Skip to Content
BioengineeringBioengineering
  • Review
  • Open Access

12 August 2026

29 Pages

Mouse Models of Atherosclerosis: What They Teach Us, What They Miss, and When to Use Them

,
,
and
1
Division of Clinical Immunology & Rheumatology, Department of Medicine, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA
2
Department of Pathology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA
3
Department of Cellular and Molecular Signaling, The Institute of Biomedicine and Biotechnology of Cantabria, CSIC-University of Cantabria, 39011 Santander, Spain
4
Department of Biomedical Engineering, School of Medicine, The University of Alabama at Birmingham, Birmingham, AL 35294, USA

Abstract

Mouse models have been indispensable for defining the mechanisms of atherosclerosis, yet no single model reproduces the full spectrum of human disease. This review provides a practical framework for selecting mouse models according to the biological question being addressed. We compare classical lipoprotein-driven models, including Apoe−/− and Ldlr−/− mice, with models designed to study human-like lipoprotein metabolism, immune and immunometabolic mechanisms, adult-onset hypercholesterolemia, plaque complexity, coronary disease, and myocardial infarction-like outcomes. Particular emphasis is placed on how genetic background, lipoprotein composition, diet, sex, age, vascular site, and experimental design shape lesion development and influence interpretation. We also discuss discrepancies across single-cell RNA-sequencing studies, highlighting how differences in model, tissue processing, disease stage, and analytical strategy can alter the macrophage and immune-cell states detected. Rather than ranking models, we define what each model can teach, what it may miss, and when it is most appropriate to use. We conclude that future progress will depend on question-driven model selection, cross-model validation, improved reporting, and greater integration of molecular, spatial, and human benchmarking approaches.

1. Introduction

Atherosclerosis is the major pathological process underlying coronary artery disease, ischemic stroke, and peripheral vascular disease [1,2]. It develops over decades and is characterized by the progressive accumulation of lipids, inflammatory cells, smooth muscle cells, extracellular matrix, and necrotic debris within the arterial wall [3,4,5,6,7]. Although atherosclerosis was historically viewed primarily as a lipid-storage disorder, it is now recognized as a chronic immunometabolic disease in which dyslipidemia, endothelial dysfunction, innate and adaptive immune activation, vascular remodeling, and defective resolution of inflammation cooperate to drive lesion initiation, progression, and clinical complications [8,9,10,11,12].
Atherogenesis develops preferentially at arterial sites exposed to disturbed blood flow, such as branch points and curvatures [13]. These hemodynamic environments promote endothelial activation and facilitate the entry of apolipoprotein B-containing lipoproteins, including low-density lipoprotein (LDL), very-low-density lipoprotein (VLDL) remnants, and chylomicron remnants, into the subendothelial space [14]. Once retained within the intima, these lipoproteins undergo oxidative, enzymatic, and other chemical modifications that increase their inflammatory and immunogenic properties. Modified lipoproteins activate endothelial cells and vascular smooth muscle cells, inducing the expression of adhesion molecules and chemokines that recruit circulating leukocytes [15,16,17]. Monocytes subsequently infiltrate the developing lesion, differentiate into macrophages, and internalize modified lipoproteins through scavenger receptors, becoming lipid-laden foam cells. These early events establish a self-amplifying inflammatory circuit in which lipid accumulation and immune activation reinforce each other [9,11,18,19,20,21,22,23].
Vascular smooth muscle cells also play a central role in lesion development. They migrate from the media into the intima, proliferate, and produce extracellular matrix components that contribute to fibrous cap formation [19,20,21]. However, smooth muscle cells are not merely structural components of the plaque. Lineage-tracing and single-cell studies have demonstrated that they can acquire diverse phenotypic states, including macrophage-like and fibroblast-like identities, with potentially lesion-promoting or plaque-stabilizing functions [22,23,24]. Advanced atherosclerotic plaques therefore represent complex multicellular ecosystems in which plaque growth, stability, and the risk of rupture are determined by the balance among lipid deposition, inflammatory activation, matrix remodeling, cell death, and tissue repair [6,25].
Inflammation is no longer recognized as merely a secondary consequence of lipid accumulation but rather as a fundamental driver of atherosclerotic disease [26,27]. Human and experimental atherosclerotic lesions contain diverse immune cell populations, including macrophages, dendritic cells, T cells, B cells, and neutrophils. Monocyte recruitment is regulated by adhesion molecules such as selectins, VCAM-1, and ICAM-1, as well as by chemokine pathways including CCL2-CCR2, CX3CL1-CX3CR1 [28,29,30]. Within plaques, macrophages adopt heterogeneous activation states and produce inflammatory cytokines, proteases, and lipid mediators that influence lesion growth and stability [31,32]. Adaptive immunity also contributes substantially to disease pathogenesis. CD4+ T cells are abundant within atherosclerotic lesions with Th1 responses generally promoting disease progression, whereas regulatory T cells often exert protective effects, although both responses are highly context dependent [33,34,35]. Furthermore, evidence that T cells recognize ApoB-derived peptides supports the concept that atherosclerosis possesses an autoimmune component directed, at least in part, against modified or processed lipoprotein antigens.
Despite major advances in lipid-lowering therapies, substantial residual cardiovascular risk persists, and a significant proportion of this risk is inflammatory [36,37]. Clinical studies targeting inflammatory pathways have reinforced the concept that inflammation is not merely associated with atherosclerosis but contributes causally to cardiovascular events [38,39]. However, systemic immunosuppression carries significant risks, underscoring the need to identify disease-relevant mechanisms and develop experimental systems capable of disentangling the lipid-driven, immune-driven, metabolic, and vascular contributions to atherogenesis [39,40,41]. Consequently, experimental models remain indispensable tools for understanding disease mechanisms and for evaluating therapeutic strategies (Box 1).
Box 1. Key differences between mouse and human atherosclerosis.
Lipoprotein metabolism. In humans, most circulating cholesterol is transported in ApoB100-containing LDL particles, and additional factors such as CETP and lipoprotein(a) contribute to atherogenic lipoprotein metabolism. In contrast, wild-type mice transport most cholesterol in HDL, produce substantial amounts of ApoB48 through hepatic ApoB mRNA editing, lack CETP and lipoprotein(a), and are relatively resistant to spontaneous atherosclerosis.
Plaque distribution and clinical complications. Human atherosclerosis commonly affects the coronary, carotid, and peripheral arteries and may progress to plaque rupture or erosion, thrombosis, myocardial infarction, and stroke. Standard Apoe−/− and Ldlr−/− mice develop lesions predominantly in the aortic root, aortic arch, brachiocephalic artery, and proximal aorta, whereas spontaneous plaque rupture, occlusive coronary thrombosis, and myocardial infarction are uncommon.
Disease development. Human atherosclerosis develops over decades in the context of aging and the interaction of metabolic, environmental, and inflammatory risk factors. Murine atherosclerosis generally develops over weeks to months and usually requires genetic, viral, or dietary manipulation of lipoprotein metabolism. This accelerated induction facilitates mechanistic studies but may not reproduce the natural history of human disease.
Immune and vascular responses. Both mouse and human plaques exhibit endothelial activation, monocyte recruitment, macrophage foam-cell formation, adaptive immune responses, and smooth-muscle-cell phenotypic remodeling. However, the abundance, localization, and activation states of these populations vary between species, model, vascular site, diet, and disease stage.
Translational implication. No mouse model reproduces the complete spectrum of human atherosclerosis. Model selection should therefore be guided by the specific biological or clinical feature being studied, and major findings should, whenever possible, be validated in complementary models and benchmarked against human data.
Mouse models have been central to atherosclerosis research because they are relatively inexpensive, reproduce rapidly, are genetically tractable, and are highly amenable to dietary, pharmacological, lineage-tracing, and cell-specific genetic manipulations. However, mice do not naturally recapitulate human atherosclerosis [42,43]. Wild-type mice are relatively resistant to spontaneous lesion formation, in part because most circulating cholesterol is carried in high-density lipoproteins (HDL) rather than LDL. Moreover, lipoprotein metabolism, bile acid biology, vascular anatomy, and plaque progression differ substantially between mice and humans [43,44,45]. Consequently, robust experimental atherosclerosis in mice generally requires genetic or viral manipulation of lipid metabolism, often in combination with cholesterol-rich or high-fat diets.
The development of Apoe−/− and Ldlr−/− mice in the early 1990s transformed the field by providing reproducible and genetically tractable models of hypercholesterolemia-driven atherosclerosis [46,47]. These models remain the most widely used systems for studying lesion initiation, immune-cell recruitment, plaque progression, and candidate gene function. Nevertheless, they are not interchangeable. Apoe−/− mice develop spontaneous hyperlipidemia and atherosclerosis even when maintained on a chow diet, largely because of impaired clearance of triglyceride-rich remnant lipoproteins. In contrast, Ldlr−/− mice are more diet-dependent and predominantly accumulate ApoB100-containing LDL, particularly under cholesterol-rich dietary conditions [48,49,50,51]. Furthermore, ApoE and LDLR exert biological functions beyond plasma lipid regulation, influencing immune cell behavior, vascular cell function, and inflammatory responses. Consequently, findings obtained in one model cannot always be generalized to the other.
Over the past three decades, additional mouse models have been developed to address limitations of the classical Apoe−/− and Ldlr−/− systems. These include ApoE/LDLR double knockouts, ApoB100-only or Ldlr−/−/Apobec1−/− models of LDL-driven familial hypercholesterolemia, humanized APOE3-Leiden and APOE3-Leiden.CETP mice, AAV-PCSK9 models that induce hypercholesterolemia without germline modification, somatic genome-editing approaches targeting Ldlr, and models designed to reproduce advanced plaque instability, coronary artery disease, myocardial infarction, or atherothrombosis [52,53,54,55,56,57,58,59]. Each model captures a distinct aspect of human disease while introducing its own biological constraints and experimental limitations.
Rather than providing a simple catalog of available models, this review examines how each model functions as a biological filter that shapes the interpretation of atherosclerosis mechanisms. We focus on how genetic design, lipoprotein context, diet dependence, immune perturbation, lesion distribution, and plaque complexity determine which questions a model can answer, and which conclusions it may inadvertently distort.

2. Models of Atherosclerosis

2.1. Lipoprotein-Driven Models of Lesion Initiation and Progression (Table 1)

Table 1. Comparative characteristics and recommended applications of mouse models of atherosclerosis. This table provides a practical comparison of commonly used and specialized mouse models of atherosclerosis. Models are organized according to the principal disease feature they are designed to interrogate, including lipoprotein-driven lesion development, immunoinflammatory and immunometabolic mechanisms, adult-onset hypercholesterolemia, humanized lipoprotein biology, plaque complexity, coronary artery disease, and myocardial infarction-like outcomes. For each model, the table summarizes the underlying genetic or experimental manipulation, predominant lipoprotein abnormality, dietary dependence, characteristic lesion phenotype, major strengths, principal limitations, and research questions for which the model is best suited. The categories are intended as practical guidance rather than rigid classifications, because several models can be applied across multiple areas of atherosclerosis research. Model performance may also vary according to genetic background, sex, age, diet composition, duration of feeding, microbiota, vascular site, and experimental endpoint.
The most widely used mouse models of atherosclerosis are those in which disease is driven primarily by perturbations in lipoprotein metabolism. This category includes the classical Apoe−/− and Ldlr−/− mice, as well as models developed to recapitulate specific aspects of human dyslipidemia, including Ldlr−/−/Apobec1−/− mice, ApoB100-only models, human ApoB and ApoB/lipoprotein(a) transgenic mice, APOE3-Leiden and APOE3-Leiden.CETP mice, and more recent viral and somatic gene-editing approaches such as PCSK9-AAV, and AAV-CRISPR Ldlr models [53,54,55,60,61,62,63].
These models are essential because wild-type mice are naturally resistant to spontaneous atherosclerosis. Unlike humans, mice transport most circulating cholesterol in HDL-rich particles rather than LDL-rich particles and have very low levels of ApoB-containing atherogenic particles [43,50,64]. As a result, robust lesion formation generally requires experimental strategies (genetic, dietary, transgenic, viral, or somatic editing) that increase non-HDL cholesterol and promote retention of ApoB-containing lipoproteins in the arterial wall.

2.1.1. Apoe−/− Mice: The Classical Remnant-Driven Model

Apoe−/− mice remain the most widely used and experimentally robust model of murine atherosclerosis [65]. APOE is a key ligand that mediates hepatic clearance of chylomicron and VLDL remnants through LDLR, LDL receptor-related protein 1, and heparan sulfate proteoglycans [66,67,68]. Loss of ApoE leads to the spontaneous accumulation of cholesterol-rich remnant lipoproteins and the development of hypercholesterolemia and atherosclerotic lesions, even in chow-fed animals with lesion formation accelerated by Western-type or high-fat/high-cholesterol diets [69,70]. The ease and reproducibility of lesion formation have made Apoe−/− mice invaluable for studying lesion initiation, foam cell formation, vascular inflammation, immune-cell recruitment, candidate gene function, and therapeutic interventions including bone marrow transplantation and pharmacological intervention [71,72,73].
Importantly, Apoe−/− mice should not be viewed simply as hyperlipidemic mice that develop atherosclerosis. ApoE has pleiotropic functions that extend beyond lipoprotein clearance. In addition to being produced by hepatocytes, ApoE is expressed by macrophages and other cell types, where it regulates cholesterol efflux, foam cell formation, oxidative stress, inflammatory signaling, immune regulation, smooth muscle cell behavior, and possibly platelet and endothelial cell function [74,75,76,77,78,79,80,81,82,83]. Consequently, phenotypes observed in Apoe−/− mice reflect the combined effects of hyperlipidemia, plaque formation, and the systemic consequences of ApoE deficiency [66,84,85,86]. This consideration is particularly important when Apoe−/− mice are used to study inflammatory or immunological pathways as findings may not necessarily translate to models where ApoE expression is preserved.

