Cardiovascular diseases (CVDs) are a large group of diseases and have become the leading cause of morbidity and mortality worldwide. Although considerable progresses have been made in the diagnosis, treatment and prognosis of CVD, communication barriers between clinicians and researchers still exist because the phenotypes of CVD are complex and diverse in clinical practice and lack of unity. Therefore, it is particularly important to establish a standardized and unified terminology to describe CVD. In recent years, there have been several studies, such as the Human Phenotype Ontology, attempting to provide a standardized description of the disease phenotypes. In the present article, we outline recent advances in the classification of the major types of CVD to retrospectively review the current progresses of phenotypic studies in the cardiovascular field and provide a reference for future cardiovascular research.
As the leading cause of human death, cardiovascular disease (CVD) is a major public health problem worldwide, especially in developing countries (Zhou et al. 2019). The Global Burden of Cardiovascular Disease study (Roth et al. 2017) from 1990 to 2015 showed that there were an estimated 422.7 million CVD patients and 17.92 million deaths from CVD worldwide in 2015, placing a huge disease burden on humans. Therefore, it is of great social significance for the precise prevention and treatment of CVD.
However, the inconformity in the description of CVD phenotypes poses difficulties in disease diagnosis and treatment. The development of clinical medicine has a long history, and the methods used for classifying CVD phenotypes are diverse. In addition, the terminologies used to describe the phenotype of each disease were lack of unity (Allanson et al. 2009), making it difficult to communicate among clinical doctors. Furthermore, the rapid development of genomics (Schuster 2008) has enabled the identification of individual causative genes (Ng et al. 2009). However, the lack of linkage between clinical phenotypes and genomic data affects the precise diagnosis and treatment of human diseases (Bilder et al. 2009; Freimer and Sabatti 2003), and a unified and internationally accepted terminology should be established to describe disease phenotypes (Allanson et al. 2009).
It is particularly important to construct a set of terminologies for the precise description of disease phenotypes. The accurate description of disease phenotypes provides standards for accurate diagnosis, individualized treatment and prognosis evaluation of CVD. Some studies have systematically described diseases from multiple perspectives, such as clinical manifestations, pathologies and genotypes. Human Phenotype Ontology (HPO) provides a structured term set to give a precise description of disease phenotypes, facilitating the clinical doctors and testing organizations to have the easy access to the disease databases (Fig. 1). HPO has provided great convenience for the basic data analysis, diagnosis and treatment of clinical diseases, and it has become a paradigm for the description of disease phenotypes.
In this review, we describe the current progresses and shortcomings of phenotypic classification in CVD underlying the precise description of CVD in the future, in which the accurate and uniform description of the disease phenotypes is conducive to the definite diagnosis, prognosis evaluation and individualized treatment of CVD.
Phenotypic Classification of Valvular Disease
Mitral Valve Prolapse (MVP)
MVP is a common disease that affects 2–3% of the world's population (Freed et al. 1999). MVP is characterized by an abnormal bulging of the mitral valve leaflets into the left atrium during ventricular systole (Guy and Hill 2012). MVP is the leading cause of primary mitral valve surgery (Delling et al. 2016).
Carpentier first classified MVP by the mitral value prolapse site (Carpentier 1983). According to whether MVP is accompanied by systemic diseases, MVP is further divided into two categories as follows: nonsyndromic MVP and syndromic MVP. Syndromic MVP is accompanied by a variety of systemic diseases and is considered as a systemic disease. Nonsyndromic MVP is currently considered to contain three subtypes. First, the fibroelastic deficiency (FED)-related MVP subtype mostly affects the elderly, which is considered as a kind of degeneration disease. The leaflets of the mitral valve are thin, translucent and of normal length, and the mitral annulus is mildly dilated. Mitral regurgitation occurs due to chordal rupture, and only the prolapsing or flail segment is thickened and moderately elongated (Le Tourneau et al. 2018a, b). Pathological studies have confirmed the absence of associated elastic fibers in the mitral valve of FED-related MVP patients. Second, the myxoma-related MVP (Barlow's disease) subtype is characterized by lengthy thickening of both the anterior and posterior leaflets of the mitral valve, and it is accompanied by mitral annulus disjunction (MAD) (Putnam et al. 2020). Pathological performance suggests excessive proliferation and activation of valvular interstitial cells and increased content of type III collagen. Thirdly, the FLNA-related MVP subtype is an X-associated sex chromosome inherited disease that is much severer in males than in females. This subtype is characterized by lengthy thickening of mitral valve leaflets, and it is seldom accompanied by MAD. In addition, MVP with arrhythmia has gradually attracted the attention of the scientific community in recent years. This type of patient features myxomatosis of the bileaflet and mitral annular separation, and ventricular arrhythmias and sudden death are the major symptoms of these patients. Furthermore, the pathological performance of MVP with arrhythmia is also characterized by fibrosis of the papillary muscle and basal inferior wall in the left ventricle (Del Pasqua et al. 2009).
Although the classification of MVP is currently widely recognized, there are still some shortcomings. First, different types of MVPs are not independent, and the current classifications do not solve these problems. For example, FLNA-related MVP has also been reported to have mucinous degeneration, and there are significant continuous changes from FED to Barlow's disease. Second, genetic studies of MVP are insufficient. Third, the application of imaging techniques to identify different subtypes of MVP is still immature. In future work, we should standardize the classification of MVP by improving the quality of imaging data and integrating different pathophysiological characteristics.
Tricuspid Valve Malformation
Tricuspid valve malformation (also called Ebstein’s anomaly) is a rare congenital heart disorder that accounts for approximately 1% of congenital heart diseases (Attenhofer Jost et al. 2007). There are three classification methods of Ebstein’s anomaly with different perspectives.
Carpentier classification of Ebstein’s anomaly is a straightforward classification method (Carpentier et al. 1988), and it divides Ebstein’s anomaly into four types: (1) Type A, the functional right ventricle volume is appropriate; (2) Type B, the atrialized portion of the right ventricle is large, but the anterior leaflet moves freely; (3) Type C, the anterior leaflet is severely restricted in motion and can obstruct the right ventricular outflow tract; and (4) Type D, the right ventricle is almost entirely atrialized, except for a small infundibular segment. This classification method reveals the specific pathophysiological features of different types. Celermajer classification is mainly based on the ratio of the combined area of the right atrium and atrialized right ventricle to that of the functional right ventricle and left heart in a four-chamber view at end-diastole (Celermajer et al. 1994), and it classifies this disease severity into four grades as follows: Grade 1, ratio < 0.5; Grade 2, ratio 0.5–1; Grade 3, ratio 1–1.5; and Grade 4, ratio ≥ 1.5. Both the ratio > 1.5 in adults and the ratio > 1.0 in neonates have a fatality rate of 100%. This classification method is the guideline for risk stratification of Ebstein’s anomaly patients.
In 2020, Zhou's team annotated Ebstein’s anomaly by the standard vocabulary of abnormal phenotypes in HPO (Tang et al. 2020), and they classified Ebstein’s anomaly into the three following subtypes: (1) pulmonary hypertension but without patent foramen ovale; (2) no pulmonary hypertension and rarely with Wolff-Parkinson-White syndrome or ventricular septal defect; and (3) no pulmonary hypertension or ventricular septal defect but with Wolff-Parkinson-White syndrome. Their study also analyzed the relationship between HPO-based reclassification and adverse clinical outcomes. Classification of Ebstein’s anomaly based on HPO annotation is helpful for clinical diagnosis and treatment, and it provides an essential reference for investigating the classification of other congenital heart diseases.
Bicuspid Aortic Valve (BAV)
BAV is the most common congenital heart malformation with an incidence of 1–2% in the population (Hoffman and Kaplan 2002). The normal aortic valve consists of three equal-sized semilunar leaflets, whereas patients with BAV present with two unequal-sized leaflets due to congenital leaflet dysplasia (Hoffman and Kaplan 2002). BAV leads to more than 50% death and complications of congenital heart diseases.
There have been many studies on the classification of BAVs (Angelini et al. 1989; Jilaihawi et al. 2016; Roberts 1970; Sabet et al. 1999). Currently, the most widely used method is the Sievers classification (Sievers and Schmidtke 2007). In this classification, BAV is divided into the following three types: (1) Type 0, valves with no raphe; (2) Type 1, valves with one raphe; and (3) Type 2, valves with two raphes. This classification method provides a particular reference for the clinical treatment of BAVs, in which artificial valve implantation and Ross surgery can be performed for patients with type 1 variants. For patients with type 0 variants, surgery is more challenging because a round rather than fan-shaped proximal suture method is recommended. For patients with type 2 variants, the incidence of ascending aortic aneurysms is significantly increased.
