclerotic plaque rupture. Lesions from glutamine-restricted mice are smaller and have increased SMC investment. This study identifies dietary glutamine as a driver of cardiovascular mortality, suggesting a new strategy for reducing late-stage complications of atherosclerosis.

The Koopman-von Neumann (KvN) formalism recasts classical mechanics in a Hilbert space framework using complex wavefunctions and linear operators, akin to quantum mechanics. Instead of evolving probability densities in phase space (as in Liouville's equation), KvN uses a Schrödinger-like equation for a classical wavefunction, with commuting position and momentum operators. Mapped to quantum computing, KvN offers a promising route to simulate classical dynamical systems using quantum algorithms by leveraging unitary evolution and quantum linear algebra tools, potentially enabling efficient classical-to-quantum mappings without invoking full quantum uncertainty. In this work, we specifically explore the implementation of the KvN approach on continuous-variable photonic quantum computing architectures, with the goals of leveraging quantum simulation for both sampling and computing intractable nonlinear dynamics. We will demonstrate its implementation and feasibility with two problems: the harmonic oscillator and a 1D partial differential equation governing nonlinear dynamics.

The five-year survival rate for ovarian cancer patients remains below 50%, underscoring the need for innovative therapies. One promising approach involves engineering T cells to specifically target proteins uniquely overexpressed in tumors, thereby controlling tumor growth without toxicity to healthy tissues. Mesothelin (MSLN) contributes to the malignant and invasive phenotype in ovarian cancer and has limited expression in healthy cells, making it a candidate immunotherapy target. Our previous results in a mouse model of ovarian cancer demonstrated that T cells engineered to express a T cell receptor (TCR) targeting MSLN (TCR _MSLN ) mediated therapeutic activity, delaying tumor growth and prolonging mouse survival. However, inhibitory ligands expressed in the tumor microenvironment (TME) interacted with inhibitory receptors on activated T cells, suppressing antitumor function. We hypothesized combining engineered T cells with checkpoint blockade would enhance T cell function and improve therapeutic efficacy, but administration of monospecific antibodies targeting individual inhibitory pathways had no significant impact on T cell efficacy. By contrast, the combination of PD-1, Tim-3, and Lag-3 blockade with engineered T cells significantly improved T cell function and overall animal survival relative to treatment with antibody alone or TCR _MSLN with singlet or doublet antibody combinations. Single-cell RNA sequencing revealed TCR _MSLN T cells treated with the triplet antibody combination increased expression of genes involved in interferon responses and metabolic function, and reduced expression of genes associated with exhaustion. These results suggest that strategies to disrupt multiple inhibitory pathways simultaneously may be necessary for improved adoptive T cell therapy efficacy in patients.