Cardiovascular disease is the leading cause of death worldwide and premature arterial stiffening is a key contributor to this risk. A large body of evidence now points to arterial stiffness as an independent predictor of cardiovascular events. Stiffness can be assessed by a number of indices and is itself affected by factors including mean arterial pressure, vascular smooth muscle tone and structural elements in the vessel wall, such as elastin and collagen. In addition, aging, hypertension, diabetes and hypercholesterolaemia all exacerbate the stiffening process. Stiffness is highly heritable but, despite a clear genetic basis, the precise molecular pathways regulating stiffness are poorly understood. The present review provides an overview of the current literature and examines the evidence that links genetic factors to arterial wall properties. Although the findings support stiffness as a complex genetic trait, the precise nature of the genes contributing to this are still largely unknown. There are a number of candidate genes and many of these could potentially affect the structure and function of the arterial wall. Indeed, it is likely that genes involving signalling pathways and control of the vessel wall matrix will be as important as those involved in the renin–angiotensin system, adrenergic and other vasoactive systems. Identifying the genes involved is important, since it may suggest new biomarkers as well as provide novel drug targets to reduce arterial stiffness. Current pharmacological intervention is simply to reduce blood pressure, but there are emerging therapies; for example, targeted at breaking collagen cross-links or preventing their formation, which are promising new strategies to reduce arterial stiffness and its associated cardiovascular risk.

INTRODUCTION

Despite over half a century of intensive research, CVD (cardiovascular disease) remains the leading cause of death worldwide. Several important risk factors for CVD have been identified including arterial stiffness. Stiffening of the large arteries is detrimental for several reasons. First, it increases cardiac afterload that drives left ventricular hypertrophy [1], which is itself an independent predictor of CV (cardiovascular) and overall mortality [2]. It also reduces coronary artery perfusion, due to the fall in diastolic pressure, and the resulting ischaemia of the myocardium probably contributes to the development of heart failure in older individuals with arterial stiffening [3,4]. The increase in PP (pulse pressure) with stiffening also hastens the degeneration of the elastic elements of the arterial wall, thus accelerating the process of arteriosclerosis itself. Increased stiffness also promotes atheroma formation [5,6] and vascular remodelling (leading to carotid intima-media thickening) [7], which may be the direct result of reduced shear stress and, hence, bioavailable NO [8,9].

Arterial stiffness, simply defined as hardening of the arteries, can be assessed by a number of measures such as aortic PWV (pulse wave velocity) and stiffness index; indices of arterial wall structure such as IMT (intima-media thickness), as well as the systemic arterial compliance and distensibility; aortic AIx (augmentation index), a composite measure of wave reflection and systemic arterial stiffness, and brachial PP (Table 1). As the arterial tree is so heterogeneous, there is no single modus operandi to determine arterial stiffness; however, most persuasive direct evidence for arterial stiffness has been provided by assessment of aortic PWV in a broad cross-section of individuals. Aortic PWV, therefore, is an independent predictor of CV mortality in subjects with renal failure [1012], hypertension [1315] and diabetes [16] and in unselected middle-aged/older adults [1721], suggesting that stiffness may be an important therapeutic target [22].

Table 1
Indices used for determining regional, local and systemic arterial stiffness

*Also requires pressure measurements. P, pressure; D, diameter; h, wall thickness; t, time; s, systolic; d, diastolic.

IndexDefinition
Regional stiffness Aortic PWV Velocity of travel of the pulse along a length of artery: distance/Δt (m/s) 
 Stiffness index (β)* Ratio of logarithm (systolic/diastolic BPs) to (relative changes in diameter): β=ln(Ps/Pd)/(Ds−Dd)/D
Local stiffness Arterial distensibility* Relative change in diameter (or area) for a given pressure change; inverse of elastic modulus: ΔD/(ΔP×D) (mmHg−1
 Arterial compliance* Absolute diameter (or area) change for a given pressure step: ΔDP (mmHg or cm2/mmHg) 
 Elastic modulus* Pressure change required for a theoretical 100% stretch from resting diameter: (ΔP×D)/ΔD (mmHg) 
 Young's elastic modulus* Elastic modulus per unit area: (ΔP×D)/ΔD×h2 (mmHg/cm2
Systemic stiffness AIx Difference between second and first systolic peaks as a percentage of PP: [(P2−P1)/PP]×100 
IndexDefinition
Regional stiffness Aortic PWV Velocity of travel of the pulse along a length of artery: distance/Δt (m/s) 
 Stiffness index (β)* Ratio of logarithm (systolic/diastolic BPs) to (relative changes in diameter): β=ln(Ps/Pd)/(Ds−Dd)/D
Local stiffness Arterial distensibility* Relative change in diameter (or area) for a given pressure change; inverse of elastic modulus: ΔD/(ΔP×D) (mmHg−1
 Arterial compliance* Absolute diameter (or area) change for a given pressure step: ΔDP (mmHg or cm2/mmHg) 
 Elastic modulus* Pressure change required for a theoretical 100% stretch from resting diameter: (ΔP×D)/ΔD (mmHg) 
 Young's elastic modulus* Elastic modulus per unit area: (ΔP×D)/ΔD×h2 (mmHg/cm2
Systemic stiffness AIx Difference between second and first systolic peaks as a percentage of PP: [(P2−P1)/PP]×100 

Arterial stiffness is determined by a number of factors, including structural elements within the arterial wall, vascular smooth muscle tone and mean arterial pressure. Arteries stiffen with age from loss of elastin protein, as well as fatigue-fracture of the elastic fibres and calcification of the vessel wall. Smooth muscle tone also influences the stiffness of the large arteries, which may help explain why accelerated or ‘premature’ arterial stiffening is seen in diabetes [2326], cigarette smoking [27] and hypercholesterolaemia [2830], before the development of obvious atheroma. However, the balance between structural and functional mechanisms involved is unclear and probably dynamic.

ARTERIAL STIFFNESS AS AN INHERITABLE TRAIT

Arterial stiffness is now considered a complex trait in the same way that hypertension, diabetes mellitus and obesity are modelled. Since the first pioneering Bogalusa Heart Study in 1986 [31], many studies using a variety of approaches (family, twin, genome-wide scans and candidate gene) support a substantial role for familial factors. Arterial stiffness is, in part, heritable and independent of BP (blood pressure), heart rate, height and other CV risk factors. Indeed, many studies have provided significant evidence for heritability estimates for vascular phenotypes, such as stiffness index, distensibility, carotid wall structure, AIx, aortic PWV and PP. Similarly, genotyping studies using candidate genes and genome scans have supported a genetic basis for stiffness. Nevertheless, the extent to which arterial stiffness is genetically determined and/or the precise molecular pathways regulating the arterial wall properties in humans are largely unclear.

In the present review, the current knowledge about these genetic factors will be discussed, as will be the potential molecular basis that underlies their involvement in arterial stiffening, particularly as it relates to the growth of arteries, the structure and remodelling of the extracellular matrix, and the interactions that occur between the extracellular matrix and the cellular components of the artery. The evidence is presented in three main sections: first the heritability and family findings, followed by studies on candidate genes and finally genome-wide scans. Tables 2–4 summarize current findings that support the role of a genetic basis to vascular phenotypes.