Another method is the Brussels classification (de Kerchove et al. 2019). Compared to the Sievers classification, Brussels classified BAVs into the following three types according to two normally developed junctional angles of BAVs: (1) Type A, symmetrical BAV of 180°–160°; (2) Type B, asymmetrical BAV of 159°–140°; and (3) Type C, very asymmetrical BAV of 139°–120°. Different types of variants require different repair methods. For type A patients, central plication or direct closure of the non-fused portion of the raphe is needed. For type B patients, a thin raphe is also required in addition to direct closure. For type C patients, plication of the residual cusp component and generation of a functional commissure at the raphe or pericardial patch or type B repair are required. However, these two classifications only focus on single sights of BAVs, which does not meet clinical needs. Future studies should focus on proposing a comprehensive classification to guide the treatment of BAV.
According to whether the patients present other systemic diseases, BAVs can be divided into two types as follows: syndromic BAVs and nonsyndromic BAVs. The current understanding of the phenotypes and related genes of syndromic BAV is quite clear (Table 1). However, nonsyndromic BAV is a genetic disease caused by the interaction of many different genes with a complex pedigree inheritance (Siu and Silversides 2010). At the genetic level, BAV is a heterogeneous disorder inherited in an autosomal dominant pattern with incomplete penetrance and variable expressivity (Cripe et al. 2004; Prakash et al. 2014). The prevalence of BAV in first-degree family members is tenfold higher than that in the general population. Additionally, pedigree-based genome-wide linkage analysis has revealed that the risk ratio of recurrence of BAV in families with hypoplastic left heart syndrome (HLHS) is similar to that in families with BAV, providing evidence for a genetic relationship between HLHS and BAV (Hinton et al. 2009).
Although many studies have been conducted on the classification and etiology of BAV during the past 20 years, there is still no established unified classification scheme covering all patients to completely illustrate the heterogeneity of clinical manifestations of BAV. To establish a perfect classification in the future, the phenotype; and genotype should be correlated to group BAVs into different subtypes. This phenotype-genotype classification will assist in the clinical diagnosis and treatment of BAVs.
Phenotypic Classification of Cardiomyopathy
Cardiomyopathy is a group of heterogeneous myocardial diseases (Dadson et al. 2017). Cardiomyopathy is caused by cardiac mechanical and electrical activity abnormalities, and it presents with inappropriate ventricular hypertrophy or dilation. Severe cardiomyopathy can cause cardiovascular death or progressive heart failure.
As early as 1980, the World Health Organization (WHO) (1980) proposed the first classification of cardiomyopathy, which classified cardiomyopathy into dilated cardiomyopathy (DCM), restrictive cardiomyopathy (RCM) and hypertrophic cardiomyopathy (HCM). In 1996, the WHO/ISFC (Richardson et al. 1996) classified cardiomyopathy into primary cardiomyopathy and specific cardiomyopathy. This classification method is more systematic, incorporating the newly discovered arrhythmogenic right ventricular cardiomyopathy (ARVC) and standardizing the classification of specific cardiomyopathy simultaneously. However, there are contradictions in the classification method of primary cardiomyopathy, and the classification of cardiomyopathy remains unclear.
With the rapid development of cardiac molecular genetics and a thorough understanding of the pathogenesis of cardiomyopathy, the American Heart Association (AHA) (Maron et al. 2006) has divided cardiomyopathy into the following two types: primary cardiomyopathy and secondary cardiomyopathy. Primary cardiomyopathies are those solely or predominantly confined to heart muscle and are relatively few in number, and they are further divided into three types. Secondary cardiomyopathies show pathological myocardial involvement as part of a large number and variety of generalized systemic disorders. This classification expands the scope of cardiomyopathy, which states that electrophysiological abnormalities other than structural abnormalities should also be included. This classification also emphasizes genetic etiology and the importance of genetic testing. Subsequently, the European Society of Cardiology (ESC) Cardiomyopathy and Pericardial Disease Working Group issued a related statement on the 1995 WHO/ISFC (Elliott et al. 2008), which classified cardiomyopathy into five types (Fig. 2). This classification discards the initial category of secondary cardiomyopathy and rejects that pure electrical disorder is cardiomyopathy, and this classification excludes ion channel diseases and conduction system diseases from cardiomyopathy. In 2013, Elliott et al. proposed comprehensive diagnosis and described cardiomyopathy patients by the following four aspects: cardiac morphology, affected organs, genetic patterns and etiology (Elliott 2013). This classification disregards the limitation that only clinical phenotypes are used to describe cardiomyopathy and provides a multiangle classification for cardiomyopathy patients combing with clinical phenotypes and genotypes. However, the clinical applicability of this classification is still not clear.
Many studies have intensively investigated and classified the subclasses of cardiomyopathy. In 1997, Maron classified HCM into the following four types according to the location of ventricular hypertrophy (Maron 1997): (1) Type I, anterior ventricular septal hypertrophy; (2) Type II, anterior and posterior septal hypertrophy; (3) Type III, hypertrophy of both the interventricular septum and the anterolateral wall of the left ventricle; and (4) Type IV, hypertrophy involving the posterior septum and/or lateral wall of the left ventricle or may only involve the apex without thickening of the anterior septum and the inferior (posterior) wall of the left ventricle. According to Maron’s classification, type III, accounting for 52% HCM, is the most common subtype, while type IV is the least common. This classification method classifies HCM from anatomical abnormalities but does not involve cardiac function. Subsequently, in 2014, ACC/ESC clinical expert consensus classified patients with HCM into obstructive HCM (left ventricular outflow tract pressure gradient, LVOGT ≥ 30 mmHg at rest), nonobstructive HCM (LVOGT < 30 mmHg at rest or during stress exercise) and occult obstructive HCM (normal LVOTG at rest and LVOGT ≥ 30 mmHg during stress exercise) according to the peak pressure gradient between the left ventricular outflow tract gradient and aorta (LVOTG) measured by echocardiography (Elliott et al. 2014). This classification highlights the cardiac function of HCM patients and has guiding significance for clinical diagnosis and treatment. It is found that the presence of multiple rare variants in sarcomeric genes is a risk factor for the malignant outcome of HCM, which may be considered as a criterion for risk stratification of HCM patients (Wang et al. 2014), providing novel ideas for predicting the prognosis of HCM.
In recent years, genotypic and hemodynamic studies have enriched HCM phenotypes. Myofilament mutations (MYBP3, MYH7, TNNI3, TNNT2, TPM1 and MYL2), Z-disc mutations (LBD3, ACTN2 and ANKRD1), and calcium-handing mutations (JPH2 and PLN) have been suggested to be associated with HCM (Geske et al. 2018). Regarding hemodynamic studies, Martinez-Legazpi et al. used diastolic vortex analysis to elucidate the mechanism of insufficient cardiac output in HCM patients and found that the ventricles of HCM patients were lack of vortex, resulting in poor filling (Martinez-Legazpi et al. 2014). In addition, HCM is often accompanied by systolic anterior motion (SAM). The subvalvular pressure gradient has been suggested to be used as a reliable diagnostic indicator of SAM (Meschini et al. 2021). When this quantity attains the value of 30 mmHg, SAM of the mitral leaflets is observed, and when this threshold is exceeded, the SAM becomes obstructive. This study provides a novel idea for the diagnosis of patients with clinically obstructive HCM.
In 2020, Verdonschot et al. reclassified DCM into four categories by integrating features, such as etiology, clinical comorbidities, cardiac function and transcriptomics (Verdonschot et al. 2020), which revealed the molecule-specific differences and corresponding pathogenesis of DCM patients. Subsequently, these researchers found that different DCM subtypes have different risks of clinical outcomes. Patients with type 1 disease have the best prognosis, while patients with type 3 disease who carry multiple arrhythmia-related gene variants, such as LMNA and TNN, have the worst prognosis. These findings lay a foundation for precise individualized treatment of DCM.
In terms of the classification of ARVC, Hu’s team used an unsupervised core clustering algorithm that included clinical features, histopathology and gene mutation characteristics to classify ARVC into four types as follows (Chen et al. 2019): Cluster 1 is characterized by the variation of DSG2, PKP2 and DSC2; Cluster 2 is characterized by the variation of PLN, LMNA, DES, TMEM43 and CTNNA3; Cluster 3 has mutations in DSP, PLN, CTNNA3 and other unknown mutations; Cluster 4 has unknown gene mutations. These researchers also predicted and validated the prognosis of patients using the new classification, and they suggested that targeted treatment should be performed for different types of patients. In addition, the precordial QRS voltage predicts the residual myocardium in the right ventricle, which effectively predicts death and the need for heart transplantation. Thus, the accurate classification of ARVC has been established internationally for the first time. The relationship between genotypes and phenotypes is analyzed based on a complete description of the ARVC phenotypes, which also provides a reference for classifying other types of cardiomyopathies in the future.