2.1.2. Ldlr−/− Mice: A Model of Diet-Induced LDL-Driven Disease

Ldlr−/− mice provide a complementary model of atherosclerosis [43,46]. In contrast to Apoe−/− mice, chow-fed Ldlr−/− mice develop little spontaneous atherosclerosis and generally require cholesterol-containing or Western-type diets to induce robust lesion formation [50,87,88]. Under these conditions, this mouse model accumulates LDL and VLDL particles and develops lesions in the aortic root, aortic arch, brachiocephalic artery, and en face aorta. Because ApoE expression remains intact, Ldlr−/− mice are often considered more representative of human LDL/ApoB-driven disease [50]. Their dependence on dietary manipulation is both an advantage and a limitation. On one hand, it allows investigators to tune the onset, duration, and severity of hypercholesterolemia. On the other, it makes experimental outcomes highly sensitive to diet composition, cholesterol content, fat source, cholate, duration of feeding, sex, microbiota, and genetic background. The distinction between Apoe−/− and Ldlr−/− mice is therefore not merely technical. Apoe−/− mice predominantly accumulate cholesterol-rich ApoB48-containing remnant particles, whereas Ldlr−/− mice, particularly under specific diet conditions, more closely model accumulation of ApoB100-containing LDL. As a result, interventions that produce similar effects in one model may behave differently in the other depending on lipoprotein context, diet, lesion stage, or vascular bed [50].

2.1.3. Distinct Immune Landscapes in Apoe−/− and Ldlr−/− Mice

Single-cell studies further demonstrate that Apoe−/− and Ldlr−/− mice are not immunologically equivalent. Although a high-fat diet promotes myeloid expansion in both models, the composition of the immune response differs substantially by genotype: Apoe−/− aortas are enriched in B-cell populations, including B2 cells and a small B1-like cluster, whereas Ldlr−/− lesions contain a larger macrophage representation. Within the macrophage compartment, scRNA-seq identifies resident-like macrophages, inflammatory macrophages enriched for Il1b, Ccl2, Ccl3, Ccl4, Cxcl2, Tnf, and Cd14, IFN-inducible macrophages, and TREM2hi foamy macrophages enriched for Trem2, Cd9, Lgals3, Ctsd, Fabp5, and lipid/catabolic programs [8,89,90]. These differences have important experimental implications. An intervention that appears to alter plaque inflammation may be acting on distinct biological processes depending on the model used, including B-cell accumulation, macrophage expansion, inflammatory macrophage activation, IFN-inducible programs, or lipid-handling TREM2hi foam-cell biology. Thus, similar phenotypic outcomes may arise through fundamentally different immune mechanisms.

2.1.4. The Influence of Genetic Background

Genetic background further modifies atherosclerotic susceptibility, lesion composition, and plaque distribution. Although C57BL/6 mice are widely used because of their susceptibility to atherosclerosis, other backgrounds, such as C3H/HeJ, FVB/N, and BALB/c, are comparatively resistant to disease [57,91,92,93]. Studies using Apoe−/− mice on FVB/N, BALB/c, 129/SvEv, and DBA/2J backgrounds have demonstrated marked strain-dependent differences in lesion burden, inflammatory responses, and vascular-site susceptibility [94,95,96,97]. For example, FVB/N-Apoe−/− mice develop substantially smaller aortic-root lesions than C57BL/6-Apoe−/− mice despite higher total cholesterol, whereas 129/SvEv-Apoe−/− mice show delayed lesion initiation in the aortic root but earlier and more extensive disease in the aortic arch, highlighting the contribution of vascular anatomy and local hemodynamics [94,96]. Similar background-dependent effects have been observed in Ldlr−/− mice, with C57BL/6 and FVB/N strains displaying different lesion susceptibility under comparable dietary conditions [98]. Interestingly, a recent comparison of Apoe−/− and Ldlr−/− mice on the atherosclerosis-resistant C3H background showed that high-fat diet-fed C3H-Ldlr−/− mice developed larger aortic-root lesions than C3H-Apoe−/− mice, despite lower MCP-1 levels and similar oxidative-stress markers [70]. These findings suggest that lipoprotein characteristics, including the abundance of small, dense LDL particles, may under some conditions be more important determinants of lesion formation than systemic inflammatory markers. Collectively, these studies underscore that the relative severity of Apoe−/− and Ldlr−/− models depends on interactions among the disrupted gene, genetic background, diet, sex, and vascular site.

2.1.5. Models of Human LDL-Rich Familial Hypercholesterolemia

Several models have been developed to more closely reproduce human LDL-rich familial hypercholesterolemia [99,100,101]. A major species difference is that mouse liver extensively edits ApoB mRNA, favoring ApoB48 production, whereas human liver produces ApoB100 [102,103]. Consequently, standard Ldlr−/− mice do not fully recapitulate human LDL-C-driven familial hypercholesterolemia. Ldlr−/−/Apobec1−/− mice address this limitation by combining LDLR deficiency with loss of ApoB mRNA editing, thereby forcing production of ApoB100 [53,104,105]. These mice develop markedly elevated LDL cholesterol and ApoB100 levels, along with extensive atherosclerosis, even on a low-fat chow diet [53,106]. Similarly, ApoB100-only models and related human ApoB models emphasize the role of ApoB100-containing particles in lesion formation and are particularly useful for studying LDL particle biology, ApoB100-mediated retention, familial hypercholesterolemia, and LDL-targeted therapeutic intervention. Their main limitation is practical: they require more complex breeding strategies and are less amenable to rapid genetic crosses than Apoe−/− or Ldlr−/− [49].

2.1.6. Human ApoB and Lipoprotein(a) Transgenic Models

Human ApoB-transgenic mice provide a complementary strategy for modelling human-like ApoB-containing lipoproteins while preserving endogenous murine clearance pathways [107,108,109,110]. High-expressing lines produce human ApoB100 predominantly in LDL-sized particles and can develop increased VLDL/LDL cholesterol and extensive aortic atherosclerosis, particularly following dietary challenge [88]. These models are therefore useful for studying ApoB production, LDL-particle clearance and retention, lipoprotein oxidation, lipid-driven vascular inflammation, and interventions directed against LDL- or ApoB-containing particles. Their principal limitation is that human ApoB expression alone may produce modest or variable hypercholesterolemia, depending on the transgenic line, and robust lesion development frequently requires an atherogenic diet or combination with additional genetic modifications. Moreover, the presence of human ApoB does not correct other species differences in lipoprotein metabolism, vascular anatomy, or plaque progression. Seminal studies of human ApoB-transgenic mice directly demonstrated the formation of human-like LDL particles and increased aortic atherosclerosis in high-expressing lines.
Models producing human lipoprotein(a) are even more specialized. Mice do not naturally express apo(a), and human apo(a) associates inefficiently with endogenous mouse ApoB [43]. Consequently, authentic human-like Lp(a) particles are generally generated by combining human apo(a) and human ApoB transgenes. These models enable direct investigation of ApoB100–apo(a) assembly, the proatherogenic effects of Lp(a), oxidized phospholipid biology, and therapeutic approaches designed to reduce ApoB or apo(a) expression. However, circulating Lp(a) concentrations and apo(a) isoform characteristics depend strongly on transgene design and expression level and may not reproduce the lifelong exposure or broad apo(a) size heterogeneity observed in humans. In addition, these mice rarely reproduce advanced human complications such as spontaneous plaque rupture, coronary thrombosis, or myocardial infarction. Human ApoB/apo(a) double-transgenic mice have nevertheless provided experimental evidence that Lp(a) is more atherogenic than free apo(a), and they have been used to test antisense-based lipid-lowering strategies.

2.1.7. APOE3-Leiden and APOE3-Leiden.CETP Mice

APOE3-Leiden mice represent another important class of lipoprotein-driven models. The APOE3-Leiden mutation causes a dominant form of familial dysbetalipoproteinemia in humans [111]. Transgenic mice carrying the human APOE3-Leiden construct develop diet-responsive hyperlipoproteinemia characterized by marked increases in cholesterol and triglycerides, primarily within VLDL/LDL-sized fractions [112,113]. APOE3-Leiden mice develop lesions ranging from macrophage-rich fatty streaks to advanced plaques containing oxidized lipoprotein epitopes, smooth muscle cell cap formation, fibrosis, cholesterol crystals, and necrotic features [43,114,115]. Because these mice preserve endogenous mouse ApoE expression in macrophages and other tissues, they provide an alternative to complete ApoE deficiency for studying remnant lipoprotein metabolism and diet-responsive dysbetalipoproteinemia-like atherosclerosis.
APOE3-Leiden.CETP mice extend this approach by introducing human cholesteryl ester transfer protein (CETP), a key component of human lipoprotein metabolism that is absent in mice. CETP expression shifts cholesterol distribution from HDL toward VLDL/LDL, reduces plasma-mediated SR-BI-dependent cholesterol efflux, and markedly increases atherosclerotic lesion area in APOE3-Leiden mice [116]. Because APOE3-Leiden.CETP mice exhibit a more human-like lipoprotein profile and retain an intact ApoE–LDLR remnant-clearance pathway, they are particularly useful for testing lipid-modifying therapies, including interventions targeting VLDL/LDL metabolism, HDL biology, CETP function, and remnant clearance [117,118,119]. Their main limitations are that they are more diet-dependent, develop atherosclerosis more slowly, and are less genetically flexible and less amenable to mechanistic crosses than Apoe−/− or Ldlr−/− mice.
The predictable and adjustable dietary response of APOE3-Leiden.CETP mice makes them particularly valuable for pharmacological studies of dysbetalipoproteinemia, mixed dyslipidemia, remnant metabolism, and lipid-modifying therapies. Nevertheless, the introduction of human APOE3-Leiden and CETP does not overcome the murine vascular anatomy and immune context, and spontaneous plaque rupture, coronary thrombosis, and myocardial infarction remain uncommon. In addition, transgenic expression of APOE3-Leiden and CETP represents a defined experimental perturbation rather than the broader genetic and metabolic heterogeneity of human dyslipidemia.

2.1.8. Viral and Somatic Gene-Editing Approaches

Viral and somatic gene-editing approaches have expanded the lipoprotein-driven toolkit by eliminating the need for extensive breeding strategies. AAV-mediated expression of gain-of-function PCSK9 promotes hepatic LDLR degradation, producing sustained hypercholesterolemia and atherosclerosis after a single injection, usually combined with Western-type or high-fat diet feeding [120,121]. This approach enables rapid induction of atherosclerosis in virtually any genetic background, including conditional knockouts, reporter strains and aged mice [122]. However, PCSK9-AAV should not be considered an interchangeable substitute for Ldlr−/− mice. PCSK9 is expressed at supraphysiological levels and may exert effects beyond LDLR degradation, particularly in studies involving lipoprotein metabolism or macrophage biology [123,124,125].
AAV-CRISPR Ldlr models provide a related but mechanistically distinct approach by directly disrupting hepatic Ldlr in adult mice [55]. These models induce severe hypercholesterolemia and atherosclerosis with a single injection, avoiding the need for germline Ldlr−/− breeding. Importantly, direct comparison between AAV-CRISPR Ldlr and AAV-hPCSK9 showed that both approaches generate atherosclerosis, but their efficiency can differ by sex, with AAV-CRISPR performing better for Ldlr removal in male mice and AAV-hPCSK9 being more effective in female mice [55]. Somatic editing also enables genetic-interaction studies [126,127]. For example, hepatic disruption of Ldlr induces hypercholesterolemia and atherosclerosis, whereas concomitant disruption of Apob prevents disease by reducing hepatic ApoB production [128,129]. These features make AAV-CRISPR models especially useful for adult-onset metabolic disease modeling, therapeutic target validation, and rapid testing of candidate genes. Nevertheless, they are subject to limitations common to somatic editing approaches, including variable editing efficiency, incomplete deletion, potential off-target effects, vector-related confounders, and the need for proper controls.

2.1.9. Summary of Lipoprotein-Driven Models of Lesion Initiation and Progression Models

Collectively, lipoprotein-driven models form the experimental foundation of murine atherosclerosis research, but each represents a distinct biological context rather than a generic model of disease. Apoe−/− mice emphasize remnant-driven hyperlipidemia and complete loss of ApoE biology; Ldlr−/− mice recapitulate diet-dependent LDL/ApoB-driven disease with preserved ApoE; Ldlr−/−/Apobec1−/− and ApoB100-only models closely reproduce human-like LDL-C and ApoB100 excess; human ApoB and Lp(a) transgenic models isolate specific human lipoprotein particles; APOE3-Leiden and APOE3-Leiden.CETP mice capture diet-responsive remnant metabolism and human-like responses to lipid-modifying therapies; and PCSK9-AAV or AAV-CRISPR models offer rapid, flexible, and adult-onset induction of hypercholesterolemia. Therefore, model selection should begin with the underlying lipoprotein question: Is the study focused on remnant lipoproteins, LDL/ApoB100, human ApoB production, Lp(a), humanized lipid pharmacology, rapid disease induction, or the interaction between dyslipidemia and a second biological process?
In addition to selecting the appropriate lipoprotein context, investigators must consider the time required to reach the plaque stage relevant to the biological question. Representative timelines for the development of early and more complex lesions in commonly used Apoe−/−, Ldlr−/−, and PCSK9-AAV models are summarized in Table 2. These timelines should be regarded as practical starting points rather than fixed thresholds because lesion progression is influenced by sex, age, genetic background, diet composition, vascular site, and experimental endpoint.
Table 2. Representative experimental timelines and lesion stages in commonly used mouse models of atherosclerosis. This table provides practical guidance on the approximate time required to generate early and more complex atherosclerotic lesions in commonly used experimental models, including chow-fed Apoe−/− mice, Western diet-fed Ldlr−/− mice, and AAV-PCSK9-induced models. For each model, the table summarizes the dietary or experimental induction strategy, representative windows for early and advanced lesion development, typical research applications, and major factors that may influence disease progression. These timelines are intended as practical starting points rather than fixed thresholds, because lesion development varies according to genetic background, sex, age at study initiation, diet composition, feeding duration, vascular site, vector serotype and dose, efficiency of LDLR depletion, microbiota, and the criteria used to define lesion stage. Investigators should therefore verify plasma lipoprotein levels and plaque characteristics within their specific experimental setting.

2.2. Immunoinflammatory and Immunometabolic Mechanism Models (Table 1)

Atherosclerosis is an inflammatory and immunometabolic disease, but there is no commonly used mouse model in which atherosclerosis is driven by immunity alone. Robust murine lesion formation almost always requires a hyperlipidemic background. Therefore, “immunoinflammatory models” should be understood as lipid-driven models of atherosclerosis that are particularly useful for interrogating immune, inflammatory, or immunometabolic mechanisms. This distinction is important. The goal is not to identify a purely immune model but rather to select a lipid context in which immune mechanisms can be interpreted clearly.