Table 2
Heritability studies of arterial stiffness phenotypes

*Adjusted for age, sex, diabetes status, mean arterial pressure, hypertension and smoking status; †adjusted for age, sex, diabetes status, impaired glucose tolerance, smoking status, cholesterol, body surface area and hypertension; ‡adjusted for age and sex; §adjusted for age, sex, systolic BP, number of cigarettes/day, total cholesterol, HDL (high-density lipoprotein)-cholesterol, triacylglycerols (triglycerides), diabetes status, BMI, antihypertensive treatment, menopausal status and hormone replacement therapy; ¶adjusted for traditional risk factors; ¶adjusted for age, age2, sex and BMI; **adjusted for age, sex and BMI; ††adjusted for age, ethnicity, sex and their interaction; ‡‡adjusted for age, sex, height, diabetes status and mean arterial pressure; §§adjusted for age, age2, sex, BMI, field centre and age–sex and age2–sex interactions. −, unknown.

PhenotypeStudy sampleSample size (age)Heritability estimateReference
IMT     
 Family study 76 family participants (−) 0.30 Zannad et al. [36
 Strong Heart Family Study 950 subjects in 32 extended families (42 years) 0.21† North et al. [37
 Family study 252 participants from 122 families (60.6 years) 0.32 Lange et al. [38
 Twin study 98 monozygotic and dizygotic twins (54.3 and 51.7 years) 0.31 Swan et al. [39
 Framingham Offspring Study 906 men and 980 women from 586 extended families (57 years) 0.38§ Fox et al. [40
 Twin study 264 monzygotic and dizygotic twins (53 years) 0.59∥ Zhao et al. [41
 Erasmus Rucphen Family Study 930 participants (52 years) 0.41 Sayad-Tabatabaei et al. [42
Stiffness index (β)     
 Strong Heart Family Study 950 subjects in 32 extended families (42 years) 0.23† North et al. [37
 Northern Manhattan Study 605 relatives from 88 families (46.9 years) 0.20 Juo et al. [43
Distensibility     
 Northern Manhattan Study 605 relatives from 88 families (46.9 years) 0.17* Juo et al. [43
AIx     
 Twin study 225 and 594 monozygotic and dizygotic twins (45 years) 0.37 Snieder et al. [44
 Strong Heart Family Study 950 subjects in 32 extended families (42 years) 0.18† North et al. [37
Forward and reflected wave amplitudes     
 Framingham Offspring Study 1480 participants in 817 pedigrees (60 years) 0.21 and 0.48 Mitchell et al. [45
PWV     
 Aortic Erasmus Rucphen Family Study 930 participants (52 years) 0.36‡ Sayad-Tabatabaei et al. [42
 Aortic Framingham Offspring Study 1480 participants in 817 pedigrees (60 years) 0.40 Mitchell et al. [45
 Radial and foot Twin study 702 monozygotic and dizygotic twins (17.7 years) 0.43 and 0.53 Ge et al. [46
PP     
 Family study 440 men and women in 10 families (40–60 years) 0.21¶ Atwood et al. [48
 Family study 1825 in 528 pedigrees (34.3 years) 0.13** Adeyemo et al. [49
 Twin study 308 European-American and 226 African American twin pairs (14.7 years) 0.54†† Snieder et al. [50
 Family study 1454 men and women in 26 pedigrees (27.8 years) 0.25¶ Camp et al. [51
 Framingham Study 6421 individuals in 1593 families (−) 0.52 DeStefano et al. [52
 Diabetes Heart Study 950 men and women in 367 pedigrees (61.2 years) 0.40‡‡ Hsu et al. [53
 Insulin Resistance Atherosclerosis Family Study 1856 men and women in 132 pedigrees (42.8 years) 0.22‡‡ Hsu et al. [53
 NHLBI Family Heart Study 2761 men and women in 393 pedigrees (50 years) 0.19‡‡ Hsu et al. [53
 Family Blood Pressure Program 10789 men and women of different ethnic groups (−) 0.29** Bielinski et al. [54
   1612 Mexican American men and women (55 years) 0.31§§  
   3667 white men and women (53 years) 0.25§§  
   1557 Asian men and women (51 years) 0.31§§  
   3962 men and women (51 years) 0.33§§  
 Subjects with hypertension and normotension 3962 men and women (−) 0.37‡ and 0.53 Bochud et al. [55
PhenotypeStudy sampleSample size (age)Heritability estimateReference
IMT     
 Family study 76 family participants (−) 0.30 Zannad et al. [36
 Strong Heart Family Study 950 subjects in 32 extended families (42 years) 0.21† North et al. [37
 Family study 252 participants from 122 families (60.6 years) 0.32 Lange et al. [38
 Twin study 98 monozygotic and dizygotic twins (54.3 and 51.7 years) 0.31 Swan et al. [39
 Framingham Offspring Study 906 men and 980 women from 586 extended families (57 years) 0.38§ Fox et al. [40
 Twin study 264 monzygotic and dizygotic twins (53 years) 0.59∥ Zhao et al. [41
 Erasmus Rucphen Family Study 930 participants (52 years) 0.41 Sayad-Tabatabaei et al. [42
Stiffness index (β)     
 Strong Heart Family Study 950 subjects in 32 extended families (42 years) 0.23† North et al. [37
 Northern Manhattan Study 605 relatives from 88 families (46.9 years) 0.20 Juo et al. [43
Distensibility     
 Northern Manhattan Study 605 relatives from 88 families (46.9 years) 0.17* Juo et al. [43
AIx     
 Twin study 225 and 594 monozygotic and dizygotic twins (45 years) 0.37 Snieder et al. [44
 Strong Heart Family Study 950 subjects in 32 extended families (42 years) 0.18† North et al. [37
Forward and reflected wave amplitudes     
 Framingham Offspring Study 1480 participants in 817 pedigrees (60 years) 0.21 and 0.48 Mitchell et al. [45
PWV     
 Aortic Erasmus Rucphen Family Study 930 participants (52 years) 0.36‡ Sayad-Tabatabaei et al. [42
 Aortic Framingham Offspring Study 1480 participants in 817 pedigrees (60 years) 0.40 Mitchell et al. [45
 Radial and foot Twin study 702 monozygotic and dizygotic twins (17.7 years) 0.43 and 0.53 Ge et al. [46
PP     
 Family study 440 men and women in 10 families (40–60 years) 0.21¶ Atwood et al. [48
 Family study 1825 in 528 pedigrees (34.3 years) 0.13** Adeyemo et al. [49
 Twin study 308 European-American and 226 African American twin pairs (14.7 years) 0.54†† Snieder et al. [50
 Family study 1454 men and women in 26 pedigrees (27.8 years) 0.25¶ Camp et al. [51
 Framingham Study 6421 individuals in 1593 families (−) 0.52 DeStefano et al. [52
 Diabetes Heart Study 950 men and women in 367 pedigrees (61.2 years) 0.40‡‡ Hsu et al. [53
 Insulin Resistance Atherosclerosis Family Study 1856 men and women in 132 pedigrees (42.8 years) 0.22‡‡ Hsu et al. [53
 NHLBI Family Heart Study 2761 men and women in 393 pedigrees (50 years) 0.19‡‡ Hsu et al. [53
 Family Blood Pressure Program 10789 men and women of different ethnic groups (−) 0.29** Bielinski et al. [54
   1612 Mexican American men and women (55 years) 0.31§§  
   3667 white men and women (53 years) 0.25§§  
   1557 Asian men and women (51 years) 0.31§§  
   3962 men and women (51 years) 0.33§§  
 Subjects with hypertension and normotension 3962 men and women (−) 0.37‡ and 0.53 Bochud et al. [55
Table 3
Genetic polymorphisms associated with arterial stiffness phenotypes

+, significant positive association; −, no association. HT, subjects with hypertension; NT, subjects with normotension