Although some meaningful genetic mutations are associated with RCM (Muchtar et al. 2017), no classification method clearly defines the disease due to its diverse etiology. Further investigations should be considered to combine gene mutations, clinical phenotypes and pathology to classify cardiomyopathy in detail. Moreover, the differences in the prognosis of different types should also be explored through long-term follow-up. Together, these studies may provide a reference for clinical diagnosis, treatment and prognosis towards precision medicine.
Phenotypic Classification of Heart Failure (HF)
HF is a common clinical syndrome with high morbidity and mortality. According to the 2016 ESC guidelines (Ponikowski et al. 2016), HF patients were divided into three types according to the left ventricular ejection fraction (LVEF) as follows: HF with reduced ejection fraction (HFrEF, LVEF ≤ 40%), HF with mid-range ejection fraction (HFmrEF, 40% < LVEF < 50%) and HF with preserved ejection fraction (HFpEF, LVEF ≥ 50%). In 2021, an update for the classification of HF was proposed with improved ejection fraction (HFimpEF, symptomatic HF with a baseline LVEF ≤ 40%, a ≥ 10-point increase from baseline of LVEF and a second measurement of LVEF > 40%) as a new type of HF (Bozkurt et al. 2021). Furthermore, the researchers revised the stages of HF into the following four stages: at risk for HF (Stage A), pre-heart failure (Stage B), HF (Stage C) and advanced HF (Stage D). These studies provide clear criteria for the classification and staging of HF. Nevertheless, the measurement of LVEF is limited by methods, operators and calculation (Fonarow 2017), making it challenging to use LVEF to accurately define patients with four types of HF.
Compared to classifying HF into different types, it has been proposed that HF is a progressive, multifactorial and complex syndrome with significant heterogeneity, and HF is considered a syndrome across a spectrum of phenotypes (Triposkiadis et al. 2019). Each HF phenotype is a result of a specific trajectory of patients. The trajectory path depends on the risk factors, combining diseases, sex, age and other characteristics of patients. Stratifying HF patients with different biological characteristics guides the accurate application of existing treatment technologies and the development of novel therapies for HF.
The treatment of HFrEF has progressed rapidly. However, due to the complex phenotypes and pathophysiological mechanisms of HFpEF, the same treatment regimen is unlikely to meet the needs of all kinds of HF patients, and no significant progress has been made in clinical trials. Therefore, it is essential to classify HFpEF patients accurately. In 2012, Shah and Pfeffer suggested to perform phenotypic analysis of HFpEF and conduct targeted treatments for different phenotypic subgroups (Shah and Pfeffer 2012). However, the proposed classification of HFpEF is complicated, limiting its clinical promotion (Shah et al. 2014a, b). In 2020, Ge proposed to divide HFpEF into five categories in which the patients of each category present similar pathophysiological changes (Ge 2020). Compared to the previous classifications, this classification is helpful to understand the risk factors, etiology, pathophysiology and clinical course of HFpEF, and it also facilitates the targeted and individualized treatment of patients with different etiologies in clinical work. It is expected that randomized clinical trials will be conducted in HFpEF patients of the same or main etiology to test the therapeutic effects of different therapeutic principles on HFpEF subtypes. In addition, considering the difficulties in obtaining the pathological tissues, the clinical characteristics, imaging findings and genotype changes can be synthesized to achieve the accurate classification of HF patients in the future.
Phenotypic Classification of Vascular Diseases
Acute Coronary Syndrome (ACS)
ACS is a group of clinical syndromes caused by acute myocardial ischemia. Based on the characteristics of ST-segment elevation in the electrocardiogram, ACS is classified into ST-segment elevation myocardial infarction (STEMI), non-ST-segment elevation myocardial infarction (NSTEMI) and unstable angina (UA). Although this approach is still applicable, it does not fully elucidate the pathophysiological mechanism of ACS.
In 2017, it was proposed that ACS can be classified into the following four categories through the pathophysiological characteristics of atherosclerotic plaques: plaque rupture with an inflammatory response, plaque rupture without an inflammatory response, plaque rupture caused by plaque erosion and ACS without thrombosis (Crea and Libby 2017). Different therapeutic strategies have been suggested for the subtypes of ACS. For example, for plaque rupture with an inflammatory response, treatment should be focused on reducing the production of inflammatory factors and regulating the function of immune cells (Morton et al. 2015; Shah et al. 2014a, b). Inhibiting the formation of cholesterol crystals should be considered unless plaque rupture is associated with an inflammatory response (Abela et al. 2011; Meuwese et al. 2009; Zimmer et al. 2016). When a plaque rupture caused by plaque erosion is encountered, treatments, including reduction of blood triglyceride levels, anticoagulants and antiplatelet therapy, should be considered (Jia et al. 2017; Libby 2015; Mangold et al. 2015). Furthermore, using vasodilators to reduce coronary spasms is an effective treatment to cure ACS patients without thrombosis. This classification method allows clinicians to apply proper treatments to different ACS patients. In addition to inflammation, plaque composition is also proposed to be associated with myocardial ischemia (Gaur et al. 2016). With simple stenosis assessment, the addition of plaque assessment is more conducive to the assessment of myocardial ischemia, which may further facilitate the accurate classification of coronary heart disease.
Although there have been remarkable progresses in the classification of ACS, the clinical manifestations and pathophysiological mechanisms of ACS patients still need to be combined. In subsequent work, it is necessary to develop biological and imaging markers that reflect the mechanism of ACS and verify them in clinical practice. Thus, a strict clinical evaluation for the targeted therapy of ACS with different classifications can be performed, which is beneficial to achieve precision medicine.
Aortic Dissection (AD)
AD is a relatively rare disease with a poor prognosis. AD has a high mortality rate, especially when treatment is delayed. If AD occurs in the ascending aorta, 40% of patients die immediately, and the mortality rate increases by 1–2% per hour. The mortality rate is approximately 50% at 48 h after the occurrence of AD (Hirst et al. 1958).
According to the onset time, AD can be divided into three categories as follows: acute (< 14 days), subacute (15–90 days) and chronic (> 90 days). This classification method has guiding significance for predicting the prognosis of patients. The mortality of untreated acute AD increases with time. In chronic AD, there is a strong scar formation between the outer wall of the dissection and the surrounding tissue, and the outer wall of the dissection can mostly withstand aortic pressure. However, the classification method lacks a pathological description. DeBakey and colleagues proposed classifying AD into three types according to the extent of the aorta involved in dissection (Debakey et al. 1965). Reul et al. were the first to subdivide the DeBakey classification, distinguishing it from thoracoabdominal dissections (Reul et al. 1975). Daily et al. from Stanford University proposed another classification method mainly based on the location of the intimal cleft (Daily et al. 1970). Daily and colleagues divided AD into two categories, namely, proximal AD (Stanford A dissection) and distal AD (Stanford B dissection), bounded by the origin of the left subclavian artery and further subdivided it into different subcategories according to aortic arch lesions. This classification method is valuable for guiding treatment options. Most patients with acute AD die from pericardial tamponade due to rupture of the ascending aorta. Therefore, emergency surgery should be performed to replace the ascending aorta and/or aortic arch with the greatest risk of rupture for acute AD. For chronic AD, surgical treatment is also recommended. In contrast, endograft therapy or medical treatment is the preferred treatment for acute distal AD, and surgical treatment is considered only in patients with failed endograft therapy, medical treatment or complications. In addition, this classification has guiding significance for distinguishing acute and chronic AD; Stanford A dissection rarely converts to chronic AD, while Stanford B dissection often presents with arterial dilatation, fibrosis and other states with drug treatment (Peterss et al. 2016). In 2016, Urbanski and Wagner proposed non-A non-B AD (Urbanski and Wagner 2016). The dissection is limited to the aortic arch or can be described as a retrograde dissection arising from the descending aorta that extends into the arch and stops before the ascending aorta. These researchers proposed that compared to conservative treatment, emergency surgery may offer improved clinical outcomes through the follow-up of patients. This classification complements the traditional AD classification and guides the clinical treatment of non-A non-B AD.
For chronic distal AD, thoracoabdominal AD is divided into five types according to the involvement range of dissection (Crawford et al. 1978). After the initial classification of thoracoabdominal AD, type V (only renal artery involvement) was removed, changing the classification to four types (Crawford et al. 1986). The main classification is determined by the relationship between AD and the anatomical location of the left subclavian artery, diaphragm and visceral artery. This classification is helpful to guide the prevention and treatment of complications, such as paraplegia during chronic distal AD, because most of the main blood vessels supplying the spinal cord originate from the distal descending thoracic aorta and the proximal descending abdominal aorta. However, the Crawford classification does not clearly define the “distal descending aorta”. Safi used T6 as an anatomical marker for the upper and lower portions of the descending aorta according to the Crawford classification, adding a V-type thoracoabdominal AD (Safi 1999), further refining the content of the Crawford classification.