2.2.1. Ldlr−/− Mice for Immune and Inflammatory Studies

Ldlr−/− mice are often the most appropriate classical model for immune and inflammatory studies. Because ApoE expression remains intact, immune phenotypes are less likely to be confounded by complete loss of ApoE-dependent macrophage and immune regulation [43,75,86]. Ldlr−/− mice are therefore well suited for studies of monocyte production, macrophage recruitment, cytokine signaling, inflammasome activation, T-cell responses, sterile inflammatory triggers, trained immunity, bone marrow transplantation, and cell-specific gene deletion [43,130,131,132]. Their diet dependence can also be advantageous experimentally. Short-term high-fat diet feeding can be used to study early leukocyte recruitment and foam-cell formation, whereas prolonged feeding enables the investigation of lesion progression, necrotic core formation, and plaque composition. However, this same diet dependence introduces an important interpretative challenge. Differences in cholesterol content, fat source, carbohydrate composition, cholate, microbiota, sex, age, and feeding duration can substantially alter systemic metabolism and immune tone [133,134].

2.2.2. Apoe−/− Mice and the Challenge of ApoE Deficiency

Apoe−/− mice remain highly valuable for immunological studies because much of the atherosclerosis literature has been generated using this background, including studies of monocyte recruitment, macrophage activation, chemokines, adhesion molecules, T-cell polarization, B-cell responses, cytokine signaling, and innate immune activation [135,136,137,138]. The robustness of lesion formation also makes Apoe−/− mice attractive when substantial disease burden is required without prolonged diet intervention. However, immune studies in Apoe−/− mice require more cautious interpretation. ApoE is not merely a lipoprotein ligand; it also regulates macrophage cholesterol efflux, inflammatory activation, oxidative stress, antigen presentation, T-cell responses, endothelial activation, and smooth muscle cell behavior [139,140,141]. Consequently, immune phenotypes observed in Apoe−/− mice may reflect interactions among the pathway under investigation, hyperlipidemia, and the absence of ApoE itself. For this reason, immune mechanisms identified in Apoe−/− mice are most compelling when validated in Ldlr−/−, PCSK9-AAV, or other ApoE-intact models.

2.2.3. Comparing Apoe−/− and Ldlr−/− Backgrounds

The comparison between Apoe−/− and Ldlr−/− mice is particularly informative for immunoinflammatory studies. Some interventions produce similar effects in both backgrounds, supporting broad relevance to atherosclerosis [50]. Others differ between models, indicating that the pathway depends on lipid context, ApoE biology, diet, lesion stage, or vascular site. Such discordance should not be dismissed as experimental noise. Instead, it may reveal whether a mechanism is remnant-dependent, LDL-dependent, ApoE-dependent, diet-dependent, or stage-specific. For example, studies in genetically resistant C3H mice showed that high-fat diet-fed Ldlr−/− mice developed larger lesions than Apoe−/− mice despite lower systemic MCP-1 levels, suggesting that lipoprotein quality, including the abundance of small dense LDL particles, may outweigh some systemic inflammatory markers in determining lesion susceptibility [70,91]. These observations reinforce the broader concept that immune pathways in atherosclerosis cannot be interpreted independently of the lipoprotein environment in which they are studied.

2.2.4. Adult-Onset PCSK9-AAV Models

PCSK9-AAV models (AAV8, commonly 1–5 × 1011 vg/mouse, administered intravenously, typically by tail-vein injection) are especially useful for immunoinflammatory and immunometabolic studies because they allow adult-onset atherosclerosis to be induced in existing strains without germline disruption of Apoe or Ldlr. This feature is particularly valuable when investigators already have conditional knockout strains, Cre lines, reporter mice, aged cohorts, or disease-prone colonies. For example, PCSK9-AAV can be used to induce hypercholesterolemia in young and aged mice at defined time points, reducing the confounding effect of lifelong Apoe−/− or Ldlr−/− deficiency, in which atherosclerosis and aging progress simultaneously [142]. It can also be applied to complex genetic backgrounds where breeding into Apoe−/− or Ldlr−/− backgrounds would be costly and time consuming. Consequently, PCSK9-AAV models are attractive for studies of macrophage biology, immunometabolism, aging, trained immunity, clonal hematopoiesis, sterile inflammation, and systemic inflammatory disease. Although initially established primarily in male C57BL/6 mice, the AAV-PCSK9 model has been successfully applied in female mice and multiple mouse strains, where it consistently induces PCSK9 expression, LDL receptor degradation, hypercholesterolemia, and atherosclerotic lesion formation. Therefore, sex- and strain-dependent differences in lipid metabolism, immune responses, and plaque characteristics may influence disease severity and should be considered when designing experiments and interpreting translational relevance.

2.2.5. AAV-CRISPR Ldlr Models

The AAV-PCSK9 model becomes particularly relevant to immunometabolism when combined with a high-fat, high-cholesterol diet. Under these conditions, AAV-PCSK9-injected C57BL/6 mice develop atherosclerosis together with metabolic dysfunction, including insulin resistance, impaired glucose tolerance, pancreatic islet hyperplasia, and increased pro-inflammatory Ly6Chigh/med monocytes in adipose tissue [143]. These features overlap with those observed in HFD-C-fed Ldlr−/− mice and make the model useful for studying the intersection of hypercholesterolemia, obesity-associated inflammation, glucose dysregulation, adipose tissue immune remodeling, and atherosclerosis [143]. Importantly, these metabolic phenotypes cannot necessarily be explained solely by elevated plasma cholesterol. Diet composition and systemic metabolic stress may independently shape immune tone and lesion biology. Therefore, AAV-PCSK9 combined with HFD-C should be viewed as an integrated metabolic syndrome/atherosclerosis model rather than simply a faster version of Ldlr−/− mice.
AAV-CRISPR Ldlr models provide another flexible platform for immune and immunometabolic studies. By producing somatic disruption of hepatic Ldlr in adult mice, this approach enables disease induction in existing genetic backgrounds and avoids long breeding schemes [55]. It may be especially useful for studying genes with developmental effects, genes requiring multiple alleles, or candidate pathways identified through genetic screens. Somatic editing can also be combined with the disruption of other hepatic genes, as demonstrated by co-targeting Ldlr and ApoB to show that reducing hepatic ApoB production prevents hypercholesterolemia and atherosclerosis [144,145]. However, studies using AAV-CRISPR must account for vector exposure, editing efficiency, possible off-target effects, sex differences, and the distinction between adult-onset somatic deletion and lifelong germline deficiency.

2.2.6. Metabolic Syndrome and Immunometabolic Disease Models

Models of obesity, diabetes, aging, and metabolic syndrome also belong within the immunometabolic category. Atherosclerosis in humans rarely develops in isolation; instead, it commonly occurs in the setting of obesity, insulin resistance, diabetes, hypertension, chronic kidney disease, clonal hematopoiesis, or recurrent systemic inflammation [146,147,148,149,150,151]. Ldlr−/− mice fed high-fat (HFD) or HFD-C diets, Ldlr−/− mice crossed with ob/ob or db/db models, Apoe−/− mice exposed to diabetic or hypertensive stimuli, and PCSK9-AAV mice fed HFD-C can all be used to examine how metabolic stress reshapes atherogenesis [46]. These models are useful for studying monocyte production, adipose inflammation, glucose-lipid interactions, endothelial dysfunction, macrophage polarization, trained immunity, and systemic inflammatory priming. Their main limitation is interpretive complexity. When lesion size changes, the underlying mechanism may involve alterations in plasma lipids, body weight, glucose metabolism, insulin signaling, adipokines, blood pressure, the microbiome, immune activation, or vascular responsiveness. Consequently, these models are powerful for studying integrated disease biology but are less suitable for isolating individual immune pathways.

2.2.7. Bone Marrow Transplantation and Conditional Genetics

Bone marrow transplantation and conditional genetic approaches are central tools within this category. Historically, bone marrow chimeras in Apoe−/− or Ldlr−/− recipients were used to distinguish hematopoietic from non-hematopoietic contributions to lesion development [152,153]. More recently, cell-specific Cre-lox approaches, inducible gene deletion, fate mapping, and single-cell transcriptomic studies have increased the precision with which macrophages, dendritic cells, T cells, B cells, endothelial cells, smooth muscle cells, and other populations can be studied. For these approaches, model choice becomes especially important. If the question concerns macrophage-intrinsic immune regulation, Ldlr−/− or PCSK9-AAV models in a floxed background may be preferable because ApoE expression is preserved. If the goal is to compare findings directly with decades of published immune studies, Apoe−/− may be appropriate, but conclusions should be interpreted within the context of ApoE deficiency.

2.2.8. Macrophage Heterogeneity and Model Interpretation

Single-cell and fate-mapping studies are particularly relevant for immune-focused models because they demonstrate that macrophages do not represent a single inflammatory phenotype. Lesional macrophages include inflammatory macrophages enriched for Il1b, Ccl2, Ccl3, Ccl4, Cxcl2, Tnf, Cd14, and Nlrp3; IFN-inducible macrophages characterized by interferon-stimulated genes; TREM2hi foamy macrophages associated with lipid handling, lysosomal catabolism, and plaque remodeling; and resident-like macrophages that partially overlap with vascular or adventitial macrophage programs [8,90]. In addition, MacAIR (aortic intima resident macrophages) contribute to the earliest foam cell populations, whereas monocyte-derived macrophages progressively dominate as plaques progress [89,154,155]. Consequently, immune perturbation models should be interpreted according to the cellular process being investigated, including cytokine signaling, IFN activation, monocyte recruitment, resident macrophage biology, foam-cell formation, or regression-associated remodeling. This consideration is particularly important in studies using bone marrow chimeras, myeloid Cre drivers, macrophage depletion, or cytokine blockade, where the same intervention may affect distinct macrophage origins or activation states.

2.2.9. Summary of Immunoinflammatory and Immunometabolic Mechanism Models

The central message of this section is that immune studies require a model matched to the biological question being asked. Apoe−/− mice are robust and historically important but are immunologically confounded by the absence of ApoE. Ldlr−/− mice develop less spontaneous disease but often provide a cleaner background for studying immune mechanisms. PCSK9-AAV and AAV-CRISPR Ldlr models are flexible and particularly useful for complex genetic backgrounds, aging, and immunometabolism, although they introduce additional considerations related to viral delivery, somatic editing, sex-dependent effects, and adult-onset disease induction. Models of metabolic syndrome increase translational relevance but sacrifice mechanistic simplicity. Therefore, the optimal model depends on whether the objective is to isolate a cell-intrinsic immune mechanism, model systemic immunometabolic disease, test a candidate inflammatory pathway in established plaques, or reproduce a clinically relevant metabolic comorbidity.

3. Models of Plaque Complexity, Coronary Disease, and Clinical-Event-like Phenotypes (Table 1)

3.1. Why Advanced Plaque Models Are Needed

The third category includes models designed to capture advanced features of human atherosclerosis that are poorly reproduced by standard Apoe−/− and Ldlr−/− mice. This category is particularly important because the clinical consequences of human atherosclerosis arise not simply from the presence of plaques but from plaque growth, luminal obstruction, plaque rupture or erosion, thrombosis, myocardial infarction, stroke, and heart failure. Classical mouse models are highly useful for studying lesion formation in the aortic root, aortic arch, brachiocephalic artery, and en face aorta, but they rarely develop spontaneous plaque rupture, occlusive coronary thrombosis, myocardial infarction, or sudden death. As a result, a model that is excellent for measuring aortic lesion burden may be inadequate for studying plaque instability or coronary events.

3.2. Limitations of Classical Apoe−/− and Ldlr−/− Models

Apoe−/− and Ldlr−/− mice can develop complex aortic lesions characterized by lipid cores, macrophage accumulation, smooth muscle cell involvement, and fibrous cap-like structures, particularly after prolonged dietary challenge or additional genetic and environmental stressors [43,46,70,156]. However, spontaneous coronary artery occlusion and myocardial infarction remain uncommon. Lesions predominantly develop in the aortic root and large proximal arteries rather than in the coronary circulation. This anatomical mismatch represents a major translational limitation for studies of myocardial infarction, ischemia–reperfusion injury, plaque rupture, and cardioprotective therapies. Therefore, when the biological question concerns clinical events rather than lesion burden, more specialized models are required.

3.3. Apoe−/− Fbn1C1039G+/− Mice: Plaque Vulnerability and Rupture-Prone Disease

One approach is to modify vessel wall integrity to promote plaque vulnerability, as in Apoe−/− Fbn1C1039G+/− mice. Mutation of fibrillin-1 alters extracellular matrix structure, and in the setting of Apoe deficiency, promotes features of advanced plaque pathology that more closely resemble human vulnerable plaques, including larger necrotic cores, intraplaque neovascularization, hemorrhage, plaque rupture-like events, thrombosis, myocardial infarction, stroke, and in some reports, sudden death [157]. This model is particularly useful for studying plaque-stabilizing therapies, matrix remodeling, intraplaque hemorrhage, and mechanisms linking plaque structure to thrombotic complications. Its main limitation is that it deliberately introduces an extracellular matrix defect and therefore may not accurately reflect the natural progression of human atherosclerosis. It is best viewed as a model of plaque vulnerability and rupture-prone disease rather than a general model of atherogenesis.

3.4. Angiotensin II Models: Vascular Stress and Plaque Destabilization

Angiotensin II infusion in Apoe−/− mice represents another strategy to increase vascular inflammation, hypertension-related stress, aneurysm formation, and features of plaque destabilization [158,159,160]. This model is useful for studying interactions among blood pressure, vascular inflammation, aneurysm biology, medial remodeling, and plaque vulnerability. However, it is less suitable as a model of spontaneous human plaque rupture because AngII introduces a potent systemic stimulus that simultaneously affects blood pressure, inflammatory signaling, aneurysm formation, and vascular remodeling [159,161]. Consequently, AngII-based models are best reserved for questions that explicitly involve hemodynamic or inflammatory vascular stress, rather than as a generic method for generating more severe atherosclerosis.