Gene (chromosome location)PopulationSample size (age)PolymorphismPhenotypeAssociation (+/−)Reference
Non-matrix gene       
AGT (1q41-q45)       
 Untreated HT n=441 (18–74 years) M235T and T174M Aortic PWV − Lajemi et al. [57
 Untreated HT n=98 (24–80 years) M235T IMT Bozec et al. [58
 Untreated HT n=98 (24–80 years) M235T Distensibility Bozec et al. [59
ACE (17q23)       
 Untreated HT n=441 (18–74 years) I/D Aortic PWV − Lajemi et al. [57
 HT and NT n=311 (49 years) and n=128 (44 years) I/D Aortic PWV Benetos et al. [60
 Type II diabetics and NT n=137 (53 years) and n=260 (53 years) I/D Aortic PWV Taniwaki et al. [61
 Untreated HT n=469 (19–85 years) I/D Aortic PWV Safar et al. [62
 Untreated HT n=469 (19–85 years) I/D PP Safar et al. [62
 Healthy men and women n=3001 (72 years) I/D Distensibility Mattace-Raso et al. [63
 Men and women n=756 (45 years) I/D Distensibility Balkestein et al. [64
 Healthy adults and offspring n=622 (<40 years) and n=328 (30 years) I/D AIx − Wojciechowska et al. [65
 FLEMENGHO study n=380 (12–16 years) I/D IMT Balkestein et al. [64
AGTR1 (3q21-q25)       
 Untreated HT n=134 (21–72 years) A1166C Aortic PWV Benetos et al. [66
 HT and NT n=311 (49 years) and n=128 (44 years) A1166C Aortic PWV Benetos et al. [60
 HT n=185 (53 years)  Aortic PWV Gardier et al. [67
 Untreated HT n=429 (18–74 years) A1166C and A153G Aortic PWV Lajemi et al. [57
 Untreated HT n=171 (47 years) A1166C Aortic PWV Mourad et al. [68
 CYP11B2 (8q21-q22)       
 Essential HT n=216 (40 years) C−344T Aortic PWV Pogoja et al. [69
 Untreated HT n=425 (19–85 years)  Aortic PWV Safar et al. [70
 Untreated HT n=441 (18–74 years)  Aortic PWV − Lajemi et al. [57
 Healthy adults and offspring n=622 (<40 years) and n=328 (30 years)  AIx Wojciechowska et al. [65
 Men and women n=756 (45 years)  Distensibility − Balkestein et al. [64
EDN1 (6p24)       
 Untreated HT n=528 (19–79 years) −138I/D Aortic PWV Lajemi et al. [77
EDNRA (4q31)       
 Untreated HT n=528 (19–79 years) A−231G and C1363T Aortic PWV Lajemi et al. [77
EDNRB (13q22)       
 Untreated HT n=528 (19–79 years) G30A Aortic PWV Lajemi et al. [77
GNB3 (12p13)       
 Healthy subjects n=99 (27 years) C825T Aortic PWV and AIx Nurnberger et al. [82
NOS3 (7q35-q36)       
 Young adults n=118 and 285 (25–37 years) G894T (E298D) Petersen's and Young's elastic modulus Chen et al. [87
 Men and women n=553 and 604 (62 years)  PP, aortic PWV, and reflected and forward wave amplitudes Mitchell et al. [88
 HT and NTs n=311 (18–74 years) and n=128 (19–72 years)  Aortic PWV − Lacolley et al. [85
 Untreated HT n=171 (47 years)  Aortic PWV Mourad et al. [68
ADRB2 (5q31-q32)       
 Treated HT n=331 (62 years) Q27E Aortic PWV Yuan et al. [89
 Twin study n=395 European-American and 275 African-American twins (14.6 years) R16G and Q27E PP Sneider et al. [90
Matrix gene       
ELN (7q11.2)       
 Healthy adults n=320 (49 years) S422G (A>G) Distensibility Hanon et al. [98
COL1A (17q21.33)       
 Young healthy adults n=489 (22.6 years) G2064T Arterial compliance Brull et al. [99
 Healthy men n=245 (50–61 years)  PP and aortic stiffness (β) Powell et al. [101
FBN1 (15q21.1)       
 Healthy male first-degree relatives with aortic aneurysm n=79 (28–81 years) VNTR2,3 and 4 Distensibility Powell et al. [100
 Patients with CAD n=145 (62 years)  Carotid PP and impedance Medley et al. [103
 Healthy individuals n=742 (16–83 years)  Aortic PWV, AIx and PP − Yasmin et al. [105
MMP3 (11q23.3)       
 Untreated subjects in two groups n=320 (>60 years and 30–60 years) 5A/6A (−1612del/ins) Aortic impedance Medley et al. [112
MMP9 (20q11.2-q13.1)       
 Patients with CAD n=84 (61 years) C−1562T and R279Q Aortic and characteristic impedance Medley et al. [116
 Healthy individuals n=865 (16–81 years) C−1562T and R279Q Aortic PWV and AIx Yasmin et al. [118
 HT n=215 (46 years) C−1562T Aortic PWV Zhou et al. [117
Gene (chromosome location)PopulationSample size (age)PolymorphismPhenotypeAssociation (+/−)Reference
Non-matrix gene       
AGT (1q41-q45)       
 Untreated HT n=441 (18–74 years) M235T and T174M Aortic PWV − Lajemi et al. [57
 Untreated HT n=98 (24–80 years) M235T IMT Bozec et al. [58
 Untreated HT n=98 (24–80 years) M235T Distensibility Bozec et al. [59
ACE (17q23)       
 Untreated HT n=441 (18–74 years) I/D Aortic PWV − Lajemi et al. [57
 HT and NT n=311 (49 years) and n=128 (44 years) I/D Aortic PWV Benetos et al. [60
 Type II diabetics and NT n=137 (53 years) and n=260 (53 years) I/D Aortic PWV Taniwaki et al. [61
 Untreated HT n=469 (19–85 years) I/D Aortic PWV Safar et al. [62
 Untreated HT n=469 (19–85 years) I/D PP Safar et al. [62
 Healthy men and women n=3001 (72 years) I/D Distensibility Mattace-Raso et al. [63
 Men and women n=756 (45 years) I/D Distensibility Balkestein et al. [64
 Healthy adults and offspring n=622 (<40 years) and n=328 (30 years) I/D AIx − Wojciechowska et al. [65
 FLEMENGHO study n=380 (12–16 years) I/D IMT Balkestein et al. [64
AGTR1 (3q21-q25)       
 Untreated HT n=134 (21–72 years) A1166C Aortic PWV Benetos et al. [66
 HT and NT n=311 (49 years) and n=128 (44 years) A1166C Aortic PWV Benetos et al. [60
 HT n=185 (53 years)  Aortic PWV Gardier et al. [67
 Untreated HT n=429 (18–74 years) A1166C and A153G Aortic PWV Lajemi et al. [57
 Untreated HT n=171 (47 years) A1166C Aortic PWV Mourad et al. [68
 CYP11B2 (8q21-q22)       
 Essential HT n=216 (40 years) C−344T Aortic PWV Pogoja et al. [69
 Untreated HT n=425 (19–85 years)  Aortic PWV Safar et al. [70
 Untreated HT n=441 (18–74 years)  Aortic PWV − Lajemi et al. [57
 Healthy adults and offspring n=622 (<40 years) and n=328 (30 years)  AIx Wojciechowska et al. [65
 Men and women n=756 (45 years)  Distensibility − Balkestein et al. [64
EDN1 (6p24)       
 Untreated HT n=528 (19–79 years) −138I/D Aortic PWV Lajemi et al. [77
EDNRA (4q31)       
 Untreated HT n=528 (19–79 years) A−231G and C1363T Aortic PWV Lajemi et al. [77
EDNRB (13q22)       
 Untreated HT n=528 (19–79 years) G30A Aortic PWV Lajemi et al. [77
GNB3 (12p13)       
 Healthy subjects n=99 (27 years) C825T Aortic PWV and AIx Nurnberger et al. [82
NOS3 (7q35-q36)       
 Young adults n=118 and 285 (25–37 years) G894T (E298D) Petersen's and Young's elastic modulus Chen et al. [87
 Men and women n=553 and 604 (62 years)  PP, aortic PWV, and reflected and forward wave amplitudes Mitchell et al. [88
 HT and NTs n=311 (18–74 years) and n=128 (19–72 years)  Aortic PWV − Lacolley et al. [85
 Untreated HT n=171 (47 years)  Aortic PWV Mourad et al. [68
ADRB2 (5q31-q32)       
 Treated HT n=331 (62 years) Q27E Aortic PWV Yuan et al. [89
 Twin study n=395 European-American and 275 African-American twins (14.6 years) R16G and Q27E PP Sneider et al. [90
Matrix gene       
ELN (7q11.2)       
 Healthy adults n=320 (49 years) S422G (A>G) Distensibility Hanon et al. [98
COL1A (17q21.33)       
 Young healthy adults n=489 (22.6 years) G2064T Arterial compliance Brull et al. [99
 Healthy men n=245 (50–61 years)  PP and aortic stiffness (β) Powell et al. [101
FBN1 (15q21.1)       
 Healthy male first-degree relatives with aortic aneurysm n=79 (28–81 years) VNTR2,3 and 4 Distensibility Powell et al. [100
 Patients with CAD n=145 (62 years)  Carotid PP and impedance Medley et al. [103
 Healthy individuals n=742 (16–83 years)  Aortic PWV, AIx and PP − Yasmin et al. [105
MMP3 (11q23.3)       
 Untreated subjects in two groups n=320 (>60 years and 30–60 years) 5A/6A (−1612del/ins) Aortic impedance Medley et al. [112
MMP9 (20q11.2-q13.1)       
 Patients with CAD n=84 (61 years) C−1562T and R279Q Aortic and characteristic impedance Medley et al. [116
 Healthy individuals n=865 (16–81 years) C−1562T and R279Q Aortic PWV and AIx Yasmin et al. [118
 HT n=215 (46 years) C−1562T Aortic PWV Zhou et al. [117
Table 4
Genomic regions associated with PP