Previous studies have only considered the phenotypes of AD that has already occurred, however, the premonitory phenotypes of AD, such as intramural hemorrhagic hematoma and transmural aortic ulcer, are not described in these studies. Considering the factors above, the ESC proposed a new classification criterion that classifies AD into five categories (Erbel et al. 2001). This classification emphasizes the precancerous lesions of AD and provides new ideas for early clinical detection and intervention.
At present, the classification of AD is still based on the site of dissection, and the classification criteria for different sites are not consistent. In subsequent investigations, the phenotypic and genotypic abnormalities of AD should be considered in the classification. A comprehensive and unified classification will provide a reference for the clinical diagnosis and treatment of AD.
Summary and Perspectives
Over the past two centuries, great progresses in CVD treatment have been achieved by the intervention of risk factors and the development of evidence-based medicine (Leopold and Loscalzo 2018). However, the prevention and treatment of CVD are still suboptimal due to the wide heterogeneity of clinical manifestations in CAD patients. The description of phenotypes among individuals with the same disease is imprecise, leading to the lack of individualized treatment for patients (Antman and Loscalzo 2016). Therefore, there is an urgent need for precise phenotyping of CVD. Several studies have disregarded the traditional situation of classifying CVD with a single clinical phenotype. Researchers have tried to describe CVD from multiple perspectives, such as clinical manifestations, pathology and imaging, further revealing the features of the disease and interindividual heterogeneity. However, there are still many improvements that need to be achieved in the description of CVD phenotypes (Table 2). In addition, most of the classification methods currently proposed are based on single-center studies and limited by the sample size. Multicenter validation is required before these concepts can be generalized.
With significant progresses in genetic research, the molecular etiology of CVD has gradually become clear. Genotypes are an indispensable part of the phenotypes of CVD. These advances provide novel insights into CVD manifestations and help to define the molecular pathophysiological basis for disease development. Combining the genotypes and clinical phenotypes can precisely group affected patients according to the risk stratification, which is helpful to identify the individuals who are at high risk for developing CVD but still present no obvious evidence of diseases. Although the current understanding of CVD genotypes is imperfect, the development of new genomics technologies provides unparalleled opportunities to fully explore the genetic architectures of different CVDs. The continuous improvement of genomics research on CVD is essential to the disease phenome providing the support for precision medicine.
(1980) Report of the WHO/ISFC task force on the definition and classification of cardiomyopathies. Br Heart J 44:672–3. https://doi.org/10.1136/hrt.44.6.672
Abela GS, Vedre A, Janoudi A, Huang R, Durga S, Tamhane U (2011) Effect of statins on cholesterol crystallization and atherosclerotic plaque stabilization. Am J Cardiol 107:1710–1717. https://doi.org/10.1016/j.amjcard.2011.02.336
Allanson JE, Biesecker LG, Carey JC, Hennekam RC (2009) Elements of morphology: introduction. Am J Med Genet A 149A:2–5. https://doi.org/10.1002/ajmg.a.32601
Andelfinger G, Loeys B, Dietz H (2016) A decade of discovery in the genetic understanding of thoracic aortic disease. Can J Cardiol 32:13–25. https://doi.org/10.1016/j.cjca.2015.10.017
Andrabi S, Bekheirnia MR, Robbins-Furman P, Lewis RA, Prior TW, Potocki L (2011) SMAD4 mutation segregating in a family with juvenile polyposis, aortopathy, and mitral valve dysfunction. Am J Med Genet A 155A:1165–1169. https://doi.org/10.1002/ajmg.a.33968
Andreassi MG, Della Corte A (2016) Genetics of bicuspid aortic valve aortopathy. Curr Opin Cardiol 31:585–592. https://doi.org/10.1097/HCO.0000000000000328
Angelini A, Ho SY, Anderson RH, Devine WA, Zuberbuhler JR, Becker AE, Davies MJ (1989) The morphology of the normal aortic valve as compared with the aortic valve having two leaflets. J Thorac Cardiovasc Surg 98:362–367
Antman EM, Loscalzo J (2016) Precision medicine in cardiology. Nat Rev Cardiol 13:591–602. https://doi.org/10.1038/nrcardio.2016.101
Attenhofer Jost CH, Connolly HM, Dearani JA, Edwards WD, Danielson GK (2007) Ebstein’s anomaly. Circulation 115:277–285. https://doi.org/10.1161/CIRCULATIONAHA.106.619338
Atzinger CL, Meyer RA, Khoury PR, Gao Z, Tinkle BT (2011) Cross-sectional and longitudinal assessment of aortic root dilation and valvular anomalies in hypermobile and classic Ehlers-Danlos syndrome. J Pediatr 158:826-830 e1. https://doi.org/10.1016/j.jpeds.2010.11.023
Baasanjav S, Al-Gazali L, Hashiguchi T, Mizumoto S, Fischer B, Horn D, Seelow D, Ali BR, Aziz SA, Langer R, Saleh AA, Becker C, Nurnberg G, Cantagrel V, Gleeson JG, Gomez D, Michel JB, Stricker S, Lindner TH, Nurnberg P, Sugahara K, Mundlos S, Hoffmann K (2011) Faulty initiation of proteoglycan synthesis causes cardiac and joint defects. Am J Hum Genet 89:15–27. https://doi.org/10.1016/j.ajhg.2011.05.021
Bilder RM, Sabb FW, Cannon TD, London ED, Jentsch JD, Parker DS, Poldrack RA, Evans C, Freimer NB (2009) Phenomics: the systematic study of phenotypes on a genome-wide scale. Neuroscience 164:30–42. https://doi.org/10.1016/j.neuroscience.2009.01.027
Bozkurt B, Coats AJS, Tsutsui H, Abdelhamid CM, Adamopoulos S, Albert N, Anker SD, Atherton J, Bohm M, Butler J, Drazner MH, Michael Felker G, Filippatos G, Fiuzat M, Fonarow GC, Gomez-Mesa JE, Heidenreich P, Imamura T, Jankowska EA, Januzzi J, Khazanie P, Kinugawa K, Lam CSP, Matsue Y, Metra M, Ohtani T, Francesco Piepoli M, Ponikowski P, Rosano GMC, Sakata Y, Seferovic P, Starling RC, Teerlink JR, Vardeny O, Yamamoto K, Yancy C, Zhang J, Zieroth S (2021) Universal definition and classification of heart failure: a report of the Heart Failure Society of America, Heart Failure Association of the European Society of Cardiology, Japanese Heart Failure Society and Writing Committee of the Universal Definition of Heart Failure: Endorsed by the Canadian Heart Failure Society, Heart Failure Association of India, Cardiac Society of Australia and New Zealand, and Chinese Heart Failure Association. Eur J Heart Fail 23:352–380. https://doi.org/10.1002/ejhf.2115
Bull MJ (2020) Down syndrome. N Engl J Med 382:2344–2352. https://doi.org/10.1056/NEJMra1706537
Carpentier A (1983) Cardiac valve surgery–the “French correction.” J Thorac Cardiovasc Surg 86:323–337
Carpentier A, Chauvaud S, Mace L, Relland J, Mihaileanu S, Marino JP, Abry B, Guibourt P (1988) A new reconstructive operation for Ebstein’s anomaly of the tricuspid valve. J Thorac Cardiovasc Surg 96:92–101