3.5. SR-BI−/−/Apoe−/− Mice: Coronary Disease and MI-like Complications

SR-BI-based models are among the few murine models that reproducibly develop coronary atherosclerosis and myocardial infarction-like complications. SR-BI is a major HDL receptor that mediates the selective uptake of HDL cholesteryl esters by the liver and steroidogenic tissues. Loss of SR-BI disrupts HDL metabolism and reverse cholesterol transport. When SR-BI deficiency is combined with Apoe deficiency, mice develop severe dyslipidemia, abnormal lipoprotein particles, occlusive coronary artery lesions, spontaneous myocardial infarctions, cardiac dysfunction, electrocardiographic abnormalities, cardiac enlargement, reduced ejection fraction, and premature death. These features make SR-BI−/−/Apoe−/− mice unusually valuable for studying coronary atherosclerosis and MI-like complications in a murine system [162,163]. Their main limitation is disease severity. The phenotype develops rapidly and is accompanied by abnormal lipoprotein morphology and systemic pathology that differ substantially from typical human atherosclerosis. Thus, this model is highly useful for studying coronary-event biology but less suitable for investigating slow, multifactorial plaque progression.

3.6. SR-BI−/−/ApoeR61h/h Mice: Diet-Inducible Coronary Disease

SR-BI−/−/ApoeR61h/h mice were developed to provide greater control over the timing of coronary disease. ApoeR61h/h mice express reduced levels of a hypomorphic APOE variant. When combined with SR-BI deficiency, these mice remain relatively protected on chow diet but develop diet-induced hypercholesterolemia, occlusive coronary atherosclerosis, myocardial infarction, cardiac dysfunction, and premature death when challenged with an atherogenic diet [162,164]. This diet-inducible behavior is a major advantage because investigators can control disease onset, severity, duration, and potentially regression. The model is particularly useful for testing therapies directed at advanced coronary lesions, cardiac dysfunction, or diet-induced progression. However, as with other SR-BI models, the phenotype is strongly influenced by major disturbances in HDL metabolism and lipoprotein handling and should therefore be regarded as a specialized model of coronary disease rather than a universal model of atherosclerosis.

3.7. SR-BI−/−/Ldlr−/− Mice: Coronary Pathology with Preserved ApoE Expression

SR-BI−/−/Ldlr−/− mice provide another model of coronary disease, particularly under atherogenic diet conditions [165,166,167]. Because ApoE expression is preserved, this model may avoid some of the confounding effects associated with ApoE deficiency while still generating advanced coronary lesions and myocardial pathology in certain settings. It may therefore be particularly relevant for studies examining the interaction between LDLR deficiency and impaired HDL/SR-BI function. However, the combination of defective selective cholesterol uptake, elevated HDL, LDLR deficiency, and severe dyslipidemia creates a highly complex lipoprotein environment. As with SR-BI−/−/Apoe−/− mice, the model’s strength is its ability to generate coronary pathology, albeit at the cost of metabolic complexity.

3.8. Apoe−/−/Ldlr−/− Mice: Severe Hyperlipidemic Atherosclerosis

Apoe−/−/Ldlr−/− double knockout mice can develop more severe hyperlipidemia and more advanced lesions than either single knockout strain alone. Following prolonged high-fat, high-cholesterol feeding, these mice may also develop coronary involvement [57,168]. They are useful when a substantial lipid-driven disease burden is required and can serve as an intermediate model between classical lesion models and more aggressive coronary disease models. However, they do not consistently reproduce spontaneous plaque rupture or myocardial infarction to the extent seen in SR-BI-based models. Their principal value lies in modeling severe hyperlipidemic atherosclerosis rather than clinical cardiovascular events.

3.9. Modeling Myocardial Infarction and Ischemia–Reperfusion Injury

For studies of myocardial infarction and ischemia–reperfusion injury, model choice becomes especially important. Most experimental myocardial infarction (MI) studies rely on left anterior descending (LAD) coronary artery ligation or ischemia–reperfusion protocols in young, otherwise healthy mice, whereas human MI usually occurs in older individuals with coronary atherosclerosis, vascular dysfunction, metabolic comorbidities, and plaque rupture or erosion [169,170,171,172,173]. Standard Apoe−/− and Ldlr−/− mice generally fail to develop substantial coronary plaque burden and therefore may not adequately reproduce the vascular context in which human MI occurs. Specialized models with coronary lesions, including SR-BI-based models and potentially Apoe−/− Fbn1C1039G+/− mice, may provide more relevant platforms for investigating how atherosclerosis influences coronary function, infarct size, reperfusion injury, and cardioprotective therapies. Nevertheless, these models also introduce severe and, in some cases, nonphysiological disturbances in lipid metabolism. Experimental design must therefore balance clinical relevance against mechanistic interpretability.

4. Discussion and Future Directions

Mouse models have transformed atherosclerosis research, but the next phase of the field will require more precise model selection rather than simply generating more severe disease. Apoe−/− and Ldlr−/− mice will remain essential because of their robustness, genetic tractability, and extensive historical use. However, the growing availability of humanized lipoprotein models, adult-onset viral induction systems, somatic genome-editing approaches, metabolic syndrome models, and models of plaque complication now allows investigators to align model choice more closely to the biological question.
Studies focused on LDL retention, ApoB100 biology, or familial hypercholesterolemia may be better served by Ldlr−/−, Ldlr−/−/Apobec1−/−, ApoB100-only, or human ApoB transgenic models. Studies of remnant lipoproteins, dysbetalipoproteinemia, CETP biology, or responses to lipid-lowering therapies may benefit from APOE3-Leiden or APOE3-Leiden.CETP mice. Immune and inflammatory studies may require ApoE-intact backgrounds, such as Ldlr−/− or adult-onset PCSK9-AAV and AAV-CRISPR Ldlr approaches, particularly when the pathway of interest intersects with macrophage cholesterol handling or inflammatory regulation. Studies of plaque rupture, coronary disease, or myocardial infarction require specialized models beyond standard Apoe−/− and Ldlr−/− mice, including Apoe−/− Fbn1C1039G+/− and SR-BI-based models.
A second priority is cross-model validation. Many candidate genes and therapeutic interventions have been tested in only one model, most commonly Apoe−/− or Ldlr−/− mice. Whenever feasible, key mechanistic findings should be validated in a complementary system. For example, an inflammatory pathway identified in Apoe−/− mice could be tested in Ldlr−/− or PCSK9-AAV models, whereas lipid-modifying interventions may require validation in APOE3-Leiden.CETP mice when the goal is to model human-like lipoprotein-driven atherosclerosis [174] and evaluate lipid-lowering therapies [61]. Discordant results across models should not be viewed merely as failed replication; rather, they may reveal that a pathway is ApoE-dependent, LDL-dependent, remnant-dependent, diet-dependent, sex-dependent, or lesion-stage-specific.
Improved reporting and standardization will also be essential. Atherosclerosis studies are highly sensitive to strain background, sex, age, diet composition, cholesterol and cholate content, feeding duration, housing conditions, microbiome, plasma lipid distribution, lesion site, and quantification method. In viral and somatic editing models, investigators should additionally report vector serotype, dose, route, timing, PCSK9 expression or editing efficiency, hepatic LDLR protein abundance, and criteria for excluding unsuccessful delivery. These variables are not minor technical details; they define the biological context of the model.
Future studies should also move beyond total cholesterol as the main comparator between models. The atherogenicity of a model depends not only on cholesterol concentration but also on the type, size, number, and composition of ApoB-containing particles. Apoe−/−, Ldlr−/−, Ldlr−/−/Apobec1−/−, APOE3-Leiden, human ApoB, Lp(a), PCSK9-AAV, AAV-CRISPR, and SR-BI-based models each generate distinct lipoprotein landscapes. Lipoprotein fractionation, ApoB48/ApoB100 quantification, HDL measurements, triglycerides, remnant cholesterol, cholesterol efflux assays, CETP activity, and Lp(a) measurements should therefore be incorporated whenever relevant.
Adult-onset induction systems represent an important opportunity. PCSK9-AAV and AAV-CRISPR Ldlr approaches allow atherosclerosis to be induced in existing floxed, Cre-driver, reporter, aged, or disease-prone mice without years of breeding. These models are particularly useful for studying aging, clonal hematopoiesis, obesity, diabetes, chronic inflammation, and complex immune pathways. However, they are not interchangeable with germline Ldlr−/− mice. PCSK9-AAV produces supraphysiological PCSK9 expression, whereas AAV-CRISPR depends on editing efficiency, AAV tropism, sex, strain, and age at delivery. Future work should define the contexts in which these approaches faithfully reproduce classical models and those in which they introduce distinct biology.
Better modelling of immunometabolic disease is another major need. Human atherosclerosis usually develops in the setting of multiple interacting risk factors, including obesity, insulin resistance, aging, hypertension, chronic inflammation, and altered hematopoiesis. Combining atherosclerosis-prone backgrounds or adult-onset PCSK9-AAV induction with metabolic stress, aging, or inflammatory challenges may better capture residual inflammatory risk. These models are more clinically relevant but less mechanistically simple, and experiments should therefore be designed to distinguish the contributions of lipids, glucose metabolism, adipose inflammation, hematopoietic remodelling, and vascular inflammation.
The field should also continue improving models of advanced plaque complications. Standard Apoe−/− and Ldlr−/− mice are excellent for studying lesion initiation and progression, but they rarely reproduce spontaneous plaque rupture, coronary thrombosis, myocardial infarction, or sudden death. Models such as Apoe−/− Fbn1C1039G+/−, SR-BI−/−/Apoe−/−, SR-BI−/−/Ldlr−/−, and SR-BI−/−/ApoeR61h/h mice may be more appropriate for studying plaque vulnerability, coronary disease, and clinical-event-like phenotypes. These specialized models should complement, not replace, classical models.
Finally, future studies should place greater emphasis on plaque composition, spatial biology, and computational benchmarking against human disease. Lesion area remains informative, but plaque size alone does not capture necrotic-core formation, fibrous-cap structure, smooth-muscle-cell plasticity, macrophage states, calcification, intraplaque haemorrhage, efferocytosis, adventitial inflammation, or immune-cell organization. AI-assisted pathology can automate and standardize the segmentation and quantification of lesion burden, plaque distribution, and composition across large histological and three-dimensional imaging datasets [175,176]. Spatial transcriptomics, spatial proteomics, multiplex imaging, and lineage tracing can further connect molecular cell states with defined plaque compartments and reveal spatially restricted cellular interactions that are lost during tissue dissociation [177,178]. Integrating these approaches with single-cell datasets, lipoprotein profiles, immune phenotyping, histopathology, and therapeutic responses through machine-learning methods could enable multidimensional comparisons among mouse models and human disease, helping investigators identify which model best reproduces a specific biological or pathological feature. However, these tools will require representative training datasets, external validation across strains, sexes, diets, vascular sites, and imaging platforms, transparent reporting, and continued expert oversight to prevent technical or algorithmic differences from being misinterpreted as biological variation.

Sex as a Biological Variable in Model Selection and Interpretation

Sex substantially influences experimental atherosclerosis, although the magnitude and direction of these effects depend on the model, age, diet, vascular site, and analytical endpoint [179]. In young Apoe−/− mice, females often develop larger aortic-root lesions than males, whereas this difference diminishes with age [179,180]. In Ldlr−/− mice, females may also develop larger aortic-root lesions, while males can show greater disease when the entire aorta is assessed [179]. Sex-dependent phenotypes should therefore not be generalized across vascular sites or experimental designs.
The greater lesion burden observed in young females does not imply that estrogen is proatherogenic. Ovariectomy increases lesion formation in Apoe−/− mice, whereas 17β-estradiol replacement reduces atherosclerosis [181]. Similar protection is observed in Ldlr−/− mice, even without major changes in plasma cholesterol, supporting direct vascular and immunoregulatory effects of estrogen [182]. Thus, sex, gonadal status, hormone levels, and timing of hormone exposure should be considered distinct experimental variables [179].
Sex may also affect plaque composition independently of lesion size. Male mice can develop smaller but more inflammatory lesions, whereas females may exhibit greater plaque burden with distinct macrophage, inflammasome, and adaptive immune responses [179]. Genetic or pharmacological interventions may therefore produce different outcomes in males and females. Studies should assess lesion composition and inflammatory endpoints in addition to plaque area and plasma cholesterol and should initially analyze each sex separately.
AAV-PCSK9 models have been validated in female mice, but their efficiency can be sex dependent. At the same low vector dose, AAV8-mediated mutant PCSK9 expression can produce lower circulating PCSK9 and cholesterol levels in females than in males, although higher doses induce hypercholesterolemia in both sexes [183]. Vector performance also depends on the strategy used to reduce LDLR. In direct comparisons, AAV-hPCSK9 produced stronger atherosclerosis in females, whereas AAV-CRISPR-mediated Ldlr disruption was more effective in males [55].
These findings have practical implications for study design. AAV-based studies should report sex, age, vector serotype and dose, construct, delivery route, diet, circulating PCSK9, hepatic LDLR abundance, plasma lipoproteins, and lesion site. Pilot studies should confirm comparable induction of hypercholesterolemia in each sex, and therapeutic effects should be evaluated independently because sex-dependent differences in lesion burden, immune activation, hormone status, and vector efficiency may alter both treatment magnitude and mechanism [55,179,183].
In summary, the future of mouse atherosclerosis research will depend on using models more strategically. No model is universally superior; each has distinct strengths, limitations, and translational applications. The goal should be to match the model to the biological question, report the experimental context rigorously, and interpret findings within the disease axis that each model is designed to interrogate.

