Roles of mTOR in thoracic aortopathy understood by complex intracellular signaling interactions

Modeling cardiomyocyte signaling and metabolism predicts genotype-to-phenotype mechanisms in hypertrophic cardiomyopathy

Familial hypertrophic cardiomyopathy (HCM) is a significant precursor of heart failure and sudden cardiac death, primarily caused by mutations in sarcomeric and structural proteins. Despite the extensive research on the HCM genotype, the complex and context-specific nature of many signaling and metabolic pathways linking the HCM genotype to phenotype has hindered therapeutic advancements for patients. Here, we have developed a computational model of HCM encompassing cardiomyocyte signaling and metabolic networks and their associated interactions. Utilizing a stochastic logic-based ODE approach, we linked cardiomyocyte signaling to the metabolic network through a gene regulatory network and post-translational modifications. We validated the model against published data on activities of signaling species in the HCM context and transcriptomes of two HCM mouse models (i.e., R403Q-αMyHC and R92W-TnT). Our model predicts that HCM mutation induces changes in metabolic functions such as ATP synthase deficiency and a transition from fatty acids to carbohydrate metabolism. The model indicated major shifts in glutamine-related metabolism and increased apoptosis after HCM-induced ATP synthase deficiency. We predicted that the transcription factors STAT, SRF, GATA4, TP53, and FoxO are the key regulators of cardiomyocyte hypertrophy and apoptosis in HCM in alignment with experiments. Moreover, we identified shared (e.g., activation of PGC1α by AMPK, and FHL1 by titin) and context-specific mechanisms (e.g., regulation of Ca2+ sensitivity by titin in HCM patients) that may control genotype-to-phenotype transition in HCM across different species or mutations. We also predicted potential combination drug targets for HCM (e.g., mavacamten plus ROS inhibitors) preventing or reversing HCM phenotype (i.e., hypertrophic growth, apoptosis, and metabolic remodeling) in cardiomyocytes. This study provides new insights into mechanisms linking genotype to phenotype in familial hypertrophic cardiomyopathy and offers a framework for assessing new treatments and exploring variations in HCM experimental models.

Short-Term Disruption of TGFβ Signaling in Adult Mice Renders the Aorta Vulnerable to Hypertension-Induced Dissection

Hypertension and transient increases in blood pressure from extreme exertion are risk factors for aortic dissection in patients with age-related vascular degeneration or inherited connective tissue disorders. Yet, the common experimental model of angiotensin II-induced aortopathy in mice appears independent of high blood pressure as lesions do not occur in response to an alternative vasoconstrictor, norepinephrine, and are not prevented by co-treatment with a vasodilator, hydralazine. We investigated vasoconstrictor administration to adult mice 1 week after disruption of TGFβ signaling in smooth muscle cells. Norepinephrine increased blood pressure and induced aortic dissection by 7 days and even within 30 minutes that was rescued by hydralazine; results were similar with angiotensin II. Changes in regulatory contractile molecule expression were not of pathological significance. Rather, reduced synthesis of extracellular matrix yielded a vulnerable aortic phenotype by decreasing medial collagen, most dynamically type XVIII, and impairing cell-matrix adhesion. We conclude that transient and sustained increases in blood pressure cause dissection in aortas rendered vulnerable by inhibition of TGFβ-driven extracellular matrix production by smooth muscle cells. A corollary is that medial fibrosis, a frequent feature of medial degeneration, may afford some protection against aortic dissection.

Multiscale insights into postnatal aortic development

Despite its vital importance for establishing proper cardiovascular function, the process through which the vasculature develops and matures postnatally remains poorly understood. From a clinical perspective, an ability to mechanistically model the developmental time course in arteries and veins, as well as to predict how various pathologies and therapeutic interventions alter the affected vessels, promises to improve treatment strategies and long-term clinical outcomes, particularly in pediatric patients suffering from congenital heart defects. In the present study, we conducted a multiscale investigation into the postnatal development of the murine thoracic aorta, examining key allometric relations as well as relationships between in vivo mechanical stresses, collagen and elastin expression, and the gradual accumulation of load-bearing constituents within the aortic wall. Our findings suggest that the production of fibrillar collagens in the developing aorta associates strongly with the ratio of circumferential stresses between systole and diastole, hence emphasizing the importance of a pulsatile mechanobiological stimulus. Moreover, rates of collagen turnover and elastic fiber compaction can be inferred directly by synthesizing transcriptional data and quantitative histological measurements of evolving collagen and elastin content. Consistent with previous studies, we also observed that wall shear stresses acting on the aorta are similar at birth and in maturity, supporting the hypothesis that at least some stress targets are established early in development and maintained thereafter, thus providing a possible homeostatic basis to guide future experiments and inform future predictive modeling.