Celermajer DS, Bull C, Till JA, Cullen S, Vassillikos VP, Sullivan ID, Allan L, Nihoyannopoulos P, Somerville J, Deanfield JE (1994) Ebstein’s anomaly: presentation and outcome from fetus to adult. J Am Coll Cardiol 23:170–176. https://doi.org/10.1016/0735-1097(94)90516-9
Chauvaud S, Berrebi A, d’Attellis N, Mousseaux E, Hernigou A, Carpentier A (2003) Ebstein’s anomaly: repair based on functional analysis. Eur J Cardiothorac Surg 23:525–531. https://doi.org/10.1016/s1010-7940(02)00836-9
Chen L, Song J, Chen X, Chen K, Ren J, Zhang N, Rao M, Hu Z, Zhang Y, Gu M, Zhao H, Tang H, Yang Z, Hu S (2019) A novel genotype-based clinicopathology classification of arrhythmogenic cardiomyopathy provides novel insights into disease progression. Eur Heart J 40:1690–1703. https://doi.org/10.1093/eurheartj/ehz172
Crawford ES, Snyder DM, Cho GC, Roehm JO Jr (1978) Progress in treatment of thoracoabdominal and abdominal aortic aneurysms involving celiac, superior mesenteric, and renal arteries. Ann Surg 188:404–422. https://doi.org/10.1097/00000658-197809000-00016
Crawford ES, Crawford JL, Safi HJ, Coselli JS, Hess KR, Brooks B, Norton HJ, Glaeser DH (1986) Thoracoabdominal aortic aneurysms: preoperative and intraoperative factors determining immediate and long-term results of operations in 605 patients. J Vasc Surg 3:389–404. https://doi.org/10.1067/mva.1986.avs0030389
Crawford ES, Svensson LG, Coselli JS, Safi HJ, Hess KR (1989) Surgical treatment of aneurysm and/or dissection of the ascending aorta, transverse aortic arch, and ascending aorta and transverse aortic arch. Factors influencing survival in 717 patients. J Thorac Cardiovasc Surg 98:659–673
Crea F, Libby P (2017) Acute coronary syndromes: the way forward from mechanisms to precision treatment. Circulation 136:1155–1166. https://doi.org/10.1161/CIRCULATIONAHA.117.029870
Cripe L, Andelfinger G, Martin LJ, Shooner K, Benson DW (2004) Bicuspid aortic valve is heritable. J Am Coll Cardiol 44:138–143. https://doi.org/10.1016/j.jacc.2004.03.050
Dadson K, Hauck L, Billia F (2017) Molecular mechanisms in cardiomyopathy. Clin Sci (lond) 131:1375–1392. https://doi.org/10.1042/CS20160170
Daily PO, Trueblood HW, Stinson EB, Wuerflein RD, Shumway NE (1970) Management of acute aortic dissections. Ann Thorac Surg 10:237–247. https://doi.org/10.1016/s0003-4975(10)65594-4
de Kerchove L, Mastrobuoni S, Froede L, Tamer S, Boodhwani M, van Dyck M, El Khoury G, Schafers HJ (2019) Variability of repairable bicuspid aortic valve phenotypes: towards an anatomical and repair-oriented classification. Eur J Cardiothorac Surg. https://doi.org/10.1093/ejcts/ezz033
Debakey ME, Henly WS, Cooley DA, Morris GC Jr, Crawford ES, Beall AC Jr (1965) Surgical management of dissecting aneurysms of the aorta. J Thorac Cardiovasc Surg 49:130–149
DeBakey ME, McCollum CH, Crawford ES, Morris GC Jr, Howell J, Noon GP, Lawrie G (1982) Dissection and dissecting aneurysms of the aorta: twenty-year follow-up of five hundred twenty-seven patients treated surgically. Surgery 92:1118–1134
Del Pasqua A, Rinelli G, Toscano A, Iacobelli R, Digilio C, Marino B, Saffirio C, Mondillo S, Pasquini L, Sanders SP, de Zorzi A (2009) New findings concerning cardiovascular manifestations emerging from long-term follow-up of 150 patients with the Williams-Beuren-Beuren syndrome. Cardiol Young 19:563–567. https://doi.org/10.1017/S1047951109990837
Delling FN, Rong J, Larson MG, Lehman B, Fuller D, Osypiuk E, Stantchev P, Hackman B, Manning WJ, Benjamin EJ, Levine RA, Vasan RS (2016) Evolution of mitral valve prolapse: insights from the framingham heart study. Circulation 133:1688–1695. https://doi.org/10.1161/CIRCULATIONAHA.115.020621
Detaint D, Faivre L, Collod-Beroud G, Child AH, Loeys BL, Binquet C, Gautier E, Arbustini E, Mayer K, Arslan-Kirchner M, Stheneur C, Halliday D, Beroud C, Bonithon-Kopp C, Claustres M, Plauchu H, Robinson PN, Kiotsekoglou A, De Backer J, Ades L, Francke U, De Paepe A, Boileau C, Jondeau G (2010) Cardiovascular manifestations in men and women carrying a FBN1 mutation. Eur Heart J 31:2223–2229. https://doi.org/10.1093/eurheartj/ehq258
Durst R, Sauls K, Peal DS, deVlaming A, Toomer K, Leyne M, Salani M, Talkowski ME, Brand H, Perrocheau M, Simpson C, Jett C, Stone MR, Charles F, Chiang C, Lynch SN, Bouatia-Naji N, Delling FN, Freed LA, Tribouilloy C, Le Tourneau T, LeMarec H, Fernandez-Friera L, Solis J, Trujillano D, Ossowski S, Estivill X, Dina C, Bruneval P, Chester A, Schott JJ, Irvine KD, Mao Y, Wessels A, Motiwala T, Puceat M, Tsukasaki Y, Menick DR, Kasiganesan H, Nie X, Broome AM, Williams K, Johnson A, Markwald RR, Jeunemaitre X, Hagege A, Levine RA, Milan DJ, Norris RA, Slaugenhaupt SA (2015) Mutations in DCHS1 cause mitral valve prolapse. Nature 525:109–113. https://doi.org/10.1038/nature14670
Elliott PM (2013) Classification of cardiomyopathies: evolution or revolution? J Am Coll Cardiol 62:2073–2074. https://doi.org/10.1016/j.jacc.2013.10.008
Elliott P, Andersson B, Arbustini E, Bilinska Z, Cecchi F, Charron P, Dubourg O, Kuhl U, Maisch B, McKenna WJ, Monserrat L, Pankuweit S, Rapezzi C, Seferovic P, Tavazzi L, Keren A (2008) Classification of the cardiomyopathies: a position statement from the European society of cardiology working group on myocardial and pericardial diseases. Eur Heart J 29:270–276. https://doi.org/10.1093/eurheartj/ehm342
Elliott PM, Anastasakis A, Borger MA, Borggrefe M, Cecchi F, Charron P, Hagege AA, Lafont A, Limongelli G, Mahrholdt H, McKenna WJ, Mogensen J, Nihoyannopoulos P, Nistri S, Pieper PG, Pieske B, Rapezzi C, Rutten FH, Tillmanns C, Watkins H (2014) 2014 ESC Guidelines on diagnosis and management of hypertrophic cardiomyopathy: the Task Force for the Diagnosis and Management of Hypertrophic Cardiomyopathy of the European Society of Cardiology (ESC). Eur Heart J 35:2733–2779. https://doi.org/10.1093/eurheartj/ehu284
Erbel R, Alfonso F, Boileau C, Dirsch O, Eber B, Haverich A, Rakowski H, Struyven J, Radegran K, Sechtem U, Taylor J, Zollikofer C, Klein WW, Mulder B, Providencia LA, Task Force on Aortic Dissection, E. S. o. C (2001) Diagnosis and management of aortic dissection. Eur Heart J 22:1642–1681. https://doi.org/10.1053/euhj.2001.2782
Fonarow GC (2017) Refining classification of heart failure based on ejection fraction. JACC Heart Fail 5:808–809. https://doi.org/10.1016/j.jchf.2017.08.011
Freed LA, Levy D, Levine RA, Larson MG, Evans JC, Fuller DL, Lehman B, Benjamin EJ (1999) Prevalence and clinical outcome of mitral-valve prolapse. N Engl J Med 341:1–7. https://doi.org/10.1056/NEJM199907013410101
Freimer N, Sabatti C (2003) The human phenome project. Nat Genet 34:15–21. https://doi.org/10.1038/ng0503-15
Galea J, Ellul S, Schembri A, Schembri-Wismayer P, Calleja-Agius J (2014) Ebstein anomaly: a review. Neonatal Netw 33:268–274. https://doi.org/10.1891/0730-08184.108.40.2068
Gaur S, Ovrehus KA, Dey D, Leipsic J, Botker HE, Jensen JM, Narula J, Ahmadi A, Achenbach S, Ko BS, Christiansen EH, Kaltoft AK, Berman DS, Bezerra H, Lassen JF, Norgaard BL (2016) Coronary plaque quantification and fractional flow reserve by coronary computed tomography angiography identify ischaemia-causing lesions. Eur Heart J 37:1220–1227. https://doi.org/10.1093/eurheartj/ehv690