Author Contributions

Conceptualization, writing, review and editing, X.G., A.R.M., M.R.-G. and I.C. Supervision, I.C.; project administration, I.C. Funding acquisition, I.C. and M.R.-G. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the Gout, Hyperuricemia and Crystal-Associated Disease Network (GCAN Early Career Award), and the UAB Presidential Office Bridge Award (I.C.) and by the Spanish State Research Agency (AEI) under Grant PID2025-169543OB-I00 (M.R.G.).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Acknowledgments

The authors have reviewed and edited the output and take full responsibility for the content of this publication.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
AAVAdeno-associated virus
AngIIAngiotensin II
apo(a)Apolipoprotein(a)
ApoBApolipoprotein B
ApoB48Apolipoprotein B48
ApoB100Apolipoprotein B100
ApoEApolipoprotein E
CCL2C-C motif chemokine ligand 2
CCR2C-C motif chemokine receptor 2
CD4Cluster of differentiation 4
CETPCholesteryl ester transfer protein
CRISPRClustered regularly interspaced short palindromic repeats
CX3CL1C-X3-C motif chemokine ligand 1
CX3CR1C-X3-C motif chemokine receptor 1
HDLHigh-density lipoprotein
HFD-CHigh-fat, high-cholesterol diet
ICAM-1Intercellular adhesion molecule 1
IFNInterferon
LADLeft anterior descending
LDLLow-density lipoprotein
LDL-CLow-density lipoprotein cholesterol
LDLRLow-density lipoprotein receptor
Lp(a)Lipoprotein(a)
MacAIRAortic intima-resident macrophage(s)
MCP-1Monocyte chemoattractant protein 1
MIMyocardial infarction
PCSK9Proprotein convertase subtilisin/kexin type 9
RNA-seqRNA sequencing
scRNA-seqSingle-cell RNA sequencing
SR-BIScavenger receptor class B type I
Th1T helper type 1
TREM2Triggering receptor expressed on myeloid cells 2
VCAM-1Vascular cell adhesion molecule 1
VLDLVery-low-density lipoprotein