Multiscale computational model predicts how environmental changes and drug treatments affect microvascular remodeling in fibrotic disease

Investigating the molecular, cellular, and tissue-level changes caused by disease, and the effects of pharmacological treatments across these biological scales, necessitates the use of multiscale computational modeling in combination with experimentation. Many diseases dynamically alter the tissue microenvironment in ways that trigger microvascular network remodeling, which leads to the expansion or regression of microvessel networks. When microvessels undergo remodeling in idiopathic pulmonary fibrosis (IPF), functional gas exchange is impaired due to loss of alveolar structures and lung function declines. Here, we integrated a multiscale computational model with independent experiments to investigate how combinations of biomechanical and biochemical cues in IPF alter cell fate decisions leading to microvascular remodeling. Our computational model predicted that extracellular matrix (ECM) stiffening reduced microvessel area, which was accompanied by physical uncoupling of endothelial cell (ECs) and pericytes, the cells that comprise microvessels. Nintedanib, an FDA-approved drug for treating IPF, was predicted to further potentiate microvessel regression by decreasing the percentage of quiescent pericytes while increasing the percentage of pericytes undergoing pericyte-myofibroblast transition (PMT) in high ECM stiffnesses. Importantly, the model suggested that YAP/TAZ inhibition may overcome the deleterious effects of nintedanib by promoting EC-pericyte coupling and maintaining microvessel homeostasis. Overall, our combination of computational and experimental modeling can explain how cell decisions affect tissue changes during disease and in response to treatments.

Logic-based modeling of biological networks with Netflux

Molecular signaling networks drive a diverse range of cellular decisions, including whether to proliferate, how and when to die, and many processes in between. Such networks often connect hundreds of proteins, genes, and processes. Understanding these complex networks is greatly aided by computational modeling, but these tools require extensive programming knowledge. In this article, we describe a user-friendly, programming-free network simulation tool called Netflux (https://github.com/saucermanlab/Netflux). Over the last decade, Netflux has been used to construct numerous predictive network models that have deepened our understanding of how complex biological networks make cell decisions. Here, we provide a Netflux tutorial that covers how to construct a network model and then simulate network responses to perturbations. Upon completion of this tutorial, you will be able to construct your own model in Netflux and simulate how perturbations to proteins and genes propagate through signaling and gene-regulatory networks.

A multiscale computational model of arterial growth and remodeling including Notch signaling

Blood vessels grow and remodel in response to mechanical stimuli. Many computational models capture this process phenomenologically, by assuming stress homeostasis, but this approach cannot unravel the underlying cellular mechanisms. Mechano-sensitive Notch signaling is well-known to be key in vascular development and homeostasis. Here, we present a multiscale framework coupling a constrained mixture model, capturing the mechanics and turnover of arterial constituents, to a cell-cell signaling model, describing Notch signaling dynamics among vascular smooth muscle cells (SMCs) as influenced by mechanical stimuli. Tissue turnover was regulated by both Notch activity, informed by in vitro data, and a phenomenological contribution, accounting for mechanisms other than Notch. This novel framework predicted changes in wall thickness and arterial composition in response to hypertension similar to previous in vivo data. The simulations suggested that Notch contributes to arterial growth in hypertension mainly by promoting SMC proliferation, while other mechanisms are needed to fully capture remodeling. The results also indicated that interventions to Notch, such as external Jagged ligands, can alter both the geometry and composition of hypertensive vessels, especially in the short term. Overall, our model enables a deeper analysis of the role of Notch and Notch interventions in arterial growth and remodeling and could be adopted to investigate therapeutic strategies and optimize vascular regeneration protocols.