Ge J (2020) Coding proposal on phenotyping heart failure with preserved ejection fraction: a practical tool for facilitating etiology-oriented therapy. Cardiol J 27:97–98. https://doi.org/10.5603/CJ.2020.0023
Geske JB, Ommen SR, Gersh BJ (2018) Hypertrophic cardiomyopathy: clinical update. JACC Heart Fail 6:364–375. https://doi.org/10.1016/j.jchf.2018.02.010
Guy TS, Hill AC (2012) Mitral valve prolapse. Annu Rev Med 63:277–292. https://doi.org/10.1146/annurev-med-022811-091602
Hall HN, Williamson KA, FitzPatrick DR (2019) The genetic architecture of aniridia and Gillespie syndrome. Hum Genet 138:881–898. https://doi.org/10.1007/s00439-018-1934-8
Hinton RB, Martin LJ, Rame-Gowda S, Tabangin ME, Cripe LH, Benson DW (2009) Hypoplastic left heart syndrome links to chromosomes 10q and 6q and is genetically related to bicuspid aortic valve. J Am Coll Cardiol 53:1065–1071. https://doi.org/10.1016/j.jacc.2008.12.023
Hirst AE Jr, Johns VJ Jr, Kime SW Jr (1958) Dissecting aneurysm of the aorta: a review of 505 cases. Med (baltim) 37:217–279. https://doi.org/10.1097/00005792-195809000-00003
Hoffman JI, Kaplan S (2002) The incidence of congenital heart disease. J Am Coll Cardiol 39:1890–1900. https://doi.org/10.1016/s0735-1097(02)01886-7
Hortop J, Tsipouras P, Hanley JA, Maron BJ, Shapiro JR (1986) Cardiovascular involvement in osteogenesis imperfecta. Circulation 73:54–61. https://doi.org/10.1161/01.cir.73.1.54
Jia H, Dai J, Hou J, Xing L, Ma L, Liu H, Xu M, Yao Y, Hu S, Yamamoto E, Lee H, Zhang S, Yu B, Jang IK (2017) Effective anti-thrombotic therapy without stenting: intravascular optical coherence tomography-based management in plaque erosion (the EROSION study). Eur Heart J 38:792–800. https://doi.org/10.1093/eurheartj/ehw381
Jilaihawi H, Chen M, Webb J, Himbert D, Ruiz CE, Rodes-Cabau J, Pache G, Colombo A, Nickenig G, Lee M, Tamburino C, Sievert H, Abramowitz Y, Tarantini G, Alqoofi F, Chakravarty T, Kashif M, Takahashi N, Kazuno Y, Maeno Y, Kawamori H, Chieffo A, Blanke P, Dvir D, Ribeiro HB, Feng Y, Zhao ZG, Sinning JM, Kliger C, Giustino G, Pajerski B, Imme S, Grube E, Leipsic J, Vahanian A, Michev I, Jelnin V, Latib A, Cheng W, Makkar R (2016) A bicuspid aortic valve imaging classification for the TAVR era. JACC Cardiovasc Imaging 9:1145–1158. https://doi.org/10.1016/j.jcmg.2015.12.022
Jondeau G, Ropers J, Regalado E, Braverman A, Evangelista A, Teixedo G, De Backer J, Muino-Mosquera L, Naudion S, Zordan C, Morisaki T, Morisaki H, Von Kodolitsch Y, Dupuis-Girod S, Morris SA, Jeremy R, Odent S, Ades LC, Bakshi M, Holman K, LeMaire S, Milleron O, Langeois M, Spentchian M, Aubart M, Boileau C, Pyeritz R, Milewicz DM, Montalcino Aortic C (2016) International registry of patients carrying TGFBR1 or TGFBR2 mutations: results of the MAC (Montalcino Aortic Consortium). Circ Cardiovasc Genet 9:548–558. https://doi.org/10.1161/CIRCGENETICS.116.001485
Le Tourneau T, Le Scouarnec S, Cueff C, Bernstein D, Aalberts JJJ, Lecointe S, Merot J, Bernstein JA, Oomen T, Dina C, Karakachoff M, Desal H, Al Habash O, Delling FN, Capoulade R, Suurmeijer AJH, Milan D, Norris RA, Markwald R, Aikawa E, Slaugenhaupt SA, Jeunemaitre X, Hagege A, Roussel JC, Trochu JN, Levine RA, Kyndt F, Probst V, Le Marec H, Schott JJ (2018a) New insights into mitral valve dystrophy: a Filamin-A genotype-phenotype and outcome study. Eur Heart J 39:1269–1277. https://doi.org/10.1093/eurheartj/ehx505
Le Tourneau T, Merot J, Rimbert A, Le Scouarnec S, Probst V, Le Marec H, Levine RA, Schott JJ (2018b) Genetics of syndromic and non-syndromic mitral valve prolapse. Heart 104:978–984. https://doi.org/10.1136/heartjnl-2017-312420
Lee B, Godfrey M, Vitale E, Hori H, Mattei MG, Sarfarazi M, Tsipouras P, Ramirez F, Hollister DW (1991) Linkage of Marfan syndrome and a phenotypically related disorder to two different fibrillin genes. Nature 352:330–334. https://doi.org/10.1038/352330a0
Leopold JA, Loscalzo J (2018) Emerging role of precision medicine in cardiovascular disease. Circ Res 122:1302–1315. https://doi.org/10.1161/CIRCRESAHA.117.310782
Libby P (2015) Triglycerides on the rise: should we swap seats on the seesaw? Eur Heart J 36:774–776. https://doi.org/10.1093/eurheartj/ehu500
Loeys BL, Chen J, Neptune ER, Judge DP, Podowski M, Holm T, Meyers J, Leitch CC, Katsanis N, Sharifi N, Xu FL, Myers LA, Spevak PJ, Cameron DE, De Backer J, Hellemans J, Chen Y, Davis EC, Webb CL, Kress W, Coucke P, Rifkin DB, De Paepe AM, Dietz HC (2005) A syndrome of altered cardiovascular, craniofacial, neurocognitive and skeletal development caused by mutations in TGFBR1 or TGFBR2. Nat Genet 37:275–281. https://doi.org/10.1038/ng1511
Loeys BL, Schwarze U, Holm T, Callewaert BL, Thomas GH, Pannu H, De Backer JF, Oswald GL, Symoens S, Manouvrier S, Roberts AE, Faravelli F, Greco MA, Pyeritz RE, Milewicz DM, Coucke PJ, Cameron DE, Braverman AC, Byers PH, De Paepe AM, Dietz HC (2006) Aneurysm syndromes caused by mutations in the TGF-beta receptor. N Engl J Med 355:788–798. https://doi.org/10.1056/NEJMoa055695
Mangold A, Alias S, Scherz T, Hofbauer T, Jakowitsch J, Panzenbock A, Simon D, Laimer D, Bangert C, Kammerlander A, Mascherbauer J, Winter MP, Distelmaier K, Adlbrecht C, Preissner KT, Lang IM (2015) Coronary neutrophil extracellular trap burden and deoxyribonuclease activity in ST-elevation acute coronary syndrome are predictors of ST-segment resolution and infarct size. Circ Res 116:1182–1192. https://doi.org/10.1161/CIRCRESAHA.116.304944
Maron BJ (1997) Hypertrophic cardiomyopathy. Lancet 350:127–133. https://doi.org/10.1016/S0140-6736(97)01282-8
Maron BJ, McKenna WJ, Danielson GK, Kappenberger LJ, Kuhn HJ, Seidman CE, Shah PM, Spencer WH 3rd, Spirito P, Ten Cate FJ, Wigle ED (2003) American College of Cardiology/European Society of Cardiology Clinical Expert Consensus Document on Hypertrophic Cardiomyopathy. A report of the American College of Cardiology Foundation Task Force on Clinical Expert Consensus Documents and the European Society of Cardiology Committee for Practice Guidelines. Eur Heart J 24:1965–1991. https://doi.org/10.1016/s0195-668x(03)00479-2
Maron BJ, Towbin JA, Thiene G, Antzelevitch C, Corrado D, Arnett D, Moss AJ, Seidman CE, Young JB, American Heart A, Council on Clinical Cardiology HF, Transplantation C, Quality of C, Outcomes R, Functional G, Translational Biology Interdisciplinary Working G, Council on E and Prevention (2006) Contemporary definitions and classification of the cardiomyopathies: an American Heart Association Scientific Statement from the Council on Clinical Cardiology, Heart Failure and Transplantation Committee; Quality of Care and Outcomes Research and Functional Genomics and Translational Biology Interdisciplinary Working Groups; and Council on Epidemiology and Prevention. Circulation 113:1807–1816. https://doi.org/10.1161/CIRCULATIONAHA.106.174287