References

  1. Libby, P.; Buring, J.E.; Badimon, L.; Hansson, G.K.; Deanfield, J.; Bittencourt, M.S.; Tokgozoglu, L.; Lewis, E.F. Atherosclerosis. Nat. Rev. Dis. Prim. 2019, 5, 56. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  2. Verboova, L.; Nedoroscik, A.; Kiskova-Simkova, T.; Smirjakova, A.; Bohus, P.; Kollar, M.; Virag, M.; Mazarova, K.; Zavacka, M. Atherosclerosis: A Pathologist’s Perspective. J. Cardiovasc. Dev. Dis. 2026, 13, 85. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  3. Lusis, A.J. Atherosclerosis. Nature 2000, 407, 233–241. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  4. Araujo, G.; Valencia, L.M.; Martin-Ozimek, A.; Soto, Y.; Proctor, S.D. Atherosclerosis: From lipid-lowering and anti-inflammatory therapies to targeting arterial retention of ApoB-containing lipoproteins. Front. Immunol. 2025, 16, 1485801. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  5. Jarad, S.; Gill, G.; Amadi, P.; Gu, H.M.; Zhang, D.W. VSMCs in atherosclerosis: Implications on the role of inflammation and extracellular matrix remodelling. Pharmacol. Res. 2025, 218, 107833. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  6. Di Nubila, A.; Dilella, G.; Simone, R.; Barbieri, S.S. Vascular Extracellular Matrix in Atherosclerosis. Int. J. Mol. Sci. 2024, 25, 12017. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  7. Rayner, K.J. Cell Death in the Vessel Wall: The Good, the Bad, the Ugly. Arterioscler. Thromb. Vasc. Biol. 2017, 37, e75–e81. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  8. Zernecke, A.; Winkels, H.; Cochain, C.; Williams, J.W.; Wolf, D.; Soehnlein, O.; Robbins, C.S.; Monaco, C.; Park, I.; McNamara, C.A.; et al. Meta-Analysis of Leukocyte Diversity in Atherosclerotic Mouse Aortas. Circ. Res. 2020, 127, 402–426. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  9. Galkina, E.; Ley, K. Immune and inflammatory mechanisms of atherosclerosis. Annu Rev. Immunol. 2009, 27, 165–197. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  10. Wolf, D.; Ley, K. Immunity and Inflammation in Atherosclerosis. Circ. Res. 2019, 124, 315–327. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  11. Roy, P.; Orecchioni, M.; Ley, K. How the immune system shapes atherosclerosis: Roles of innate and adaptive immunity. Nat. Rev. Immunol. 2022, 22, 251–265. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  12. van der Vaart, J.I.; van Eenige, R.; Rensen, P.C.N.; Kooijman, S. Atherosclerosis: An overview of mouse models and a detailed methodology to quantify lesions in the aortic root. Vasc. Biol. 2024, 6, e230017. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  13. Scipione, C.A.; Cybulsky, M.I. Early atherogenesis: New insights from new approaches. Curr. Opin. Lipidol. 2022, 33, 271–276. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  14. Ginsberg, H.N.; Packard, C.J.; Chapman, M.J.; Boren, J.; Aguilar-Salinas, C.A.; Averna, M.; Ference, B.A.; Gaudet, D.; Hegele, R.A.; Kersten, S.; et al. Triglyceride-rich lipoproteins and their remnants: Metabolic insights, role in atherosclerotic cardiovascular disease, and emerging therapeutic strategies-a consensus statement from the European Atherosclerosis Society. Eur. Heart J. 2021, 42, 4791–4806. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  15. Lorey, M.B.; Oorni, K.; Kovanen, P.T. Modified Lipoproteins Induce Arterial Wall Inflammation During Atherogenesis. Front. Cardiovasc. Med. 2022, 9, 841545. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  16. Orekhov, A.N.; Bobryshev, Y.V.; Sobenin, I.A.; Melnichenko, A.A.; Chistiakov, D.A. Modified low density lipoprotein and lipoprotein-containing circulating immune complexes as diagnostic and prognostic biomarkers of atherosclerosis and type 1 diabetes macrovascular disease. Int. J. Mol. Sci. 2014, 15, 12807–12841. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  17. Gleissner, C.A.; Leitinger, N.; Ley, K. Effects of native and modified low-density lipoproteins on monocyte recruitment in atherosclerosis. Hypertension 2007, 50, 276–283. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  18. Oppi, S.; Luscher, T.F.; Stein, S. Mouse Models for Atherosclerosis Research-Which Is My Line? Front. Cardiovasc. Med. 2019, 6, 46. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  19. Alonso-Herranz, L.; Albarran-Juarez, J.; Bentzon, J.F. Mechanisms of fibrous cap formation in atherosclerosis. Front. Cardiovasc. Med. 2023, 10, 1254114. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  20. Newby, A.C.; Zaltsman, A.B. Fibrous cap formation or destruction--the critical importance of vascular smooth muscle cell proliferation, migration and matrix formation. Cardiovasc. Res. 1999, 41, 345–360. [Google Scholar] [CrossRef] [Scilit]
  21. Doran, A.C.; Meller, N.; McNamara, C.A. Role of smooth muscle cells in the initiation and early progression of atherosclerosis. Arterioscler. Thromb. Vasc. Biol. 2008, 28, 812–819. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  22. Yu, Y.; Cai, Y.; Yang, F.; Yang, Y.; Cui, Z.; Shi, D.; Bai, R. Vascular smooth muscle cell phenotypic switching in atherosclerosis. Heliyon 2024, 10, e37727. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  23. Bennett, M.R.; Sinha, S.; Owens, G.K. Vascular Smooth Muscle Cells in Atherosclerosis. Circ. Res. 2016, 118, 692–702. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  24. Miano, J.M.; Fisher, E.A.; Majesky, M.W. Fate and State of Vascular Smooth Muscle Cells in Atherosclerosis. Circulation 2021, 143, 2110–2116. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  25. Yan, F.; Sun, S.Y.; Wu, H. The “angiogenesis-plaque stability paradox” in atherosclerosis pathogenesis. Front. Cardiovasc. Med. 2025, 12, 1659006. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  26. Zeng, R.X.; Li, S.; Li, J.J. Cholesterol-Inflammation Fusion Hypothesis in Atherosclerosis: An Evolving Paradigm in Pathogenesis and Therapy. JACC Asia 2026, 6, 284–296. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  27. Bora, R.; Kilic, A.T.; Toprak, B. Atherosclerosis and Inflammation: Are the Rules of the Game Changing with Biological Therapies? J. Inflamm. Res. 2025, 18, 9811–9822. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  28. Raghu, H.; Lepus, C.M.; Wang, Q.; Wong, H.H.; Lingampalli, N.; Oliviero, F.; Punzi, L.; Giori, N.J.; Goodman, S.B.; Chu, C.R.; et al. CCL2/CCR2, but not CCL5/CCR5, mediates monocyte recruitment, inflammation and cartilage destruction in osteoarthritis. Ann. Rheum. Dis. 2017, 76, 914–922. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  29. Becker, F.; Holthoff, C.; Anthoni, C.; Rijcken, E.; Alexander, J.S.; Gavins, F.N.; Spiegel, H.U.; Senninger, N.; Vowinkel, T. Downregulation of CX(3)CR1 ameliorates experimental colitis: Evidence for CX(3)CL1-CX(3)CR1-mediated immune cell recruitment. Int. J. Colorectal Dis. 2017, 32, 315–324. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  30. Pickett, J.R.; Wu, Y.; Zacchi, L.F.; Ta, H.T. Targeting endothelial vascular cell adhesion molecule-1 in atherosclerosis: Drug discovery and development of vascular cell adhesion molecule-1-directed novel therapeutics. Cardiovasc. Res. 2023, 119, 2278–2293. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  31. Tabas, I.; Bornfeldt, K.E. Macrophage Phenotype and Function in Different Stages of Atherosclerosis. Circ. Res. 2016, 118, 653–667. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  32. Moore, K.J.; Sheedy, F.J.; Fisher, E.A. Macrophages in atherosclerosis: A dynamic balance. Nat. Rev. Immunol. 2013, 13, 709–721. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  33. Chen, J.; Xiang, X.; Nie, L.; Guo, X.; Zhang, F.; Wen, C.; Xia, Y.; Mao, L. The emerging role of Th1 cells in atherosclerosis and its implications for therapy. Front. Immunol. 2022, 13, 1079668. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  34. Pastrana, J.L.; Sha, X.; Virtue, A.; Mai, J.; Cueto, R.; Lee, I.A.; Wang, H.; Yang, X.F. Regulatory T cells and Atherosclerosis. J. Clin. Exp. Cardiol. 2012, 2012, 2. [Google Scholar] [CrossRef] [PubMed]
  35. Saigusa, R.; Winkels, H.; Ley, K. T cell subsets and functions in atherosclerosis. Nat. Rev. Cardiol. 2020, 17, 387–401. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  36. Reijnders, E.; van der Laarse, A.; Jukema, J.W.; Cobbaert, C.M. High residual cardiovascular risk after lipid-lowering: Prime time for Predictive, Preventive, Personalized, Participatory, and Psycho-cognitive medicine. Front. Cardiovasc. Med. 2023, 10, 1264319. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  37. Riaz, H.; Khan, S.U.; Lateef, N.; Talluri, S.; Khan, M.S.; Desai, M.Y. Residual inflammatory risk after contemporary lipid lowering therapy. Eur. Heart J. Qual. Care Clin. Outcomes 2020, 6, 105–111. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  38. Soehnlein, O.; Libby, P. Targeting inflammation in atherosclerosis—From experimental insights to the clinic. Nat. Rev. Drug Discov. 2021, 20, 589–610. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  39. Libby, P. Targeting Inflammatory Pathways in Cardiovascular Disease: The Inflammasome, Interleukin-1, Interleukin-6 and Beyond. Cells 2021, 10, 951. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  40. Certo, M.; Rahimzadeh, M.; Mauro, C. Immunometabolism in atherosclerosis: A new understanding of an old disease. Trends Biochem. Sci. 2024, 49, 791–803. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  41. Hu, T.; Liu, C.H.; Lei, M.; Zeng, Q.; Li, L.; Tang, H.; Zhang, N. Metabolic regulation of the immune system in health and diseases: Mechanisms and interventions. Signal Transduct. Target Ther. 2024, 9, 268. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  42. Lee, Y.T.; Lin, H.Y.; Chan, Y.W.; Li, K.H.; To, O.T.; Yan, B.P.; Liu, T.; Li, G.; Wong, W.T.; Keung, W.; et al. Mouse models of atherosclerosis: A historical perspective and recent advances. Lipids Health Dis. 2017, 16, 12. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  43. Getz, G.S.; Reardon, C.A. Animal models of atherosclerosis. Arterioscler. Thromb. Vasc. Biol. 2012, 32, 1104–1115. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  44. von Scheidt, M.; Zhao, Y.; Kurt, Z.; Pan, C.; Zeng, L.; Yang, X.; Schunkert, H.; Lusis, A.J. Applications and Limitations of Mouse Models for Understanding Human Atherosclerosis. Cell Metab. 2017, 25, 248–261. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  45. Breslow, J.L. Mouse models of atherosclerosis. Science 1996, 272, 685–688. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  46. Ishibashi, S.; Brown, M.S.; Goldstein, J.L.; Gerard, R.D.; Hammer, R.E.; Herz, J. Hypercholesterolemia in low density lipoprotein receptor knockout mice and its reversal by adenovirus-mediated gene delivery. J. Clin. Investig. 1993, 92, 883–893. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  47. Plump, A.S.; Smith, J.D.; Hayek, T.; Aalto-Setala, K.; Walsh, A.; Verstuyft, J.G.; Rubin, E.M.; Breslow, J.L. Severe hypercholesterolemia and atherosclerosis in apolipoprotein E-deficient mice created by homologous recombination in ES cells. Cell 1992, 71, 343–353. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  48. Basu, D.; Bornfeldt, K.E. Hypertriglyceridemia and Atherosclerosis: Using Human Research to Guide Mechanistic Studies in Animal Models. Front. Endocrinol. 2020, 11, 504. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  49. Veniant, M.M.; Beigneux, A.P.; Bensadoun, A.; Fong, L.G.; Young, S.G. Lipoprotein size and susceptibility to atherosclerosis--insights from genetically modified mouse models. Curr. Drug Targets 2008, 9, 174–189. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  50. Getz, G.S.; Reardon, C.A. Do the Apoe-/- and Ldlr-/- Mice Yield the Same Insight on Atherogenesis? Arterioscler. Thromb. Vasc. Biol. 2016, 36, 1734–1741. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  51. Ramirez, C.; Sierra, S.; Tercero, I.; Vazquez, J.A.; Pineda, A.; Manrique, T.; Burgos, J.S. ApoB100/LDLR-/- hypercholesterolaemic mice as a model for mild cognitive impairment and neuronal damage. PLoS ONE 2011, 6, e22712. [Google Scholar] [CrossRef] [Scilit] [PubMed][Green Version]
  52. Steinfeld, K.; Beyer, D.; Muhlfeld, C.; Mietens, A.; Eichner, G.; Altinkilic, B.; Kampschulte, M.; Jiang, Q.; Krombach, G.A.; Linn, T.; et al. Low testosterone in ApoE/LDL receptor double-knockout mice is associated with rarefied testicular capillaries together with fewer and smaller Leydig cells. Sci. Rep. 2018, 8, 5424. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  53. Powell-Braxton, L.; Veniant, M.; Latvala, R.D.; Hirano, K.I.; Won, W.B.; Ross, J.; Dybdal, N.; Zlot, C.H.; Young, S.G.; Davidson, N.O. A mouse model of human familial hypercholesterolemia: Markedly elevated low density lipoprotein cholesterol levels and severe atherosclerosis on a low-fat chow diet. Nat. Med. 1998, 4, 934–938. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  54. Poznyak, A.V.; Silaeva, Y.Y.; Orekhov, A.N.; Deykin, A.V. Animal models of human atherosclerosis: Current progress. Braz. J. Med. Biol. Res. 2020, 53, e9557. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  55. Jarrett, K.E.; Lee, C.; De Giorgi, M.; Hurley, A.; Gillard, B.K.; Doerfler, A.M.; Li, A.; Pownall, H.J.; Bao, G.; Lagor, W.R. Somatic Editing of Ldlr With Adeno-Associated Viral-CRISPR Is an Efficient Tool for Atherosclerosis Research. Arterioscler. Thromb. Vasc. Biol. 2018, 38, 1997–2006. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  56. Noonan, J.; Cardoso, L.; Bobik, A.; Peter, K. Atherosclerotic Plaque Instability and Rupture: Recommended Mouse Models to Empower Clinically Relevant Discoveries, Diagnostics, and Therapeutics. Arterioscler. Thromb. Vasc. Biol. 2025, 45, 1707–1714. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  57. Golforoush, P.; Yellon, D.M.; Davidson, S.M. Mouse models of atherosclerosis and their suitability for the study of myocardial infarction. Basic Res. Cardiol. 2020, 115, 73. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  58. Braun, A.; Rigotti, A.; Trigatti, B.L. Myocardial infarction following atherosclerosis in murine models. Curr. Drug Targets 2008, 9, 217–223. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  59. Chen, H.; Wan, Q.; Yang, J.; Rao, H.; Xu, C.; Xu, P.; Yang, X.; Wang, H.; Feng, W.; Wang, L.; et al. Novel Mouse Model of Coronary Atherosclerosis with Myocardial Infarction: Insights into Human CAD. Circ. Res. 2025, 137, e106–e123. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  60. Grass, D.S.; Saini, U.; Felkner, R.H.; Wallace, R.E.; Lago, W.J.; Young, S.G.; Swanson, M.E. Transgenic mice expressing both human apolipoprotein B and human CETP have a lipoprotein cholesterol distribution similar to that of normolipidemic humans. J. Lipid Res. 1995, 36, 1082–1091. [Google Scholar] [CrossRef] [Scilit]
  61. Zadelaar, S.; Kleemann, R.; Verschuren, L.; de Vries-Van der Weij, J.; van der Hoorn, J.; Princen, H.M.; Kooistra, T. Mouse models for atherosclerosis and pharmaceutical modifiers. Arterioscler. Thromb. Vasc. Biol. 2007, 27, 1706–1721. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  62. de Vries-van der Weij, J.; Zadelaar, S.; Toet, K.; Havekes, L.M.; Kooistra, T.; Rensen, P.C. Human CETP aggravates atherosclerosis by increasing VLDL-cholesterol rather than by decreasing HDL-cholesterol in APOE*3-Leiden mice. Atherosclerosis 2009, 206, 153–158. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  63. Bjorklund, M.M.; Hollensen, A.K.; Hagensen, M.K.; Dagnaes-Hansen, F.; Christoffersen, C.; Mikkelsen, J.G.; Bentzon, J.F. Induction of atherosclerosis in mice and hamsters without germline genetic engineering. Circ. Res. 2014, 114, 1684–1689. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  64. Gordon, S.M.; Li, H.; Zhu, X.; Shah, A.S.; Lu, L.J.; Davidson, W.S. A comparison of the mouse and human lipoproteome: Suitability of the mouse model for studies of human lipoproteins. J. Proteome Res. 2015, 14, 2686–2695. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  65. Kotsovilis, S.; Salagianni, M.; Varela, A.; Davos, C.H.; Galani, I.E.; Andreakos, E. Comprehensive Analysis of 1-Year-Old Female Apolipoprotein E-Deficient Mice Reveals Advanced Atherosclerosis with Vulnerable Plaque Characteristics. Int. J. Mol. Sci. 2024, 25, 1355. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  66. Liu, C.; Liu, J.; Wang, Y.Y.; Xu, S.F.; Yu, L.M. APOE Lipoprotein Particles: Pathophysiology, Therapy, and the Crosstalk in Alzheimer’s Disease and Cardiovascular Disease. Mol. Neurobiol. 2025, 63, 325. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  67. Getz, G.S.; Reardon, C.A. Apoprotein E and Reverse Cholesterol Transport. Int. J. Mol. Sci. 2018, 19, 3479. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  68. Stanford, K.I.; Bishop, J.R.; Foley, E.M.; Gonzales, J.C.; Niesman, I.R.; Witztum, J.L.; Esko, J.D. Syndecan-1 is the primary heparan sulfate proteoglycan mediating hepatic clearance of triglyceride-rich lipoproteins in mice. J. Clin. Investig. 2009, 119, 3236–3245. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  69. von Holt, K.; Lebrun, S.; Stinn, W.; Conroy, L.; Wallerath, T.; Schleef, R. Progression of atherosclerosis in the Apo E-/- model: 12-month exposure to cigarette mainstream smoke combined with high-cholesterol/fat diet. Atherosclerosis 2009, 205, 135–143. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  70. Torikai, H.; Chen, M.H.; Jin, L.; He, J.; Angle, J.F.; Shi, W. Atherogenesis in Apoe-/- and Ldlr-/- Mice with a Genetically Resistant Background. Cells 2023, 12, 1255. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  71. Getz, G.S.; Reardon, C.A. ApoE knockout and knockin mice: The history of their contribution to the understanding of atherogenesis. J. Lipid Res. 2016, 57, 758–766. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  72. Vasquez, E.C.; Peotta, V.A.; Gava, A.L.; Pereira, T.M.; Meyrelles, S.S. Cardiac and vascular phenotypes in the apolipoprotein E-deficient mouse. J. Biomed. Sci. 2012, 19, 22. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  73. Murphy, A.J.; Akhtari, M.; Tolani, S.; Pagler, T.; Bijl, N.; Kuo, C.L.; Wang, M.; Sanson, M.; Abramowicz, S.; Welch, C.; et al. ApoE regulates hematopoietic stem cell proliferation, monocytosis, and monocyte accumulation in atherosclerotic lesions in mice. J. Clin. Investig. 2011, 121, 4138–4149. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  74. Wenner, C.; Lorkowski, S.; Engel, T.; Cullen, P. Apolipoprotein E in macrophages and hepatocytes is eegraded via the proteasomal pathway. Biochem. Biophys. Res. Commun. 2001, 282, 608–614. [Google Scholar] [CrossRef] [Scilit] [PubMed][Green Version]