Vascular smooth muscle cell mechanotransduction through serum and glucocorticoid inducible kinase-1 promotes interleukin-6 production and macrophage accumulation in murine hypertension

Objective

The objective of this investigation was to demonstrate that in vivo induction of hypertension (HTN) and in vitro cyclic stretch of aortic vascular smooth muscle cells (VSMCs) can cause serum and glucocorticoid-inducible kinase (SGK-1)-dependent production of cytokines to promote macrophage accumulation that may promote vascular pathology.

Methods

HTN was induced in C57Bl/6 mice with angiotensin II infusion (1.46 mg/kg/day × 21 days) with or without systemic infusion of EMD638683 (2.5 mg/kg/day × 21 days), a selective SGK-1 inhibitor. Systolic blood pressure was recorded. Abdominal aortas were harvested to quantify SGK-1 activity (pSGK-1/SGK-1) by immunoblot. Flow cytometry quantified the abundance of CD11b+/F480+ cells (macrophages). Plasma interleukin (IL)-6 and monocyte chemoattractant protein-1 (MCP-1) was assessed by enzyme-linked immunosorbent assay. Aortic VSMCs from wild-type mice were subjected to 12% biaxial cyclic stretch (Stretch) for 3 or 12 hours with or without EMD638683 (10 μM) and with or without SGK-1 small interfering RNA with subsequent quantitative polymerase chain reaction for IL-6 and MCP-1 expression. IL-6 and MCP-1 in culture media were analyzed by enzyme-linked immunosorbent assay. Aortic VSMCs from SGK-1flox+/+ mice were transfected with Cre-Adenovirus to knockdown SGK-1 (SGK-1KD VSMCs) and underwent parallel tension experimentation. Computational modeling was used to simulate VSMC signaling. Statistical analysis included analysis of variance with significance at a P value of <.05.

Results

SGK-1 activity, abundance of CD11b+/F4-80+ cells, and plasma IL-6 were increased in the abdominal aorta of mice with HTN and significantly reduced by treatment with EMD638683. This outcome mirrored the increased abundance of IL-6 in media from Stretch C57Bl/6 VSMCs and attenuation of the effect with EMD638683 or SGK-1 small interfering RNA. C57Bl/6 VSMCs also responded to Stretch with increased MCP-1 expression and secretion into the culture media. Further supporting the integral role of mechanical signaling through SGK-1, target gene expression and cytokine secretion was unchanged in SGK-1KD VSMCs with Stretch, and computer modeling confirmed SGK-1 as an intersecting node of signaling owing to mechanical strain and angiotensin II.

Conclusions

Mechanical activation of SGK-1 in aortic VSMCs can promote inflammatory signaling and increased macrophage abundance, therefore this kinase warrants further exploration as a pharmacotherapeutic target to abrogate hypertensive vascular pathology.

Biomechanical and transcriptional evidence that smooth muscle cell death drives an osteochondrogenic phenotype and severe proximal vascular disease in progeria

Hutchinson-Gilford Progeria Syndrome results in rapid aging and severe cardiovascular sequelae that accelerate near end-of-life. We found a progressive disease process in proximal elastic arteries that was less evident in distal muscular arteries. Changes in aortic structure and function were then associated with changes in transcriptomics assessed via both bulk and single cell RNA sequencing, which suggested a novel sequence of progressive aortic disease: adverse extracellular matrix remodeling followed by mechanical stress-induced smooth muscle cell death, leading a subset of remnant smooth muscle cells to an osteochondrogenic phenotype that results in an accumulation of proteoglycans that thickens the aortic wall and increases pulse wave velocity, with late calcification exacerbating these effects. Increased central artery pulse wave velocity is known to drive left ventricular diastolic dysfunction, the primary diagnosis in progeria children. It appears that mechanical stresses above ~ 80 kPa initiate this progressive aortic disease process, explaining why elastic lamellar structures that are organized early in development under low wall stresses appear to be nearly normal whereas other medial constituents worsen progressively in adulthood. Mitigating early mechanical stress-driven smooth muscle cell loss/phenotypic modulation promises to have important cardiovascular implications in progeria patients.

Lineage-Specific Induced Pluripotent Stem Cell-Derived Smooth Muscle Cell Modeling Predicts Integrin Alpha-V Antagonism Reduces Aortic Root Aneurysm Formation in Marfan Syndrome Mice

BACKGROUND

The role of increased smooth muscle cell (SMC) integrin αv signaling in Marfan syndrome (MFS) aortic aneurysm remains unclear. Herein, we examine the mechanism and potential efficacy of integrin αv blockade as a therapeutic strategy to reduce aneurysm progression in MFS.