Martinez-Legazpi P, Bermejo J, Benito Y, Yotti R, Perez Del Villar C, Gonzalez-Mansilla A, Barrio A, Villacorta E, Sanchez PL, Fernandez-Aviles F, del Alamo JC (2014) Contribution of the diastolic vortex ring to left ventricular filling. J Am Coll Cardiol 64:1711–1721. https://doi.org/10.1016/j.jacc.2014.06.1205
Meschini V, Mittal R, Verzicco R (2021) Systolic anterior motion in hypertrophic cardiomyopathy: a fluid–structure interaction computational model. Theoret Comput Fluid Dyn. https://doi.org/10.1007/s00162-021-00564-0
Meuwese MC, de Groot E, Duivenvoorden R, Trip MD, Ose L, Maritz FJ, Basart DC, Kastelein JJ, Habib R, Davidson MH, Zwinderman AH, Schwocho LR, Stein EA, Investigators C (2009) ACAT inhibition and progression of carotid atherosclerosis in patients with familial hypercholesterolemia: the CAPTIVATE randomized trial. JAMA 301:1131–1139. https://doi.org/10.1001/jama.301.11.1131
Morton AC, Rothman AM, Greenwood JP, Gunn J, Chase A, Clarke B, Hall AS, Fox K, Foley C, Banya W, Wang D, Flather MD, Crossman DC (2015) The effect of interleukin-1 receptor antagonist therapy on markers of inflammation in non-ST elevation acute coronary syndromes: the MRC-ILA Heart Study. Eur Heart J 36:377–384. https://doi.org/10.1093/eurheartj/ehu272
Muchtar E, Blauwet LA, Gertz MA (2017) Restrictive cardiomyopathy: genetics, pathogenesis, clinical manifestations, diagnosis, and therapy. Circ Res 121:819–837. https://doi.org/10.1161/CIRCRESAHA.117.310982
Ng SB, Turner EH, Robertson PD, Flygare SD, Bigham AW, Lee C, Shaffer T, Wong M, Bhattacharjee A, Eichler EE, Bamshad M, Nickerson DA, Shendure J (2009) Targeted capture and massively parallel sequencing of 12 human exomes. Nature 461:272–276. https://doi.org/10.1038/nature08250
Peterss S, Mansour AM, Ross JA, Vaitkeviciute I, Charilaou P, Dumfarth J, Fang H, Ziganshin BA, Rizzo JA, Adeniran AJ, Elefteriades JA (2016) Changing pathology of the thoracic aorta from acute to chronic dissection: literature review and insights. J Am Coll Cardiol 68:1054–1065. https://doi.org/10.1016/j.jacc.2016.05.091
Ponikowski P, Voors AA, Anker SD, Bueno H, Cleland JG, Coats AJ, Falk V, Gonzalez-Juanatey JR, Harjola VP, Jankowska EA, Jessup M, Linde C, Nihoyannopoulos P, Parissis JT, Pieske B, Riley JP, Rosano GM, Ruilope LM, Ruschitzka F, Rutten FH, van der Meer P, Authors/Task force M., and Document, R (2016) 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: the Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). Developed with the special contribution of the Heart Failure Association (HFA) of the ESC. Eur J Heart Fail 18:891–975. https://doi.org/10.1002/ejhf.592
Prakash SK, Bosse Y, Muehlschlegel JD, Michelena HI, Limongelli G, Della Corte A, Pluchinotta FR, Russo MG, Evangelista A, Benson DW, Body SC, Milewicz DM, Investigators BA (2014) A roadmap to investigate the genetic basis of bicuspid aortic valve and its complications: insights from the International BAVCon (Bicuspid Aortic Valve Consortium). J Am Coll Cardiol 64:832–839. https://doi.org/10.1016/j.jacc.2014.04.073
Prakash SK, Bondy CA, Maslen CL, Silberbach M, Lin AE, Perrone L, Limongelli G, Michelena HI, Bossone E, Citro R, Bavcon Investigators GRI, Lemaire SA, Body SC, Milewicz DM (2016) Autosomal and X chromosome structural variants are associated with congenital heart defects in Turner syndrome: The NHLBI GenTAC registry. Am J Med Genet A 170:3157–3164. https://doi.org/10.1002/ajmg.a.37953
Prunier F, Terrien G, Le Corre Y, Apana AL, Biere L, Kauffenstein G, Furber A, Bergen AA, Gorgels TG, Le Saux O, Leftheriotis G, Martin L (2013) Pseudoxanthoma elasticum: cardiac findings in patients and Abcc6-deficient mouse model. PLoS ONE 8:e68700. https://doi.org/10.1371/journal.pone.0068700
Putnam AJ, Kebed K, Mor-Avi V, Rashedi N, Sun D, Patel B, Balkhy H, Lang RM, Patel AR (2020) Prevalence of mitral annular disjunction in patients with mitral valve prolapse and severe regurgitation. Int J Cardiovasc Imaging 36:1363–1370. https://doi.org/10.1007/s10554-020-01818-4
Reul GJ, Cooley DA, Hallman GL, Reddy SB, Kyger ER 3rd, Wukasch DC (1975) Dissecting aneurysm of the descending aorta. Improved surgical results in 91 patients. Arch Surg 110:632–640. https://doi.org/10.1001/archsurg.1975.01360110178030
Richardson P, McKenna W, Bristow M, Maisch B, Mautner B, O’Connell J, Olsen E, Thiene G, Goodwin J, Gyarfas I, Martin I, Nordet P (1996) Report of the 1995 World Health Organization/International society and federation of cardiology task force on the definition and classification of cardiomyopathies. Circulation 93:841–842. https://doi.org/10.1161/01.cir.93.5.841
Roberts WC (1970) The congenitally bicuspid aortic valve. A study of 85 autopsy cases. Am J Cardiol 26:72–83. https://doi.org/10.1016/0002-9149(70)90761-7
Roman MJ, Devereux RB, Kramer-Fox R, Spitzer MC (1989) Comparison of cardiovascular and skeletal features of primary mitral valve prolapse and Marfan syndrome. Am J Cardiol 63:317–321. https://doi.org/10.1016/0002-9149(89)90338-x
Roth GA, Johnson C, Abajobir A, Abd-Allah F, Abera SF, Abyu G, Ahmed M, Aksut B, Alam T, Alam K, Alla F, Alvis-Guzman N, Amrock S, Ansari H, Arnlov J, Asayesh H, Atey TM, Avila-Burgos L, Awasthi A, Banerjee A, Barac A, Barnighausen T, Barregard L, Bedi N, Belay Ketema E, Bennett D, Berhe G, Bhutta Z, Bitew S, Carapetis J, Carrero JJ, Malta DC, Castaneda-Orjuela CA, Castillo-Rivas J, Catala-Lopez F, Choi JY, Christensen H, Cirillo M, Cooper L Jr, Criqui M, Cundiff D, Damasceno A, Dandona L, Dandona R, Davletov K, Dharmaratne S, Dorairaj P, Dubey M, Ehrenkranz R, El Sayed Zaki M, Faraon EJA, Esteghamati A, Farid T, Farvid M, Feigin V, Ding EL, Fowkes G, Gebrehiwot T, Gillum R, Gold A, Gona P, Gupta R, Habtewold TD, Hafezi-Nejad N, Hailu T, Hailu GB, Hankey G, Hassen HY, Abate KH, Havmoeller R, Hay SI, Horino M, Hotez PJ, Jacobsen K, James S, Javanbakht M, Jeemon P, John D, Jonas J, Kalkonde Y, Karimkhani C, Kasaeian A, Khader Y, Khan A, Khang YH, Khera S, Khoja AT, Khubchandani J, Kim D, Kolte D, Kosen S, Krohn KJ, Kumar GA, Kwan GF, Lal DK, Larsson A, Linn S, Lopez A, Lotufo PA, El Razek HMA et al (2017) Global, regional, and national burden of cardiovascular diseases for 10 causes, 1990 to 2015. J Am Coll Cardiol 70:1–25. https://doi.org/10.1016/j.jacc.2017.04.052
Rubegni P, Mondillo S, De Aloe G, Agricola E, Bardelli AM, Fimiani M (2000) Mitral valve prolapse in healthy relatives of patients with familial Pseudoxanthoma elasticum. Am J Cardiol 85:1268–1271. https://doi.org/10.1016/s0002-9149(00)00745-1
Sabet HY, Edwards WD, Tazelaar HD, Daly RC (1999) Congenitally bicuspid aortic valves: a surgical pathology study of 542 cases (1991 through 1996) and a literature review of 2,715 additional cases. Mayo Clin Proc 74:14–26. https://doi.org/10.4065/74.1.14
Safi HJ (1999) How I do it: thoracoabdominal aortic aneurysm graft replacement. Cardiovasc Surg 7:607–613. https://doi.org/10.1016/s0967-2109(99)00039-3