  75. Phu, T.A.; Vu, N.K.; Ng, M.; Gao, A.S.; Stoolman, J.S.; Chandel, N.S.; Raffai, R.L. ApoE enhances mitochondrial metabolism via microRNA-142a/146a-regulated circuits that suppress hematopoiesis and inflammation in hyperlipidemia. Cell Rep. 2023, 42, 113206. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  76. Baitsch, D.; Bock, H.H.; Engel, T.; Telgmann, R.; Muller-Tidow, C.; Varga, G.; Bot, M.; Herz, J.; Robenek, H.; von Eckardstein, A.; et al. Apolipoprotein E induces antiinflammatory phenotype in macrophages. Arterioscler. Thromb. Vasc. Biol. 2011, 31, 1160–1168. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  77. Zhao, N.; Liu, C.C.; Qiao, W.; Bu, G. Apolipoprotein E, Receptors, and Modulation of Alzheimer’s Disease. Biol. Psychiatry 2018, 83, 347–357. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  78. Dove, D.E.; Linton, M.F.; Fazio, S. ApoE-mediated cholesterol efflux from macrophages: Separation of autocrine and paracrine effects. Am. J. Physiol. Cell Physiol. 2005, 288, C586–C592. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  79. Lin, C.Y.; Duan, H.; Mazzone, T. Apolipoprotein E-dependent cholesterol efflux from macrophages: Kinetic study and divergent mechanisms for endogenous versus exogenous apolipoprotein E. J. Lipid Res. 1999, 40, 1618–1627. [Google Scholar] [CrossRef] [Scilit]
  80. Liu, B.; Fang, L.; Mo, P.; Chen, C.; Ji, Y.; Pang, L.; Chen, H.; Deng, Y.; Ou, W.; Liu, S.M. Apoe-knockout induces strong vascular oxidative stress and significant changes in the gene expression profile related to the pathways implicated in redox, inflammation, and endothelial function. Cell. Signal. 2023, 108, 110696. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  81. Pauli, J.; Reisenauer, T.; Winski, G.; Sachs, N.; Chernogubova, E.; Freytag, H.; Otto, C.; Reeps, C.; Eckstein, H.H.; Scholz, C.J.; et al. Apolipoprotein E (ApoE) Rescues the Contractile Smooth Muscle Cell Phenotype in Popliteal Artery Aneurysm Disease. Biomolecules 2023, 13, 1074. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  82. Yue, L.; Bian, J.T.; Grizelj, I.; Cavka, A.; Phillips, S.A.; Makino, A.; Mazzone, T. Apolipoprotein E enhances endothelial-NO production by modulating caveolin 1 interaction with endothelial NO synthase. Hypertension 2012, 60, 1040–1046. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  83. Riddell, D.R.; Graham, A.; Owen, J.S. Apolipoprotein E inhibits platelet aggregation through the L-arginine:Nitric oxide pathway. Implications for vascular disease. J. Biol. Chem. 1997, 272, 89–95. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  84. Wouters, K.; Shiri-Sverdlov, R.; van Gorp, P.J.; van Bilsen, M.; Hofker, M.H. Understanding hyperlipidemia and atherosclerosis: Lessons from genetically modified apoe and ldlr mice. Clin. Chem. Lab. Med. 2005, 43, 470–479. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  85. Meir, K.S.; Leitersdorf, E. Atherosclerosis in the apolipoprotein-E-deficient mouse: A decade of progress. Arterioscler. Thromb. Vasc. Biol. 2004, 24, 1006–1014. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  86. Centa, M.; Prokopec, K.E.; Garimella, M.G.; Habir, K.; Hofste, L.; Stark, J.M.; Dahdah, A.; Tibbitt, C.A.; Polyzos, K.A.; Gistera, A.; et al. Acute Loss of Apolipoprotein E Triggers an Autoimmune Response That Accelerates Atherosclerosis. Arterioscler. Thromb. Vasc. Biol. 2018, 38, e145–e158. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  87. Twisk, J.; Gillian-Daniel, D.L.; Tebon, A.; Wang, L.; Barrett, P.H.; Attie, A.D. The role of the LDL receptor in apolipoprotein B secretion. J. Clin. Investig. 2000, 105, 521–532. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  88. Getz, G.S.; Reardon, C.A. Diet and murine atherosclerosis. Arterioscler. Thromb. Vasc. Biol. 2006, 26, 242–249. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  89. Winkels, H.; Ehinger, E.; Vassallo, M.; Buscher, K.; Dinh, H.Q.; Kobiyama, K.; Hamers, A.A.J.; Cochain, C.; Vafadarnejad, E.; Saliba, A.E.; et al. Atlas of the Immune Cell Repertoire in Mouse Atherosclerosis Defined by Single-Cell RNA-Sequencing and Mass Cytometry. Circ. Res. 2018, 122, 1675–1688. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  90. Cochain, C.; Vafadarnejad, E.; Arampatzi, P.; Pelisek, J.; Winkels, H.; Ley, K.; Wolf, D.; Saliba, A.E.; Zernecke, A. Single-Cell RNA-Seq Reveals the Transcriptional Landscape and Heterogeneity of Aortic Macrophages in Murine Atherosclerosis. Circ. Res. 2018, 122, 1661–1674. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  91. Shi, W.; Wang, N.J.; Shih, D.M.; Sun, V.Z.; Wang, X.; Lusis, A.J. Determinants of atherosclerosis susceptibility in the C3H and C57BL/6 mouse model: Evidence for involvement of endothelial cells but not blood cells or cholesterol metabolism. Circ. Res. 2000, 86, 1078–1084. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  92. Wang, S.S.; Shi, W.; Wang, X.; Velky, L.; Greenlee, S.; Wang, M.T.; Drake, T.A.; Lusis, A.J. Mapping, genetic isolation, and characterization of genetic loci that determine resistance to atherosclerosis in C3H mice. Arterioscler. Thromb. Vasc. Biol. 2007, 27, 2671–2676. [Google Scholar] [CrossRef] [Scilit] [PubMed][Green Version]
  93. Su, Z.; Li, Y.; James, J.C.; McDuffie, M.; Matsumoto, A.H.; Helm, G.A.; Weber, J.L.; Lusis, A.J.; Shi, W. Quantitative trait locus analysis of atherosclerosis in an intercross between C57BL/6 and C3H mice carrying the mutant apolipoprotein E gene. Genetics 2006, 172, 1799–1807. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  94. Dansky, H.M.; Charlton, S.A.; Sikes, J.L.; Heath, S.C.; Simantov, R.; Levin, L.F.; Shu, P.; Moore, K.J.; Breslow, J.L.; Smith, J.D. Genetic background determines the extent of atherosclerosis in ApoE-deficient mice. Arterioscler. Thromb. Vasc. Biol. 1999, 19, 1960–1968. [Google Scholar] [CrossRef] [Scilit] [PubMed][Green Version]
  95. Tian, J.; Pei, H.; James, J.C.; Li, Y.; Matsumoto, A.H.; Helm, G.A.; Shi, W. Circulating adhesion molecules in apoE-deficient mouse strains with different atherosclerosis susceptibility. Biochem. Biophys. Res. Commun. 2005, 329, 1102–1107. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  96. Maeda, N.; Johnson, L.; Kim, S.; Hagaman, J.; Friedman, M.; Reddick, R. Anatomical differences and atherosclerosis in apolipoprotein E-deficient mice with 129/SvEv and C57BL/6 genetic backgrounds. Atherosclerosis 2007, 195, 75–82. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  97. Kayashima, Y.; Tomita, H.; Zhilicheva, S.; Kim, S.; Kim, H.S.; Bennett, B.J.; Maeda, N. Quantitative trait loci affecting atherosclerosis at the aortic root identified in an intercross between DBA2J and 129S6 apolipoprotein E-null mice. PLoS ONE 2014, 9, e88274. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  98. Teupser, D.; Persky, A.D.; Breslow, J.L. Induction of atherosclerosis by low-fat, semisynthetic diets in LDL receptor-deficient C57BL/6J and FVB/NJ mice: Comparison of lesions of the aortic root, brachiocephalic artery, and whole aorta (en face measurement). Arterioscler. Thromb. Vasc. Biol. 2003, 23, 1907–1913. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  99. Yang, J.; Wong, L.Y.; Tian, X.Y.; Wei, R.; Lai, W.H.; Au, K.W.; Luo, Z.; Ward, C.; Ho, W.I.; Ibanez, D.P.; et al. A Familial Hypercholesterolemia Human Liver Chimeric Mouse Model Using Induced Pluripotent Stem Cell-derived Hepatocytes. J. Vis. Exp. 2018, 139, e57556. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  100. He, K.; Wang, J.; Shi, H.; Yu, Q.; Zhang, X.; Guo, M.; Sun, H.; Lin, X.; Wu, Y.; Wang, L.; et al. An interspecies study of lipid profiles and atherosclerosis in familial hypercholesterolemia animal models with low-density lipoprotein receptor deficiency. Am. J. Transl. Res. 2019, 11, 3116–3127. [Google Scholar] [PubMed]
  101. Sato, A.; Tsukiyama, T.; Komeno, M.; Iwatani, C.; Tsuchiya, H.; Kawamoto, I.; Murase, M.; Nakagawa, T.; Itagaki, I.; Seita, Y.; et al. Generation of a familial hypercholesterolemia model in non-human primate. Sci. Rep. 2023, 13, 15649. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  102. Srivastava, R.A.; Tang, J.; Baumann, D.; Schonfeld, G. Hormonal and nutritional stimuli modulate apolipoprotein B mRNA editing in mouse liver. Biochem. Biophys. Res. Commun. 1992, 188, 135–141. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  103. Oka, K.; Kobayashi, K.; Sullivan, M.; Martinez, J.; Teng, B.B.; Ishimura-Oka, K.; Chan, L. Tissue-specific inhibition of apolipoprotein B mRNA editing in the liver by adenovirus-mediated transfer of a dominant negative mutant APOBEC-1 leads to increased low density lipoprotein in mice. J. Biol. Chem. 1997, 272, 1456–1460. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  104. Johnson, L.A.; Altenburg, M.K.; Walzem, R.L.; Scanga, L.T.; Maeda, N. Absence of hyperlipidemia in LDL receptor-deficient mice having apolipoprotein B100 without the putative receptor-binding sequences. Arterioscler. Thromb. Vasc. Biol. 2008, 28, 1745–1752. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  105. Hirano, K.; Young, S.G.; Farese, R.V., Jr.; Ng, J.; Sande, E.; Warburton, C.; Powell-Braxton, L.M.; Davidson, N.O. Targeted disruption of the mouse apobec-1 gene abolishes apolipoprotein B mRNA editing and eliminates apolipoprotein B48. J. Biol. Chem. 1996, 271, 9887–9890. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  106. Veniant, M.M.; Withycombe, S.; Young, S.G. Lipoprotein size and atherosclerosis susceptibility in Apoe-/- and Ldlr-/- mice. Arterioscler. Thromb. Vasc. Biol. 2001, 21, 1567–1570. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  107. Toth, M.E.; Dukay, B.; Hoyk, Z.; Santha, M. Cerebrovascular Changes and Neurodegeneration Related to Hyperlipidemia: Characteristics of the Human ApoB-100 Transgenic Mice. Curr. Pharm. Des. 2020, 26, 1486–1494. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  108. Callow, M.J.; Stoltzfus, L.J.; Lawn, R.M.; Rubin, E.M. Expression of human apolipoprotein B and assembly of lipoprotein(a) in transgenic mice. Proc. Natl. Acad. Sci. USA 1994, 91, 2130–2134. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  109. Callow, M.J.; Verstuyft, J.; Tangirala, R.; Palinski, W.; Rubin, E.M. Atherogenesis in transgenic mice with human apolipoprotein B and lipoprotein (a). J. Clin. Investig. 1995, 96, 1639–1646. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  110. Young, S.G.; Farese, R.V., Jr.; Pierotti, V.R.; Taylor, S.; Grass, D.S.; Linton, M.F. Transgenic mice expressing human apoB100 and apoB48. Curr. Opin. Lipidol. 1994, 5, 94–101. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  111. van den Maagdenberg, A.M.; Hofker, M.H.; Krimpenfort, P.J.; de Bruijn, I.; van Vlijmen, B.; van der Boom, H.; Havekes, L.M.; Frants, R.R. Transgenic mice carrying the apolipoprotein E3-Leiden gene exhibit hyperlipoproteinemia. J. Biol. Chem. 1993, 268, 10540–10545. [Google Scholar] [CrossRef] [Scilit]
  112. Johansen, M.O.; Moreno-Vedia, J.; Balling, M.; Davey Smith, G.; Nordestgaard, B.G. Triglyceride content increases while cholesterol content decreases in HDL and LDL+IDL fractions following normal meals: The Copenhagen General Population Study of 25,656 individuals. Atherosclerosis 2023, 383, 117316. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  113. Chiu, S.; Williams, P.T.; Krauss, R.M. Effects of a very high saturated fat diet on LDL particles in adults with atherogenic dyslipidemia: A randomized controlled trial. PLoS ONE 2017, 12, e0170664. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  114. Lutgens, E.; Daemen, M.; Kockx, M.; Doevendans, P.; Hofker, M.; Havekes, L.; Wellens, H.; de Muinck, E.D. Atherosclerosis in APOE*3-Leiden transgenic mice: From proliferative to atheromatous stage. Circulation 1999, 99, 276–283. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  115. Leppanen, P.; Luoma, J.S.; Hofker, M.H.; Havekes, L.M.; Yla-Herttuala, S. Characterization of atherosclerotic lesions in apo E3-leiden transgenic mice. Atherosclerosis 1998, 136, 147–152. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  116. Westerterp, M.; van der Hoogt, C.C.; de Haan, W.; Offerman, E.H.; Dallinga-Thie, G.M.; Jukema, J.W.; Havekes, L.M.; Rensen, P.C. Cholesteryl ester transfer protein decreases high-density lipoprotein and severely aggravates atherosclerosis in APOE*3-Leiden mice. Arterioscler. Thromb. Vasc. Biol. 2006, 26, 2552–2559. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  117. Paalvast, Y.; Gerding, A.; Wang, Y.; Bloks, V.W.; van Dijk, T.H.; Havinga, R.; Willems van Dijk, K.; Rensen, P.C.N.; Bakker, B.M.; Kuivenhoven, J.A.; et al. Male apoE*3-Leiden.CETP mice on high-fat high-cholesterol diet exhibit a biphasic dyslipidemic response, mimicking the changes in plasma lipids observed through life in men. Physiol. Rep. 2017, 5, e13376. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  118. Zhou, E.; Li, Z.; Nakashima, H.; Liu, C.; Ying, Z.; Foks, A.C.; Berbee, J.F.P.; van Dijk, K.W.; Rensen, P.C.N.; Wang, Y. Hepatic Scavenger Receptor Class B Type 1 Knockdown Reduces Atherosclerosis and Enhances the Antiatherosclerotic Effect of Brown Fat Activation in APOE*3-Leiden. CETP Mice. Arterioscler. Thromb. Vasc. Biol. 2021, 41, 1474–1486. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  119. Bijland, S.; van den Berg, S.A.; Voshol, P.J.; van den Hoek, A.M.; Princen, H.M.; Havekes, L.M.; Rensen, P.C.; Willems van Dijk, K. CETP does not affect triglyceride production or clearance in APOE*3-Leiden mice. J. Lipid Res. 2010, 51, 97–102. [Google Scholar] [CrossRef] [Scilit] [PubMed][Green Version]