H2, heritability; NR, not reported; Sug, suggestive linkage; Sign, significant linkage.*Bivariate relationship between serum creatinine and PP; †PWV; ‡forward and reflected wave amplitudes; §coronary artery calcification.

Mean PP (H2)Study sampleSample size (age)Selection of pedigreesMarkers (n)Type of analysis (LOD score)Evidence of linkageReference
NR (0.21) San Antonio Family Heart Study (Mexican Americans) n=440 (40–60 years) Random 399 Two-point (2.78) Sug: 7q22, 18q23, 21q22 and 8q24.23 Atwood et al. [48
45 (0.25) European descent n=1454 (27.8 years) Early onset CHD deaths, stroke and hypertension 405 Multipoint (>2.5) Sug: 8p21.1, 2q23.1 Camp et al. [51
47 (0.52) Framingham Heart Study (European descent) n=1584 (47.5 years) Random 366 Multipoint (2.94) Sug: 5p13.3, 7q11.22,7q34, 8q24,10q21, 15q26 and 22q12 DeStefano et al. [52
 Family Blood Pressure Program      Bielinski et al. [54
NR (0.33)  Black men and women n=3962 (51 years) Hypertension 391 Multipoint (3.20) Sug: 3q25.3 and 9q13.33  
NR (0.31)  Asian men and women n=1557 (51 years) Hypertension 391 Multipoint (2.70) Sug: 5q33.3  
NR (0.31)  Latino men and women n=1612 (55 years) Hypertension 391 Multipoint (3.6 and 4.4) Sig: 17q23.2 and 20q12  
NR (0.25)  European men and women n=3667 (53 years) Hypertension 391 Multipoint (4.30) Sig: 21q21  
NR HyperGen (African American) n=125 (<60 years) Random 387 Multipoint (3.08) Sug: 1 and 14 Sherva et al. [122
51 (0.40) Framingham Offspring Study n=590 (58 years) Random − Multipoint (2.50) Sug: 1,7,13 and 15† Mitchell et al. [45
     (2.87) Sig: 7; Sug: 3 and 15‡  
     (3.27, 4.93) Sig: 4 and 8‡  
NR GENOA (black and white subjects) n=1351 (63 years) and n=1022 (60 years) Hypertension − Multipoint (3.62)* Sug: 5 Turner et al. [123
NR (0.29) GENOA (non-Hispanic whites) n=233 (60 years) Ischaemic damage 366 Multipoint (4.56, 5.07) Sig: 1p and 16q Turner et al. [124
NR (0.36) GENOA (non-Hispanic whites) n=948 (59.6 years) Random§ 381 Multipoint (>1.30) Sig: 1p,4p,5q, 7q,13q and 14q Turner et al. [125
Mean PP (H2)Study sampleSample size (age)Selection of pedigreesMarkers (n)Type of analysis (LOD score)Evidence of linkageReference
NR (0.21) San Antonio Family Heart Study (Mexican Americans) n=440 (40–60 years) Random 399 Two-point (2.78) Sug: 7q22, 18q23, 21q22 and 8q24.23 Atwood et al. [48
45 (0.25) European descent n=1454 (27.8 years) Early onset CHD deaths, stroke and hypertension 405 Multipoint (>2.5) Sug: 8p21.1, 2q23.1 Camp et al. [51
47 (0.52) Framingham Heart Study (European descent) n=1584 (47.5 years) Random 366 Multipoint (2.94) Sug: 5p13.3, 7q11.22,7q34, 8q24,10q21, 15q26 and 22q12 DeStefano et al. [52
 Family Blood Pressure Program      Bielinski et al. [54
NR (0.33)  Black men and women n=3962 (51 years) Hypertension 391 Multipoint (3.20) Sug: 3q25.3 and 9q13.33  
NR (0.31)  Asian men and women n=1557 (51 years) Hypertension 391 Multipoint (2.70) Sug: 5q33.3  
NR (0.31)  Latino men and women n=1612 (55 years) Hypertension 391 Multipoint (3.6 and 4.4) Sig: 17q23.2 and 20q12  
NR (0.25)  European men and women n=3667 (53 years) Hypertension 391 Multipoint (4.30) Sig: 21q21  
NR HyperGen (African American) n=125 (<60 years) Random 387 Multipoint (3.08) Sug: 1 and 14 Sherva et al. [122
51 (0.40) Framingham Offspring Study n=590 (58 years) Random − Multipoint (2.50) Sug: 1,7,13 and 15† Mitchell et al. [45
     (2.87) Sig: 7; Sug: 3 and 15‡  
     (3.27, 4.93) Sig: 4 and 8‡  
NR GENOA (black and white subjects) n=1351 (63 years) and n=1022 (60 years) Hypertension − Multipoint (3.62)* Sug: 5 Turner et al. [123
NR (0.29) GENOA (non-Hispanic whites) n=233 (60 years) Ischaemic damage 366 Multipoint (4.56, 5.07) Sig: 1p and 16q Turner et al. [124
NR (0.36) GENOA (non-Hispanic whites) n=948 (59.6 years) Random§ 381 Multipoint (>1.30) Sig: 1p,4p,5q, 7q,13q and 14q Turner et al. [125

Family and heritability studies

The Bogalusa Heart Study was the first study to demonstrate greater carotid artery stiffness in adolescents with a parental history of myocardial infarction or diabetes than subjects with no family history [31]. A decade later, we showed AIx, a composite measure of systemic arterial stiffness, to be significantly higher in offspring of families with hypertension than in the controls [32]. This was true even after adjustments for the CV risk factors; however, in that study [32], aortic PWV did not differ between the groups, which suggested the existence of a functional and/or structural decrease in the calibre of small arteries.