METHODS

Induced pluripotent stem cells (iPSCs) were differentiated into aortic SMCs of the second heart field (SHF) and neural crest (NC) lineages, enabling in vitro modeling of MFS thoracic aortic aneurysms. The pathological role of integrin αv during aneurysm formation was confirmed by blockade of integrin αv with GLPG0187 in Fbn1C1039G/+ MFS mice.

RESULTS

iPSC-derived MFS SHF SMCs overexpress integrin αv relative to MFS NC and healthy control SHF cells. Furthermore, integrin αv downstream targets (FAK [focal adhesion kinase]/AktThr308/mTORC1 [mechanistic target of rapamycin complex 1]) were activated, especially in MFS SHF. Treatment of MFS SHF SMCs with GLPG0187 reduced p-FAK/p-AktThr308/mTORC1 activity back to control SHF levels. Functionally, MFS SHF SMCs had increased proliferation and migration compared to MFS NC SMCs and control SMCs, which normalized with GLPG0187 treatment. In the Fbn1C1039G/+ MFS mouse model, integrin αv, p-AktThr308, and downstream targets of mTORC1 proteins were elevated in the aortic root/ascending segment compared to littermate wild-type control. Mice treated with GLPG0187 (age 6-14 weeks) had reduced aneurysm growth, elastin fragmentation, and reduction of the FAK/AktThr308/mTORC1 pathway. GLPG0187 treatment reduced the amount and severity of SMC modulation assessed by single-cell RNA sequencing.

CONCLUSIONS

The integrin αv-FAK-AktThr308 signaling pathway is activated in iPSC SMCs from MFS patients, specifically from the SHF lineage. Mechanistically, this signaling pathway promotes SMC proliferation and migration in vitro. As biological proof of concept, GLPG0187 treatment slowed aneurysm growth and p-AktThr308 signaling in Fbn1C1039G/+ mice. Integrin αv blockade via GLPG0187 may be a promising therapeutic approach to inhibit MFS aneurysmal growth.

Progression of Thoracic Aortic Dissection Is Aggravated by the hsa_circ_0007386/miR-1271-5P/IGF1R/AKT Axis via Induction of Arterial Smooth Muscle Cell Apoptosis

BACKGROUND

The molecular mechanisms associated with thoracic aortic dissection (TAD) remain poorly understood. A comprehensive high-throughput sequencing-based analysis of the circRNA-miRNA-mRNA competitive endogenous RNA (ceRNA) regulatory network in TAD has not been conducted. The purpose of this study is to identify and verify the key ceRNA networks which may have crucial biological functions in the pathogenesis of TAD.

METHODS

Gene expression profiles of the GSE97745, GSE98770, and GSE52093 datasets were acquired from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using the GEO2R tools. Protein-protein interaction (PPI) networks of the hub genes were constructed using STRING; the hub genes and modules were identified by MCODE and CytoHubba plugins of the Cytoscape. We analyzed the hub genes using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. The functions of these hub genes were assessed using Cytoscape software. Our data-along with data from GSE97745, GSE98770, and GSE52093-were used to verify the findings.

RESULTS

Upon combined biological prediction, a total of 11 ce-circRNAs, 11 ce-miRNAs, and 26 ce-mRNAs were screened to construct a circRNA-miRNA-mRNA ceRNA network. PPI network and module analysis identified four hub nodes, including IGF1R, JAK2, CSF1, and GAB1. Genes associated with the Ras and PI3K-Akt signaling pathways were clustered in the four hub node modules in TAD. The node degrees were most significant for IGF1R, which were also the most significant in the two modules (up module and hub module). IGF1R was selected as a key gene, and the hsa_circ_0007386/miR-1271-5P/IGF1R/AKT regulatory axis was established. The relative expression levels of the regulatory axis members were confirmed by RT-PCR in 12 samples, including TAD tissues and normal tissues. Downregulation of IGF1R expression in smooth muscle cells (SMCs) was found to induce apoptosis by regulating the AKT levels. In addition, IGF1R showed high diagnostic efficacy in both AD tissue and blood samples.