  120. Somanathan, S.; Jacobs, F.; Wang, Q.; Hanlon, A.L.; Wilson, J.M.; Rader, D.J. AAV vectors expressing LDLR gain-of-function variants demonstrate increased efficacy in mouse models of familial hypercholesterolemia. Circ. Res. 2014, 115, 591–599. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  121. Goettsch, C.; Hutcheson, J.D.; Hagita, S.; Rogers, M.A.; Creager, M.D.; Pham, T.; Choi, J.; Mlynarchik, A.K.; Pieper, B.; Kjolby, M.; et al. A single injection of gain-of-function mutant PCSK9 adeno-associated virus vector induces cardiovascular calcification in mice with no genetic modification. Atherosclerosis 2016, 251, 109–118. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  122. Kumar, S.; Kang, D.W.; Rezvan, A.; Jo, H. Accelerated atherosclerosis development in C57Bl6 mice by overexpressing AAV-mediated PCSK9 and partial carotid ligation. Lab. Investig. 2017, 97, 935–945. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  123. Dutka, M.; Zimmer, K.; Cwiertnia, M.; Ilczak, T.; Bobinski, R. The role of PCSK9 in heart failure and other cardiovascular diseases-mechanisms of action beyond its effect on LDL cholesterol. Heart Fail Rev. 2024, 29, 917–937. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  124. Kosenko, T.; Golder, M.; Leblond, G.; Weng, W.; Lagace, T.A. Low density lipoprotein binds to proprotein convertase subtilisin/kexin type-9 (PCSK9) in human plasma and inhibits PCSK9-mediated low density lipoprotein receptor degradation. J. Biol. Chem. 2013, 288, 8279–8288. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  125. Yurtseven, E.; Ural, D.; Baysal, K.; Tokgozoglu, L. An Update on the Role of PCSK9 in Atherosclerosis. J. Atheroscler. Thromb. 2020, 27, 909–918. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  126. Ding, Q.; Strong, A.; Patel, K.M.; Ng, S.L.; Gosis, B.S.; Regan, S.N.; Cowan, C.A.; Rader, D.J.; Musunuru, K. Permanent alteration of PCSK9 with in vivo CRISPR-Cas9 genome editing. Circ. Res. 2014, 115, 488–492. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  127. Chadwick, A.C.; Musunuru, K. CRISPR-Cas9 Genome Editing for Treatment of Atherogenic Dyslipidemia. Arterioscler. Thromb. Vasc. Biol. 2018, 38, 12–18. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  128. O’Hare, E.A.; Wang, X.; Montasser, M.E.; Chang, Y.P.; Mitchell, B.D.; Zaghloul, N.A. Disruption of ldlr causes increased LDL-c and vascular lipid accumulation in a zebrafish model of hypercholesterolemia. J. Lipid Res. 2014, 55, 2242–2253. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  129. Fisher, E.; Lake, E.; McLeod, R.S. Apolipoprotein B100 quality control and the regulation of hepatic very low density lipoprotein secretion. J. Biomed. Res. 2014, 28, 178–193. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  130. Shi, W.; Li, J.; Bao, K.; Chen, M.H.; Liu, Z. Ldlr-Deficient Mice with an Atherosclerosis-Resistant Background Develop Severe Hyperglycemia and Type 2 Diabetes on a Western-Type Diet. Biomedicines 2022, 10, 1429. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  131. Swirski, F.K.; Libby, P.; Aikawa, E.; Alcaide, P.; Luscinskas, F.W.; Weissleder, R.; Pittet, M.J. Ly-6Chi monocytes dominate hypercholesterolemia-associated monocytosis and give rise to macrophages in atheromata. J. Clin. Investig. 2007, 117, 195–205. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  132. Duewell, P.; Kono, H.; Rayner, K.J.; Sirois, C.M.; Vladimer, G.; Bauernfeind, F.G.; Abela, G.S.; Franchi, L.; Nunez, G.; Schnurr, M.; et al. NLRP3 inflammasomes are required for atherogenesis and activated by cholesterol crystals. Nature 2010, 464, 1357–1361. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  133. Sosic-Jurjevic, B.; Lutjohann, D.; Trifunovic, S.; Pavlovic, S.; Borkovic Mitic, S.; Jovanovic, L.; Ristic, N.; Marina, L.; Ajdzanovic, V.; Filipovic, B. Differences in Cholesterol Metabolism, Hepato-Intestinal Aging, and Hepatic Endocrine Milieu in Rats as Affected by the Sex and Age. Int. J. Mol. Sci. 2023, 24, 12624. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  134. Getz, G.S.; Reardon, C.A. Diet, Microbes, and Murine Atherosclerosis. Arterioscler. Thromb. Vasc. Biol. 2018, 38, 2269–2271. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  135. Gaudreault, N.; Kumar, N.; Posada, J.M.; Stephens, K.B.; Reyes de Mochel, N.S.; Eberle, D.; Olivas, V.R.; Kim, R.Y.; Harms, M.J.; Johnson, S.; et al. ApoE suppresses atherosclerosis by reducing lipid accumulation in circulating monocytes and the expression of inflammatory molecules on monocytes and vascular endothelium. Arterioscler. Thromb. Vasc. Biol. 2012, 32, 264–272. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  136. Potteaux, S.; Gautier, E.L.; Hutchison, S.B.; van Rooijen, N.; Rader, D.J.; Thomas, M.J.; Sorci-Thomas, M.G.; Randolph, G.J. Suppressed monocyte recruitment drives macrophage removal from atherosclerotic plaques of Apoe-/- mice during disease regression. J. Clin. Investig. 2011, 121, 2025–2036. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  137. Ait-Oufella, H.; Sage, A.P.; Mallat, Z.; Tedgui, A. Adaptive (T and B cells) immunity and control by dendritic cells in atherosclerosis. Circ. Res. 2014, 114, 1640–1660. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  138. Ajoolabady, A.; Pratico, D.; Lin, L.; Mantzoros, C.S.; Bahijri, S.; Tuomilehto, J.; Ren, J. Inflammation in atherosclerosis: Pathophysiology and mechanisms. Cell Death Dis. 2024, 15, 817. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  139. Getz, G.S.; Reardon, C.A. Apoprotein E as a lipid transport and signaling protein in the blood, liver, and artery wall. J. Lipid Res. 2009, 50, S156–S161. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  140. Zhu, Y.; Kodvawala, A.; Hui, D.Y. Apolipoprotein E inhibits toll-like receptor (TLR)-3- and TLR-4-mediated macrophage activation through distinct mechanisms. Biochem. J. 2010, 428, 47–54. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  141. Titolo, G.; Morello, M.; Caiazza, S.; Luisi, E.; Solimene, A.; Serpico, C.; D’Elia, S.; Golino, P.; Loffredo, F.S.; Natale, F.; et al. APOE Genotype and Endothelial Biomarkers: Towards Personalized Cardiovascular Screening. Genes 2025, 16, 1494. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  142. de Mol, J.; Smit, V.; Kleijn, M.; van Santbrink, P.J.; Bot, I.; Foks, A.C. Immunosenescence accelerates atherosclerosis development in AAV-PCSK9 mouse model. Geroscience 2025, 47, 6549–6563. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  143. Keeter, W.C.; Carter, N.M.; Nadler, J.L.; Galkina, E.V. The AAV-PCSK9 murine model of atherosclerosis and metabolic dysfunction. Eur. Heart J. Open 2022, 2, oeac028. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  144. Jarrett, K.E.; Lee, C.M.; Yeh, Y.H.; Hsu, R.H.; Gupta, R.; Zhang, M.; Rodriguez, P.J.; Lee, C.S.; Gillard, B.K.; Bissig, K.D.; et al. Somatic genome editing with CRISPR/Cas9 generates and corrects a metabolic disease. Sci. Rep. 2017, 7, 44624. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  145. Mak, M.C.E.; Gurung, R.; Foo, R.S.Y. Applications of Genome Editing Technologies in CAD Research and Therapy with a Focus on Atherosclerosis. Int. J. Mol. Sci. 2023, 24, 14057. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  146. Gibson, C.J.; Lindsley, R.C.; Tchekmedyian, V.; Mar, B.G.; Shi, J.; Jaiswal, S.; Bosworth, A.; Francisco, L.; He, J.; Bansal, A.; et al. Clonal Hematopoiesis Associated With Adverse Outcomes After Autologous Stem-Cell Transplantation for Lymphoma. J. Clin. Oncol. 2017, 35, 1598–1605. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  147. Jaiswal, S.; Ebert, B.L. Clonal hematopoiesis in human aging and disease. Science 2019, 366, eaan4673. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  148. Jaiswal, S.; Fontanillas, P.; Flannick, J.; Manning, A.; Grauman, P.V.; Mar, B.G.; Lindsley, R.C.; Mermel, C.H.; Burtt, N.; Chavez, A.; et al. Age-related clonal hematopoiesis associated with adverse outcomes. N. Engl. J. Med. 2014, 371, 2488–2498. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  149. Jaiswal, S.; Natarajan, P.; Silver, A.J.; Gibson, C.J.; Bick, A.G.; Shvartz, E.; McConkey, M.; Gupta, N.; Gabriel, S.; Ardissino, D.; et al. Clonal Hematopoiesis and Risk of Atherosclerotic Cardiovascular Disease. N. Engl. J. Med. 2017, 377, 111–121. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  150. Rauch, P.J.; Gopakumar, J.; Silver, A.J.; Nachun, D.; Ahmad, H.; McConkey, M.; Nakao, T.; Bosse, M.; Rentz, T.; Vivanco Gonzalez, N.; et al. Loss-of-function mutations in Dnmt3a and Tet2 lead to accelerated atherosclerosis and concordant macrophage phenotypes. Nat. Cardiovasc. Res. 2023, 2, 805–818. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  151. Fuster, J.J.; MacLauchlan, S.; Zuriaga, M.A.; Polackal, M.N.; Ostriker, A.C.; Chakraborty, R.; Wu, C.L.; Sano, S.; Muralidharan, S.; Rius, C.; et al. Clonal hematopoiesis associated with TET2 deficiency accelerates atherosclerosis development in mice. Science 2017, 355, 842–847. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  152. Zhao, L.; Lee, E.; Zukas, A.M.; Middleton, M.K.; Kinder, M.; Acharya, P.S.; Hall, J.A.; Rader, D.J.; Pure, E. CD44 expressed on both bone marrow-derived and non-bone marrow-derived cells promotes atherogenesis in ApoE-deficient mice. Arterioscler. Thromb. Vasc. Biol. 2008, 28, 1283–1289. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  153. Rentz, T.; Dorighello, G.G.; Dos Santos, R.R.; Barreto, L.M.; Freitas, I.N.; Lazaro, C.M.; Razolli, D.S.; Cazita, P.M.; Oliveira, H.C.F. CETP Expression in Bone-Marrow-Derived Cells Reduces the Inflammatory Features of Atherosclerosis in Hypercholesterolemic Mice. Biomolecules 2023, 13, 1556. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  154. Lin, J.D.; Nishi, H.; Poles, J.; Niu, X.; McCauley, C.; Rahman, K.; Brown, E.J.; Yeung, S.T.; Vozhilla, N.; Weinstock, A.; et al. Single-cell analysis of fate-mapped macrophages reveals heterogeneity, including stem-like properties, during atherosclerosis progression and regression. JCI Insight 2019, 4, e124574. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  155. Williams, J.W.; Zaitsev, K.; Kim, K.W.; Ivanov, S.; Saunders, B.T.; Schrank, P.R.; Kim, K.; Elvington, A.; Kim, S.H.; Tucker, C.G.; et al. Limited proliferation capacity of aortic intima resident macrophages requires monocyte recruitment for atherosclerotic plaque progression. Nat. Immunol. 2020, 21, 1194–1204. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  156. Nakashima, Y.; Plump, A.S.; Raines, E.W.; Breslow, J.L.; Ross, R. ApoE-deficient mice develop lesions of all phases of atherosclerosis throughout the arterial tree. Arterioscler. Thromb. 1994, 14, 133–140. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  157. Van der Donckt, C.; Van Herck, J.L.; Schrijvers, D.M.; Vanhoutte, G.; Verhoye, M.; Blockx, I.; Van Der Linden, A.; Bauters, D.; Lijnen, H.R.; Sluimer, J.C.; et al. Elastin fragmentation in atherosclerotic mice leads to intraplaque neovascularization, plaque rupture, myocardial infarction, stroke, and sudden death. Eur. Heart J. 2015, 36, 1049–1058. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  158. Rateri, D.L.; Howatt, D.A.; Moorleghen, J.J.; Charnigo, R.; Cassis, L.A.; Daugherty, A. Prolonged infusion of angiotensin II in apoE-/- mice promotes macrophage recruitment with continued expansion of abdominal aortic aneurysm. Am. J. Pathol. 2011, 179, 1542–1548. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  159. Daugherty, A.; Manning, M.W.; Cassis, L.A. Angiotensin II promotes atherosclerotic lesions and aneurysms in apolipoprotein E-deficient mice. J. Clin. Investig. 2000, 105, 1605–1612. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  160. Weiss, D.; Kools, J.J.; Taylor, W.R. Angiotensin II-induced hypertension accelerates the development of atherosclerosis in apoE-deficient mice. Circulation 2001, 103, 448–454. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  161. Morat, N.; Civieri, G.; Spezia, M.; Menegolo, M.; Bernava, G.; Iliceto, S.; Iop, L.; Tona, F. Angiotensin II and Atherosclerosis: A New Cardiovascular Risk Factor Beyond Hypertension. Int. J. Mol. Sci. 2025, 26, 7527. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  162. Starsichova, A. SR-B1-/-ApoE-R61h/h Mice Mimic Human Coronary Heart Disease. Cardiovasc. Drugs Ther. 2024, 38, 1123–1137. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  163. Braun, A.; Trigatti, B.L.; Post, M.J.; Sato, K.; Simons, M.; Edelberg, J.M.; Rosenberg, R.D.; Schrenzel, M.; Krieger, M. Loss of SR-BI expression leads to the early onset of occlusive atherosclerotic coronary artery disease, spontaneous myocardial infarctions, severe cardiac dysfunction, and premature death in apolipoprotein E-deficient mice. Circ. Res. 2002, 90, 270–276. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  164. Zhang, S.; Picard, M.H.; Vasile, E.; Zhu, Y.; Raffai, R.L.; Weisgraber, K.H.; Krieger, M. Diet-induced occlusive coronary atherosclerosis, myocardial infarction, cardiac dysfunction, and premature death in scavenger receptor class B type I-deficient, hypomorphic apolipoprotein ER61 mice. Circulation 2005, 111, 3457–3464. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  165. Ferraro, B. The SR-B1DeltaCT/LDLR KO mouse: A new tool to shed light on coronary artery disease. Atherosclerosis 2024, 395, 117564. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  166. Mullis, D.M.; Padilla-Lopez, A.; Wang, H.; Zhu, Y.; Elde, S.; Bonham, S.A.; Yajima, S.; Kocher, O.N.; Krieger, M.; Woo, Y.J. Stromal cell-derived factor-1 alpha improves cardiac function in a novel diet-induced coronary atherosclerosis model, the SR-B1DeltaCT/LDLR KO mouse. Atherosclerosis 2024, 395, 117518. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  167. Fuller, M.; Dadoo, O.; Serkis, V.; Abutouk, D.; MacDonald, M.; Dhingani, N.; Macri, J.; Igdoura, S.A.; Trigatti, B.L. The effects of diet on occlusive coronary artery atherosclerosis and myocardial infarction in scavenger receptor class B, type 1/low-density lipoprotein receptor double knockout mice. Arterioscler. Thromb. Vasc. Biol. 2014, 34, 2394–2403. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  168. Emini Veseli, B.; Perrotta, P.; De Meyer, G.R.A.; Roth, L.; Van der Donckt, C.; Martinet, W.; De Meyer, G.R.Y. Animal models of atherosclerosis. Eur. J. Pharmacol. 2017, 816, 3–13. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  169. De Villiers, C.; Riley, P.R. Mouse models of myocardial infarction: Comparing permanent ligation and ischaemia-reperfusion. Dis. Models Mech. 2020, 13, dmm046565. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  170. Virmani, R.; Burke, A.P.; Farb, A.; Kolodgie, F.D. Pathology of the vulnerable plaque. J. Am. Coll. Cardiol. 2006, 47, C13–C18. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  171. Libby, P. The changing landscape of atherosclerosis. Nature 2021, 592, 524–533. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  172. Lindsey, M.L.; Bolli, R.; Canty, J.M., Jr.; Du, X.J.; Frangogiannis, N.G.; Frantz, S.; Gourdie, R.G.; Holmes, J.W.; Jones, S.P.; Kloner, R.A.; et al. Guidelines for experimental models of myocardial ischemia and infarction. Am. J. Physiol. Heart Circ. Physiol. 2018, 314, H812–H838. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  173. Ferdinandy, P.; Andreadou, I.; Baxter, G.F.; Botker, H.E.; Davidson, S.M.; Dobrev, D.; Gersh, B.J.; Heusch, G.; Lecour, S.; Ruiz-Meana, M.; et al. Interaction of Cardiovascular Nonmodifiable Risk Factors, Comorbidities and Comedications With Ischemia/Reperfusion Injury and Cardioprotection by Pharmacological Treatments and Ischemic Conditioning. Pharmacol. Rev. 2023, 75, 159–216. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  174. van Vlijmen, B.J.; van den Maagdenberg, A.M.; Gijbels, M.J.; van der Boom, H.; HogenEsch, H.; Frants, R.R.; Hofker, M.H.; Havekes, L.M. Diet-induced hyperlipoproteinemia and atherosclerosis in apolipoprotein E3-Leiden transgenic mice. J. Clin. Investig. 1994, 93, 1403–1410. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  175. Engster, J.C.; Reinberger, T.; Blum, N.; Stagge, P.; Buzug, T.M.; Aherrahrou, Z.; Stille, M. Artery segmentation and atherosclerotic plaque quantification using AI for murine whole slide images stained with oil red O. Sci. Rep. 2025, 15, 14152. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  176. Jurtz, V.I.; Skovbjerg, G.; Salinas, C.G.; Roostalu, U.; Pedersen, L.; Hecksher-Sorensen, J.; Rolin, B.; Nyberg, M.; van de Bunt, M.; Ingvorsen, C. Deep learning reveals 3D atherosclerotic plaque distribution and composition. Sci. Rep. 2020, 10, 21523. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  177. Sinha, A.; Sachs, N.; Kratz, E.; Pauli, J.; Steigerwald, S.; Albrecht, V.; Nordmann, T.M.; Ugur, E.; Rodriguez, E.H.; Engl, M.L.; et al. Proteomics reveals spatial and molecular heterogeneities in advanced atherosclerotic carotid artery plaques. Nat. Cardiovasc. Res. 2026, 5, 605–623. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  178. Bleckwehl, T.; Babler, A.; Tebens, M.; Maryam, S.; Nyberg, M.; Bosteen, M.; Halder, M.; Shaw, I.; Fleig, S.; Pyke, C.; et al. Encompassing view of spatial and single-cell RNA sequencing renews the role of the microvasculature in human atherosclerosis. Nat. Cardiovasc. Res. 2025, 4, 26–44. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  179. Man, J.J.; Beckman, J.A.; Jaffe, I.Z. Sex as a Biological Variable in Atherosclerosis. Circ. Res. 2020, 126, 1297–1319. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  180. Caligiuri, G.; Nicoletti, A.; Zhou, X.; Tornberg, I.; Hansson, G.K. Effects of sex and age on atherosclerosis and autoimmunity in apoE-deficient mice. Atherosclerosis 1999, 145, 301–308. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  181. Bourassa, P.A.; Milos, P.M.; Gaynor, B.J.; Breslow, J.L.; Aiello, R.J. Estrogen reduces atherosclerotic lesion development in apolipoprotein E-deficient mice. Proc. Natl. Acad. Sci. USA 1996, 93, 10022–10027. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  182. Marsh, M.M.; Walker, V.R.; Curtiss, L.K.; Banka, C.L. Protection against atherosclerosis by estrogen is independent of plasma cholesterol levels in LDL receptor-deficient mice. J. Lipid Res. 1999, 40, 893–900. [Google Scholar] [CrossRef] [Scilit]
  183. Vozenilek, A.E.; Blackburn, C.M.R.; Schilke, R.M.; Chandran, S.; Castore, R.; Klein, R.L.; Woolard, M.D. AAV8-mediated overexpression of mPCSK9 in liver differs between male and female mice. Atherosclerosis 2018, 278, 66–72. [Google Scholar] [CrossRef] [Scilit] [PubMed]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Article Metrics

Citations

Article Access Statistics

Multiple requests from the same IP address are counted as one view.