Carotid artery IMT is a strong predictor of future myocardial infarction and stroke [3335]. Many studies have examined heritability estimates of various stiffness measures in a number of populations [3646]. For example, Gaeta et al. [47] demonstrated increased IMT, surrogate measure of arterial wall structure/thickness and altered endothelial function in offspring of patients with premature CAD (coronary artery disease) compared with normontensive subjects. This finding was also confirmed in a number of other populations. Studies with heritability estimates and the associated vascular phenotypes are shown in Table 2. As seen in Table 2, moderate heritability estimates ranging from 0.21 to 0.59 are provided for the common carotid IMT in a number of family and twin studies. On the contrary, only three studies reported a heritability estimate for carotid artery distensibility and stiffness index which ranged from 0.17 and 0.23. The Strong Heart Study which included 950 subjects from 32 extended families reported a heritability value of 0.23 for carotid stiffness index [37], whereas the Northern Manhattan Family Study reported a value of 0.17 for distensibility [43].

Twin (both monozygotic and dizygotic) studies are the classic examples to demonstrate familial factors and also investigate the relative contribution of inheritance, environment and combination. As shown in Table 2, using a co-twin case-control analysis in monzygotic and dizygotic female twins, Snieder et al. [44] reported a heritability of 0.37 for AIx. The Strong Heart Study [37] reported a value of 0.18 for AIx, whereas other investigators reported a value of 0.21 and 0.48 for forward and reflected wave amplitudes [45].

Although aortic PWV is an independent determinant of CV risk, only two studies provided heritability estimates for this phenotype. In the Erasmus Rucphen Study [42], the age- and sex-adjusted heritability estimate was 0.36 and this decreased to 0.26 after further adjustments for other confounding factors, whereas, in the Framingham Offspring Study [45], the unadjusted heritability estimate was 0.40.

The heritability of PP, a surrogate measure of stiffness and an independent predictor of CV mortality, has been extensively studied using both twin and family studies in a number of populations [4855]. The heritability estimates reported for PP ranged between 0.13 to 0.54 depending on the population investigated. In a European-American African-American twin study, Snieder et al. [50] reported a value of 0.54, whereas Adeyemo et al. [49] in 1825 pedigrees reported a value of 0.13. Interestingly, in the Family Blood Pressure Program, Bielinski et al. [54] provided a moderate heritability estimate that ranged from 0.25 to 0.33 for PP in different ethnic groups. It has been suggested that estimates derived from extended pedigrees tend to be lower than those based on sib-pairs. To this extent, a more recent study by Hsu et al. [53] provided estimates of 0.40 in siblings compared with 0.22 and 0.19 in two different extended pedigrees. In addition, heritability estimates have also been shown to be higher when multiple measurements averaged over 24 h are recorded compared with a single reading (0.53 compared with 0.37) [55]. In the Framingham Study, DeStefano et al. [52] demonstrated that subjects with long-term average PP had a higher heritability estimate (0.52). The higher heritability estimates in these two studies probably reflect lesser intra-individual variability, providing a more precise measure to this phenotype.

Several studies, as discussed above, examined the extent to which genetic factors contribute to inter-individual differences in arterial stiffness phenotypes, with heritability estimates ranging between 0.13 to 0.54; however, the number and nature of the genes contributing to this are poorly understood.

Candidate gene studies

Over the last two decades, many studies have identified genetic variants to be involved in the pathophysiology of arterial stiffness and association studies examining their effect on stiffening have been published. Table 3 summarizes the influence of genes with their polymorphisms on specific phenotypes. In this section, we have divided the genes into two categories: category 1 includes all non-matrix genes that are involved with cell proliferation and vascular hypertrophy or those that influence the functional properties affecting BP control, such as RAAS (renin–angiotensin–aldosterone system), NOS (NO synthase), β2-AR (β2-adrenoreceptor), ET (endothelin) and its receptors (ETAR and ETBR), and other G-proteins. Category 2 includes genes that are involved with the extracellular matrix or those that modulate structural changes in proteins, such as elastin, collagen, fibrillin etc.

Non-matrix genes

The RAAS, which is involved in BP control, cell proliferation, matrix production and vascular hypertrophy, is thought to have a major role in arterial stiffening [56]. As seen in Table 3, many studies have investigated the association between aortic PWV and AGT (angiotensinogen), ACE (angiotensin-converting enzyme), AGTR1 (angiotensin II type 1 receptor) and CYP11B2 (aldosterone synthase) genes. However, the results are inconsistent, as positive and negative associations are reported [5765]. For example, the AGT polymorphism M235T did not associate with aortic PWV [57], but associated with distensibility [58]. A much larger study by Lajemi et al. [57] in a population with hypertension that included both treated and untreated subjects demonstrated no affect of the T174M polymorphism on aortic stiffness.

Evidence that the ACE [I/D (insertion/deletion)] gene polymorphism may be involved in the process of arterial stiffening is provided by a positive association with aortic PWV in subjects with hypertension [60] and diabetes [61]. More recently, this polymorphism has been demonstrated to independently modulate the age-related increase in PP in males with hypertension [60]. A study by Mattace-Raso et al. [63] also found an association with the common carotid artery distensibility/stiffness in adults under 70 years of age. In the Rotterdam study, the D allele of the ACE gene inversely associated with carotid distensibility in healthy adults [63]. The FLEMENGHO (Flemish Study on Environment Genes and Health Outcomes) study is interesting, as it explored interactions between two or more polymorphisms [64]. In that study, carotid artery stiffness associated with the ACE (I/D) polymorphism, whereas aortic stiffness (PWV) was increased in ACE DD homozygous subjects for α-adducin Gly460 compared with other genotypes. On the other hand, studies on patients with hypertension [57] and healthy adults [65] failed to show any affect of the ACE (I/D) polymorphism on aortic PWV and AIx.

Many studies have examined the role of AGTR1 polymorphisms (A1166C) on aortic PWV in untreated subjects with hypertension [57,60,6668]. Benetos et al. [66] showed that, after adjustments for age, BP and BMI (body mass index), a dose-dependent increase in PWV was seen in individuals harbouring the C allele. These findings were later confirmed in two different populations. In untreated subjects with hypertension, the A1166C and A153G polymorphisms affected the increase in aortic stiffness with age [57].

Furthermore, the T344C polymorphism of CYP11B2 associated with an increase in PWV in some studies [65,69,70], but not all studies [57,64]. Pojoga et al. [69] showed that CC homozygotes had elevated levels of plasma aldosterone compared with TT homozygotes. In addition, individuals harbouring the C allele had a higher degree of arterial stiffening. A more recent study in subjects with hypertension also demonstrated a significant effect of this polymorphism in men only, after adjustments for heart rate and BP [70]. To date, only one group has investigated the association between AIx and RAAS polymorphisms. Wojciechowska et al. [65] in a large group of healthy subjects under 40 years of age reported a negative or very weak association between AIx and the T344C polymorphism. A similar negative association was also found with another stiffness phenotype by Balkestein et al. [64].