Schepers D, Tortora G, Morisaki H, MacCarrick G, Lindsay M, Liang D, Mehta SG, Hague J, Verhagen J, van de Laar I, Wessels M, Detisch Y, van Haelst M, Baas A, Lichtenbelt K, Braun K, van der Linde D, Roos-Hesselink J, McGillivray G, Meester J, Maystadt I, Coucke P, El-Khoury E, Parkash S, Diness B, Risom L, Scurr I, Hilhorst-Hofstee Y, Morisaki T, Richer J, Desir J, Kempers M, Rideout AL, Horne G, Bennett C, Rahikkala E, Vandeweyer G, Alaerts M, Verstraeten A, Dietz H, Van Laer L, Loeys B (2018) A mutation update on the LDS-associated genes TGFB2/3 and SMAD2/3. Hum Mutat 39:621–634. https://doi.org/10.1002/humu.23407
Schuster SC (2008) Next-generation sequencing transforms today’s biology. Nat Methods 5:16–18. https://doi.org/10.1038/nmeth1156
Schweizer PA, Schroter J, Greiner S, Haas J, Yampolsky P, Mereles D, Buss SJ, Seyler C, Bruehl C, Draguhn A, Koenen M, Meder B, Katus HA, Thomas D (2014) The symptom complex of familial sinus node dysfunction and myocardial noncompaction is associated with mutations in the HCN4 channel. J Am Coll Cardiol 64:757–767. https://doi.org/10.1016/j.jacc.2014.06.1155
Shah AM, Pfeffer MA (2012) The many faces of heart failure with preserved ejection fraction. Nat Rev Cardiol 9:555–556. https://doi.org/10.1038/nrcardio.2012.123
Shah PK, Chyu KY, Dimayuga PC, Nilsson J (2014a) Vaccine for atherosclerosis. J Am Coll Cardiol 64:2779–2791. https://doi.org/10.1016/j.jacc.2014.10.018
Shah SJ, Katz DH, Deo RC (2014b) Phenotypic spectrum of heart failure with preserved ejection fraction. Heart Fail Clin 10:407–418. https://doi.org/10.1016/j.hfc.2014.04.008
Sievers HH, Schmidtke C (2007) A classification system for the bicuspid aortic valve from 304 surgical specimens. J Thorac Cardiovasc Surg 133:1226–1233. https://doi.org/10.1016/j.jtcvs.2007.01.039
Siu SC, Silversides CK (2010) Bicuspid aortic valve disease. J Am Coll Cardiol 55:2789–2800. https://doi.org/10.1016/j.jacc.2009.12.068
Tang X, Chen W, Zeng Z, Ding K, Zhou Z (2020) An ontology-based classification of Ebstein’s anomaly and its implications in clinical adverse outcomes. Int J Cardiol 316:79–86. https://doi.org/10.1016/j.ijcard.2020.04.073
Triposkiadis F, Butler J, Abboud FM, Armstrong PW, Adamopoulos S, Atherton JJ, Backs J, Bauersachs J, Burkhoff D, Bonow RO, Chopra VK, de Boer RA, de Windt L, Hamdani N, Hasenfuss G, Heymans S, Hulot JS, Konstam M, Lee RT, Linke WA, Lunde IG, Lyon AR, Maack C, Mann DL, Mebazaa A, Mentz RJ, Nihoyannopoulos P, Papp Z, Parissis J, Pedrazzini T, Rosano G, Rouleau J, Seferovic PM, Shah AM, Starling RC, Tocchetti CG, Trochu JN, Thum T, Zannad F, Brutsaert DL, Segers VF, De Keulenaer GW (2019) The continuous heart failure spectrum: moving beyond an ejection fraction classification. Eur Heart J 40:2155–2163. https://doi.org/10.1093/eurheartj/ehz158
Urbanski PP, Wagner M (2016) Acute non-A-non-B aortic dissection: surgical or conservative approach? Eur J Cardiothorac Surg 49:1249–1254. https://doi.org/10.1093/ejcts/ezv301
van de Laar IM, Oldenburg RA, Pals G, Roos-Hesselink JW, de Graaf BM, Verhagen JM, Hoedemaekers YM, Willemsen R, Severijnen LA, Venselaar H, Vriend G, Pattynama PM, Collee M, Majoor-Krakauer D, Poldermans D, Frohn-Mulder IM, Micha D, Timmermans J, Hilhorst-Hofstee Y, Bierma-Zeinstra SM, Willems PJ, Kros JM, Oei EH, Oostra BA, Wessels MW, Bertoli-Avella AM (2011) Mutations in SMAD3 cause a syndromic form of aortic aneurysms and dissections with early-onset osteoarthritis. Nat Genet 43:121–126. https://doi.org/10.1038/ng.744
van de Laar IM, van der Linde D, Oei EH, Bos PK, Bessems JH, Bierma-Zeinstra SM, van Meer BL, Pals G, Oldenburg RA, Bekkers JA, Moelker A, de Graaf BM, Matyas G, Frohn-Mulder IM, Timmermans J, Hilhorst-Hofstee Y, Cobben JM, Bruggenwirth HT, van Laer L, Loeys B, De Backer J, Coucke PJ, Dietz HC, Willems PJ, Oostra BA, De Paepe A, Roos-Hesselink JW, Bertoli-Avella AM, Wessels MW (2012) Phenotypic spectrum of the SMAD3-related aneurysms-osteoarthritis syndrome. J Med Genet 49:47–57. https://doi.org/10.1136/jmedgenet-2011-100382
van der Linde D, van de Laar IM, Bertoli-Avella AM, Oldenburg RA, Bekkers JA, Mattace-Raso FU, van den Meiracker AH, Moelker A, van Kooten F, Frohn-Mulder IM, Timmermans J, Moltzer E, Cobben JM, van Laer L, Loeys B, De Backer J, Coucke PJ, De Paepe A, Hilhorst-Hofstee Y, Wessels MW, Roos-Hesselink JW (2012) Aggressive cardiovascular phenotype of aneurysms-osteoarthritis syndrome caused by pathogenic SMAD3 variants. J Am Coll Cardiol 60:397–403. https://doi.org/10.1016/j.jacc.2011.12.052
Van Praagh S, Truman T, Firpo A, Bano-Rodrigo A, Fried R, McManus B, Engle MA, Van Praagh R (1989) Cardiac malformations in trisomy-18: a study of 41 postmortem cases. J Am Coll Cardiol 13:1586–1597. https://doi.org/10.1016/0735-1097(89)90353-7
Verdonschot JAJ, Merlo M, Dominguez F, Wang P, Henkens M, Adriaens ME, Hazebroek MR, Mase M, Escobar LE, Cobas-Paz R, Derks KWJ, van den Wijngaard A, Krapels IPC, Brunner HG, Sinagra G, Garcia-Pavia P, Heymans SRB (2020) Phenotypic clustering of dilated cardiomyopathy patients highlights important pathophysiological differences. Eur Heart J. https://doi.org/10.1093/eurheartj/ehaa841
Wang J, Wang Y, Zou Y, Sun K, Wang Z, Ding H, Yuan J, Wei W, Hou Q, Wang H, Liu X, Zhang H, Ji Y, Zhou X, Sharma RK, Wang D, Ahmad F, Hui R, Song L (2014) Malignant effects of multiple rare variants in sarcomere genes on the prognosis of patients with hypertrophic cardiomyopathy. Eur J Heart Fail 16:950–957. https://doi.org/10.1002/ejhf.144
Yagi H, Furutani Y, Hamada H, Sasaki T, Asakawa S, Minoshima S, Ichida F, Joo K, Kimura M, Imamura S, Kamatani N, Momma K, Takao A, Nakazawa M, Shimizu N, Matsuoka R (2003) Role of TBX1 in human del22q11.2 syndrome. Lancet 362:1366–1373. https://doi.org/10.1016/s0140-6736(03)14632-6
Zhou M, Wang H, Zeng X, Yin P, Zhu J, Chen W, Li X, Wang L, Wang L, Liu Y, Liu J, Zhang M, Qi J, Yu S, Afshin A, Gakidou E, Glenn S, Krish VS, Miller-Petrie MK, Mountjoy-Venning WC, Mullany EC, Redford SB, Liu H, Naghavi M, Hay SI, Wang L, Murray CJL, Liang X (2019) Mortality, morbidity, and risk factors in China and its provinces, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 394:1145–1158. https://doi.org/10.1016/S0140-6736(19)30427-1
Zimmer S, Grebe A, Bakke SS, Bode N, Halvorsen B, Ulas T, Skjelland M, De Nardo D, Labzin LI, Kerksiek A, Hempel C, Heneka MT, Hawxhurst V, Fitzgerald ML, Trebicka J, Bjorkhem I, Gustafsson JA, Westerterp M, Tall AR, Wright SD, Espevik T, Schultze JL, Nickenig G, Lutjohann D, Latz E (2016) Cyclodextrin promotes atherosclerosis regression via macrophage reprogramming. Sci Transl Med 8:333ra50. https://doi.org/10.1126/scitranslmed.aad6100
This study was supported by Shanghai Municipal Science and Technology Major Project (2017SHZDZX01).
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HZ performed the literature survey and wrote the manuscript, XH corrected the manuscript, JS provided the theme and guided the manuscript writing.
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Zhang, H., Hua, X. & Song, J. Phenotypes of Cardiovascular Diseases: Current Status and Future Perspectives. Phenomics (2021). https://doi.org/10.1007/s43657-021-00022-1
- Cardiovascular disease