CONCLUSIONS

The hsa_circ_0007386/miR-1271-5P/IGF1R/AKT axis may aggravate the progression of TAD by inducing VSMCs apoptosis. CeRNA networks could provide new insights into the underlying molecular mechanisms of TAD. In addition, IGF1R showed high diagnostic efficacy in both tissue and plasma samples in TAD, which can be considered as a diagnostic marker for TAD.

Molecular Mechanisms in Genetic Aortopathy-Signaling Pathways and Potential Interventions

Thoracic aortic disease affects people of all ages and the majority of those aged <60 years have an underlying genetic cause. There is presently no effective medical therapy for thoracic aneurysm and surgery remains the principal intervention. Unlike abdominal aortic aneurysm, for which the inflammatory/atherosclerotic pathogenesis is well established, the mechanism of thoracic aneurysm is less understood. This paper examines the key cell signaling systems responsible for the growth and development of the aorta, homeostasis of endothelial and vascular smooth muscle cells and interactions between pathways. The evidence supporting a role for individual signaling pathways in pathogenesis of thoracic aortic aneurysm is examined and potential novel therapeutic approaches are reviewed. Several key signaling pathways, notably TGF-β, WNT, NOTCH, PI3K/AKT and ANGII contribute to growth, proliferation, cell phenotype and survival for both vascular smooth muscle and endothelial cells. There is crosstalk between pathways, and between vascular smooth muscle and endothelial cells, with both synergistic and antagonistic interactions. A common feature of the activation of each is response to injury or abnormal cell stress. Considerable experimental evidence supports a contribution of each of these pathways to aneurysm formation. Although human information is less, there is sufficient data to implicate each pathway in the pathogenesis of human thoracic aneurysm. As some pathways i.e., WNT and NOTCH, play key roles in tissue growth and organogenesis in early life, it is possible that dysregulation of these pathways results in an abnormal aortic architecture even in infancy, thereby setting the stage for aneurysm development in later life. Given the fine tuning of these signaling systems, functional polymorphisms in key signaling elements may set up a future risk of thoracic aneurysm. Multiple novel therapeutic agents have been developed, targeting cell signaling pathways, predominantly in cancer medicine. Future investigations addressing cell specific targeting, reduced toxicity and also less intense treatment effects may hold promise for effective new medical treatments of thoracic aortic aneurysm.

Smooth Muscle Cell Death Drives an Osteochondrogenic Phenotype and Severe Proximal Vascular Disease in Progeria

Hutchinson-Gilford Progeria Syndrome results in rapid aging and severe cardiovascular sequelae that accelerate near end of life. We associate progressive deterioration of arterial structure and function with single cell transcriptional changes, which reveals a rapid disease process in proximal elastic arteries that largely spares distal muscular arteries. These data suggest a novel sequence of progressive vascular disease in progeria: initial extracellular matrix remodeling followed by mechanical stress-induced smooth muscle cell death in proximal arteries, leading a subset of remnant smooth muscle cells to an osteochondrogenic phenotypic modulation that results in an accumulation of proteoglycans that thickens the wall and increases pulse wave velocity, with late calcification exacerbating these effects. Increased pulse wave velocity drives left ventricular diastolic dysfunction, the primary diagnosis in progeria children. Mitigating smooth muscle cell loss / phenotypic modulation promises to have important cardiovascular implications in progeria patients.

Intracellular signaling control of mechanical homeostasis in the aorta

Mature arteries exhibit a preferred biomechanical state in health evidenced by a narrow range of intramural and wall shear stresses. When stresses are perturbed by changes in blood pressure or flow, homeostatic mechanisms tend to restore target values via altered contractility and/or cell and matrix turnover. In contrast, vascular disease associates with compromised homeostasis, hence we must understand mechanisms underlying mechanical homeostasis and its robustness. Here, we use a multiscale computational model wherein mechanosensitive intracellular signaling pathways drive arterial growth and remodeling. First, we identify an ensemble of cell-level parameterizations where tissue-level responses are well-regulated and adaptive to hemodynamic perturbations. The responsible mechanism is persistent multiscale negative feedback whereby mechanosensitive signaling drives mass turnover until homeostatic target stresses are reached. This demonstrates how robustness emerges despite inevitable cell and individual heterogeneity. Second, we investigate tissue-level effects of signaling node knockdowns (ATIR, ROCK, TGF[Formula: see text]RII, PDGFR, ERK1/2) and find general agreement with experimental reports of fault tolerance. Robustness against structural changes manifests via low engagement of the node under baseline stresses or compensatory multiscale feedback via upregulation of additional pathways. Third, we show how knockdowns affect collagen and smooth muscle turnover at baseline and with perturbed stresses. In several cases, basal production is not remarkably affected, but sensitivities to stress deviations, which influence feedback strength, are reduced. Such reductions can impair adaptive responses, consistent with previously reported aortic vulnerability despite grossly normal appearances. Reduced stress sensitivities thus form a candidate mechanism for how robustness is lost, enabling transitions from health towards disease.