From the published literature it appears that a number of genetic variants in the RAAS system can influence the process of arterial stiffening.

The ETs are a group of potent vasoconstrictor peptides that generated intense interest for the pharmaceutical industry and are involved in vascular remodelling [71]. Although controversial, ET and its receptors (ETAR and ETBR) have been shown to associate with hypertension in some studies [7274]. However, the precise role of ET in human hypertension is unclear, although the EDN1, EDNRA and EDNRB genes (genes encoding ET1, ETAR and ETBR receptively) associate with hypertension and PP [75,76]. A significant association was also demonstrated between specific EDNR polymorphisms and arterial stiffness [77]. For instance, in a study of untreated subjects with hypertension of European origin, a positive association between EDNRA (A−231G and C1363T), EDNRB (G30A) and EDN1 (−138I/D) polymorphisms and aortic PWV was reported [77]. In women, the age-adjusted PWV associated with both EDNRA and EDNRB polymorphisms with the −231G and 30G alleles associated in a co-dominant manner with higher PWV and both alleles being significant independent determinants of PWV. However, this relationship was not found in men. This gender-specific association between this gene polymorphism and stiffness is unclear and remains to be elucidated.

G-proteins are key components of a plethora of intercellular signalling cascades, relaying signals from more than 1000 receptors to a diversity of intercellular effector molecules, including enzymes and ion channels [78]. A number of studies have demonstrated an association between the 825T allele of GNB3 gene (G-protein β3 subunit gene) and hypertension [7981]. Interestingly, a study by Nurnberger et al. [82] examined the effect of the C825T polymorphism on arterial stiffness and wave reflection in healthy men. In that study, individuals carrying the T allele (CT heterozygotes and TT homozygotes) had significantly higher PWV and AIx, independent of confounding factors, compared with individuals who were CC homozygotes. The underlying mechanisms in this relationship are unclear, but it has been suggested that it could be related to altered vascular remodelling events arising from aberrant vascular smooth muscle cell proliferation in response to enhanced NHE (Na+/H+ exchanger) activity [79].

In addition to the factors that influence the growth of vascular smooth muscle or the expression of ECM (extracellular matrix) protein within the arterial wall, certain released vasoactive factors, for example NO released from eNOS (endothelial NOS), may also influence arterial stiffness. Inhibiting this enzyme has been shown to have a substantial effect on both vascular tone and BP [83,84]. On this basis, studies using both exogenous and endogenous NOS inhibitors to decrease basal endothelial cell NO synthesis have shown an increase in carotid artery IMT and stiffness [85,86]. Interestingly, the G894T polymorphism of the NOS3 gene (the gene encoding eNOS) had an independent effect on arterial stiffness in young adults of African-American ancestry [87]. The T allele significantly associated with lower systolic BP and a lower degree of carotid artery stiffening within this cohort, but not in adults of European origin. This finding is consistent with a previous study in which the T allele did not significantly associate with aortic PWV [85]. This suggests that the NOS3 gene may be one of the factors that contributes to the observed ethnic differences in both hypertension and arterial stiffness. The G894T polymorphism also influenced a number of phenotypes [68,88]. Nonetheless, the mechanistic basis as to how the G894T polymorphism could be linked to effects on stiffness remains to be demonstrated in much larger populations.

The human β2-AR is a member of the G-protein-linked seven-transmembrane-domain-receptor family. β2-AR stimulation causes vascular smooth muscle relaxation and approx. 50% is mediated by NO, i.e. endothelium-dependent. ADRB22-AR gene) polymorphisms have been implicated in the pathogenesis of hypertension and endothelial dysfunction. Only two studies have demonstrated the affect of ADRB2 polymorphisms on vascular phenotypes [89,90]. In a large cohort of twins, Snieder et al. [90] reported a significant association between PP and ADRB2 polymorphisms (R16G and Q27E). On the other hand in treated patients with hypertension, they found that the Q27E polymorphism significantly influenced aortic PWV. This suggests that β2-AR mediates smooth muscle relaxation in small resistance and large conduit arteries. The mechanisms linking these polymorphisms to arterial wall properties have not been defined; however, ADRB2 polymorphisms could be useful markers with which to predict disease risk and drug responses.

Matrix-related genes

Premature arterial stiffening is an important determinant of CV risk. As mentioned above, the stiffness of the large arteries depends on a number of factors, including structural elements such as elastin and collagen, which are the main extracellular matrix proteins of the vessel wall. Interestingly, these structural proteins are not fixed elements, as they can be synthesized de novo in adults, are susceptible to enzymatic degradation by a number of enzymes [elastases and MMPs (matrix metalloproteinases)] and can be modified by glycosylation and chemical ‘attack’ [91]. In recent years, genetic variation in ECM proteins has been studied extensively for evidence that they modulate the arterial wall remodelling process. The following sections and Table 3 highlight some polymorphisms that have been reported to alter arterial wall properties.

Elastin is the major protein that provides elasticity to the large arteries. Several lines of evidence support the view that disruption of arterial elastic fibres and intimal proliferation in the large elastic arteries results in a quantitative and/or qualitative modification of elastin during vascular development that is of pathogenetic importance [92,93]. Indeed, molecular genetic studies in knockout mice [94,95], human genetic disorders (supravalvular aortic stenosis, Williams syndrome and Marfan syndrome) and normotensive adults have identified deletions, more subtle mutations and several polymorphisms (S422G or A>G nucleotide change) in the ELN gene (elastin gene), which disrupt the elastic fibres, leading to a narrowed lumen which, in turn, affects the biomechanical properties of the arterial wall [96,97]. So far, only one study has examined an association between an ELN gene polymorphism (S422G or A>G nucleotide change) and carotid arterial distensibility in 320 healthy subjects without evidence of CVD [98]. In that study, the serine allele (AA and AG genotypes) was associated with decreased distensibility of the carotid artery compared with the double glycine allele (GG genotype). Moreover, this relationship was evident even after adjustment for age and mean pressure, and it was more prominent in subjects over 50 years of age. By contrast, no association was observed between the genotypes and arterial parameters in the radial artery. This could be explained by the carotid artery being an elastic artery with high amounts of elastin and collagen fibres, whereas the radial artery is a muscular artery composed principally of arterial smooth muscle.

Two studies have examined the impact of the arterial COL1A (gene encoding collagen type 1A) polymorphism (G2064T) on arterial compliance [99,101]. In a large young cohort of healthy adults, Brull et al. [99] found that individuals carrying the GG genotype had significantly more compliant arteries not only in the aorto-iliac segment, but also in the limbs compared with GT and TT individuals. This association was independent of BP level and a family history of hypertension. On the other hand, although the mean aortic stiffness was higher in men with GG genotype compared with other genotypes, adjustment for other factors did not have any affect on this association.

FBN1 (gene encoding fibrillin 1) is the disease gene for ‘Marfan's syndrome’, in which large artery stiffness and elevated PP are the main determinants of aortic dilation. Interestingly, within the FBN1 gene, a VNTR (variable nucleotide tandem repeat) polymorphism was identified in intron 28 and some of its alleles associated with systemic sclerosis [102] and PP in healthy subjects [100,101]. More recently, the 2-3 genotype for a VNTR in FBN1 also associated with large artery stiffening and elevated PP in patients with CVD compared with the 2-2 and 2-4 genotypes [103]. Medley et al. [103] showed that patients with the 2-3 genotype of the TAAAA repeat tended to have stiffer arteries, higher PP and more severe CAD than patients with other genotypes (2-2 or 2-4). A study by Powell et al. [101] confirmed their previous observation [100] of higher PP in subjects harbouring the 2-3 genotypes compared with 2-2 and 2-4 genotypes. Nonetheless, in another large cohort of healthy adults without symptomatic CVD or conventional risk factors for it, no significant differences between the three reported genotypes for aortic PWV, AIx or PP were found [105]. Although the molecular mechanisms linking an intronic polymorphism to large artery stiffening is unclear, it may perhaps relate to an effect on gene expression or via an influence on RNA splicing as the VNTR is located near the 3′ splicing boundary for exon 28 of the FBN1 gene [106].

Matrix homoeostasis is a critical determinant of the mechanical properties of the blood vessels, and the mechanisms whereby matrix proteins are deposited and turned over in the vessel wall are likely to play important roles in the process of arterial stiffening. Interestingly, significant evidence has emerged on the contribution of genetic variation in the activity of one class of proteins that regulate matrix homoeostasis, namely MMPs. Of these, MMP3 and MMP9 appear the best understood and both associate with increased susceptibility to CHD, aortic aneurysm and age-related arterial stiffening. Furthermore, the promoter variants in these genes have also been shown to modulate increased gene and protein expression in experimental and human studies.

MMP3 (stromelysin 1) is involved in a number of CV conditions and is critical in regulating arterial stiffness given its wide range of substrates and activation status. The most extensively studied MMP3 polymorphism is the −1612 5A/6A promoter polymorphism. This polymorphism has been shown to influence gene expression via effects on transcription factors binding within the promoter region [107]. Interestingly, at a clinical level, both alleles have been associated with coronary events and aortic aneurysms [108,109]. By contrast, the 6A allele has been claimed to be associated with increased carotid IMT, progression of CAD in post-bypass patients and elastic properties of large arteries [110,111]. Individuals homozygous for the 6A allele had greater progression of angiographically proven disease than those with a 5A/5A genotype [107]. In the study by Medley et al. [112], the 5A/6A heterozygous genotype was found to be associated with large artery stiffness in older, but not in younger, individuals at low CV risk. Moreover, individuals homozygous for the 5A allele exhibited a 4-fold higher level of MMP3 gene expression in dermal biopsies compared with subjects who were heterozygous. As large artery stiffness is the primary cause of isolated systolic hypertension, the clinical implications of that study include a predisposition to this condition in individuals homozygous for the MMP3 promoter polymorphism.

MMP9 (gelatinase B) is particularly important in arterial wall remodelling, as it degrades elastin and other basement membrane proteins. It is highly expressed in atherosclerotic plaques [113] and is associated with a number of CV conditions [114,115]. Although MMP9 gene expression is tightly controlled at the level of transcription, several factors, including inflammatory markers and genetic variants, stimulate its over-/underproduction. A number of variants have been identified, but the two most commonly studied are the promoter (C−1562T) and coding (R279Q) polymorphisms. Blankenberg et al. [114] demonstrated that the C−1562T polymorphism produced a 1.5-fold increase in promoter activity, predicted CV events and modulated plasma MMP9 levels in patients with CVD. In another study, Medley et al. [116] showed an association between this polymorphism and large artery stiffening in patients with CAD. Individuals harbouring the T allele had significantly stiffer arteries (higher input and characteristic impedance) and higher carotid systolic BP compared with CC homozygotes. This was seen even after adjustments for traditional CV risk factors. In a separate sample (aortic tissues), these authors [116] also reported higher gene expression in T allele carriers. Furthermore, a more recent study in untreated subjects with hypertension demonstrated increased MMP9 levels in carriers of T allele [117]. In our previous study [118], we examined the two common polymorphisms in a large cohort of healthy individuals and found that subjects carrying the T and Q alleles had significantly increased stiffness (aortic PWV; Figure 1) compared with CC or RR homozygotes respectively. A similar relationship was also observed for AIx. In addition, we also confirmed previous observations of higher levels of MMP9 in individuals harbouring the T and Q alleles. These findings suggests that large artery stiffness in individuals carrying the alleles in question may be attributable to enhanced degradation of the arterial wall matrix; however, future studies need to evaluate whether serum gelatinolytic activity in particular leads to elastin degradation in a genetically susceptible individual and, hence, influence premature arterial stiffening and/or increased vascular risk.

Influence of MMP9 polymorphisms on aortic PWV
Figure 1
Influence of MMP9 polymorphisms on aortic PWV

(A) and (B) represent aortic PWV by the three genotypes in C−1562T and R279Q polymorphisms in the whole cohort. Results are means±S.E.M. The C−1562T and R279Q alleles have a dose-dependent effect on aortic PWV independent of confounding factors (P<0.05). This Figure was reproduced from Yasmin, McEniery, C.M., O'shaughnessy, K.M. et al. (2006) Variation in the human matrix metalloproteinase-9 gene is associated with arterial stiffness in healthy individuals. Arterioscler. Thromb. Vasc. Biol. 26, 1799-1805, with permission (www.lww.com).

Figure 1
Influence of MMP9 polymorphisms on aortic PWV

(A) and (B) represent aortic PWV by the three genotypes in C−1562T and R279Q polymorphisms in the whole cohort. Results are means±S.E.M. The C−1562T and R279Q alleles have a dose-dependent effect on aortic PWV independent of confounding factors (P<0.05). This Figure was reproduced from Yasmin, McEniery, C.M., O'shaughnessy, K.M. et al. (2006) Variation in the human matrix metalloproteinase-9 gene is associated with arterial stiffness in healthy individuals. Arterioscler. Thromb. Vasc. Biol. 26, 1799-1805, with permission (www.lww.com).

Genetic polymorphisms and animal models

Numerous studies have demonstrated structural modifications of the arterial wall in experimental models of essential hypertension (for a review, see Laurent et al. [119]). Similarly, genetic studies in knockout mice and human genetic diseases have implicated deletions, mutations and polymorphisms in a number of proteins such as elastin, fibrillin, fibronectin and desmin that affect the biomechanical properties of the arterial wall; this is usually due to disruption of elastic fibres [93,120,121]. Future studies dissecting the genetics of aortic stiffness in models such as SHR (spontaneously hypertensive rats) may provide further insight into the cellular and molecular determinants of human arterial stiffness.

Genome-wide linkage studies

Genome-wide linkage scans have been suggested as an attractive, comprehensive and unbiased approach for identifying susceptible chromosomal loci. To date, many studies have performed genome scans for PP using microsatellite markers and have demonstrated conflicting results in terms of chromosomal regions. This is partly related to the rather low linkage signals. Table 4 summarizes the results of all of the genome-wide studies for PP in Mexican Americans, Utah pedigrees, the Framingham Heart Study and the Family Blood Pressure Program [45,48,51,52,54,122125]. Several chromosomal regions of suggestive and significant linkage have been identified with LOD (logarithm of the odds) scores ranging from 2.70 to 5.07 (Table 4), but have been poorly replicated. For instance, in Utah pedigrees, a region on chromosome 7 was identified [51], but in a study in multi-ethnic groups, a linkage region on chromosome 18 was identified for PP [48]. The inconsistencies of chromosomal loci and the genetic effects could be attributed to sample heterogeneity and selection of pedigrees, differences in study design and data collection, differential clustering of risk factors and CV conditions in recruited subjects and different methodologies for adjusting PP values and/or age. For example, one study recruited subjects that were relatively young (mean age, 27.8 years) [51], and Franklin et al. [126] have shown that PP increases slowly in young adults but accelerates after 50 years of age. Although this age-dependent increase in PP mainly indicates the arterial aging process [127], in young subjects it is the ventricular ejection that significantly determines PP and thus increases in PP do not reflect arterial stiffness [128]. Nonetheless, a recent meta-analysis of seven genome scans of PP published previously used a heterogeneity testing approach and identified five chromosomal regions with significant evidence of linkage and also identified a new candidate gene [NEDD4L (neuronal precursor cell expressed developmentally down-regulated 4-like gene)] for PP [129]. As PP is an indirect measure of arterial stiffness and is influenced by other factors, such as age and ventricular ejection, future studies which incorporate more direct measures, including aortic PWV and AIx, may be valuable in elucidating the genetic component for arterial stiffness.