On modeling the multiscale mechanobiology of soft tissues: Challenges and progress

Tissues grow and remodel in response to mechanical cues, extracellular and intracellular signals experienced through various biological events, from the developing embryo to disease and aging. The macroscale response of soft tissues is typically nonlinear, viscoelastic anisotropic, and often emerges from the hierarchical structure of tissues, primarily their biopolymer fiber networks at the microscale. The adaptation to mechanical cues is likewise a multiscale phenomenon. Cell mechanobiology, the ability of cells to transform mechanical inputs into chemical signaling inside the cell, and subsequent regulation of cellular behavior through intra- and inter-cellular signaling networks, is the key coupling at the microscale between the mechanical cues and the mechanical adaptation seen macroscopically. To fully understand mechanics of tissues in growth and remodeling as observed at the tissue level, multiscale models of tissue mechanobiology are essential. In this review, we summarize the state-of-the art modeling tools of soft tissues at both scales, the tissue level response, and the cell scale mechanobiology models. To help the interested reader become more familiar with these modeling frameworks, we also show representative examples. Our aim here is to bring together scientists from different disciplines and enable the future leap in multiscale modeling of tissue mechanobiology.

Notch signaling regulates strain-mediated phenotypic switching of vascular smooth muscle cells

Mechanical stimuli experienced by vascular smooth muscle cells (VSMCs) and mechanosensitive Notch signaling are important regulators of vascular growth and remodeling. However, the interplay between mechanical cues and Notch signaling, and its contribution to regulate the VSMC phenotype are still unclear. Here, we investigated the role of Notch signaling in regulating strain-mediated changes in VSMC phenotype. Synthetic and contractile VSMCs were cyclically stretched for 48 h to determine the temporal changes in phenotypic features. Different magnitudes of strain were applied to investigate its effect on Notch mechanosensitivity and the phenotypic regulation of VSMCs. In addition, Notch signaling was inhibited via DAPT treatment and activated with immobilized Jagged1 ligands to understand the role of Notch on strain-mediated phenotypic changes of VSMCs. Our data demonstrate that cyclic strain induces a decrease in Notch signaling along with a loss of VSMC contractile features. Accordingly, the activation of Notch signaling during cyclic stretching partially rescued the contractile features of VSMCs. These findings demonstrate that Notch signaling has an important role in regulating strain-mediated phenotypic switching of VSMCs.

Neural operator learning of heterogeneous mechanobiological insults contributing to aortic aneurysms

Thoracic aortic aneurysm (TAA) is a localized dilatation of the aorta that can lead to life-threatening dissection or rupture. In vivo assessments of TAA progression are largely limited to measurements of aneurysm size and growth rate. There is promise, however, that computational modelling of the evolving biomechanics of the aorta could predict future geometry and properties from initiating mechanobiological insults. We present an integrated framework to train a deep operator network (DeepONet)-based surrogate model to identify TAA contributing factors using synthetic finite-element-based datasets. For training, we employ a constrained mixture model of aortic growth and remodelling to generate maps of local aortic dilatation and distensibility for multiple TAA risk factors. We evaluate the performance of the surrogate model for insult distributions varying from fusiform (analytically defined) to complex (randomly generated). We propose two frameworks, one trained on sparse information and one on full-field greyscale images, to gain insight into a preferred neural operator-based approach. We show that this continuous learning approach can predict the patient-specific insult profile associated with any given dilatation and distensibility map with high accuracy, particularly when based on full-field images. Our findings demonstrate the feasibility of applying DeepONet to support transfer learning of patient-specific inputs to predict TAA progression.