To date, only one study has performed a genome scan for aortic PWV as well as both the forward and reflected waves. In the Framingham Offspring cohort (n=590), Mitchell et al. [45] demonstrated significant regions for forward wave amplitude on chromosome 7 at 174 cM (LOD=2.88) adjacent to the NOS3 locus, and two linkage regions for reflected wave amplitude on chromosome 4 at 181 cM (LOD=4.93) and chromosome 8 at 33 cM (LOD=3.37). In addition, four suggestive regions of linkage for aortic PWV on chromosome 2 at 94 cM (LOD=2.46), chromosome 7 at 29 cM (LOD=2.50), chromosome 13 at 108 cM (LOD=2.10) and chromosome 15 at 108 cM (LOD=2.48) were also reported.

The results thus far from the genome scans indicate that distinct genes may modulate various components of the arterial wall properties in humans. However, the density of DNA markers in the genome scans used were low and ranged from 366 [52] to 405 [51] (i.e. 10 cM separation). This, together with the small cohort sizes, makes it unlikely that these studies had the power to detect anything but large gene effects. The reality of recent genome-wide linkage scans is that very large SNP (single nucleotide polymorphism)-based association studies are the way forward. In complex disorders, effect sizes measured by attributable risk of ≤1.5 appear to be the probable reality. These can be detected in many complex conditions using much larger cohorts as shown by recent genome-wide association studies such as the WTCCC (Wellcome Trust Case Control Consortium [130], where the accuracy of genotype calling rate was substantially increased by combining results across studies, and also common loci were identified in diseases that appear to be dissimilar, such as Type 1 diabetes and Crohn's disease [131,132]. Therefore large-scale studies (using tens of thousands of subjects) hold the key to unravelling the genetics of complex conditions that have a multifactorial aetiology, such as arterial stiffness.

Gene expression profiling

To date, only one study has performed individual gene expression (RNA) profiling using microarray technology and identified a surprisingly small sets of candidate genes for arterial stiffness [133]. In that study, a small number of diseased and normal aortic tissue samples were compared, and just 32 transcripts belonging to genes encoding structural proteins, elements of the cytoskeleton and cell signalling molecules were identified. All were either strongly or significantly associated with PWV or, in the case of a subset, completely absent from stiff or distensible aortic tissues respectively. Most of the genes identified belonged to the cytoskeleton with the remainder distributed between the matrix and membrane. As seen in Figure 2, almost half of the abnormal transcripts identified are involved in signalling/communication or cell structure/motility. This suggests that changes not only in the ECM proteins, but also in the expression of signalling molecules may play an important role in arterial stiffening process in humans.

Genes differentially expressed with arterial stiffness

Figure 2
Genes differentially expressed with arterial stiffness

There are two distinct groups, with the majority of genes influencing arterial function are attributed to cellular signalling pathways and the other to vascular structure. This Figure was reproduced from Durier, S., Fassot, C., Laurent, S., Boutouyrie, P., Couetil, J.P., Fine, E., Lacolley, P., Dzau, V.J. and Pratt, R.E. (2003), Physiological genomics of human arteries: quantitative relationship between gene expression and arterial stiffness, Circulation 108, 1845-1851, with permission (www.lww.com).

Figure 2
Genes differentially expressed with arterial stiffness

There are two distinct groups, with the majority of genes influencing arterial function are attributed to cellular signalling pathways and the other to vascular structure. This Figure was reproduced from Durier, S., Fassot, C., Laurent, S., Boutouyrie, P., Couetil, J.P., Fine, E., Lacolley, P., Dzau, V.J. and Pratt, R.E. (2003), Physiological genomics of human arteries: quantitative relationship between gene expression and arterial stiffness, Circulation 108, 1845-1851, with permission (www.lww.com).

THERAPEUTIC POTENTIAL

In monogenic conditions such as Marfan's syndrome, β-blockers effectively reduce arterial stiffness. However, to date, drugs that selectively target the large arteries have not been available. Arterial stiffness is influenced by three main factors: mean arterial pressure, smooth muscle tone and structural proteins. Many studies thus far have used traditional antihypertensive agents, such as thiazide diuretics, calcium channel blockers and ACE inhibitors, to reduce arterial stiffness through a reduction in BP and have reported conflicting results (for details, see the reviews by Mahmud and Feely [134] and Hope and Hughes [135]). These discrepancies could be attributed to the use of different classes of drugs, differential effects on muscular arteries (for example, brachial or radial artery) compared with more elastic arteries (for example, carotid artery or thoracic aorta), inclusion of a small number of subjects, controls not well matched for mean pressure, and patients with hypertension or associated CV risk factors. Nevertheless, these therapies target two factors, i.e. mean pressure and vessel tone, and therefore act indirectly to reduce stiffness. In addition, nitrate-based therapies have also been shown to reduce PWV, wave reflections and BP via altering vessel tone. For this reason, there is a clear need for novel therapies that can selectively target large arteries in order to reduce arterial stiffness directly.

Aldosterone inhibitors and statins [HMG-CoA (3-hydroxy-3-methylglutaryl-CoA) reductase inhibitors] are interesting therapeutic approaches. Elevated aldosterone concentrations have been shown to promote oxidative stress, endothelial dysfunction, inflammation and fibrosis (see the review by Marney and Brown [136]). In subjects with hypertension, increased aortic stiffness is associated with increased plasma aldosterone. In addition, a polymorphism of the CYP11B2 gene also associated with a pressure-dependent increase in aortic stiffness [60]. Although an initial study in subjects with hypertension failed to demonstrate changes in brachial artery stiffness after spironolactone therapy [137], more recently this therapy has been shown to reduce brachial PWV and PIIINP (procollagen III N-terminal peptide) levels in diabetic patients with hypertension [138]. Numerous studies have also reported so-called ‘pleiotropic effects’ of statin use, which include improvement in endothelial function, increased NO bioavailability, and antioxidant and anti-inflammatory effects as well as modulating arterial wall properties [139142]. However, most of these studies were short-term, hence long-term studies which elucidate the ability of statins or spironolactone, particularly in the elderly and/or in patients with isolated systolic hypertension are needed. Interestingly, in REGRESS (Regression Growth Evaluation Statin Study) and LOCAT (Lopid Coronary Angiography Trial), patients with certain genotypes (5A/6A and 6A/6A) and taking statins experienced fewer clinical events than the placebo group [143,144]. This suggests that certain polymorphisms confer a genotype-specific response to medication. Future trials, including candidate genes not only of the RAAS, but also other systems involved in arterial structure, vasomotor tone and remodelling, would enable us to develop better treatment strategies and personalize treatment based on the genetic milieu.

Interventions that either promote or reduce the activities of enzymes and/or endogenous inhibitors targeting structural proteins, such as elastin and collagen, are also attractive. As are therapies that target the formation of AGE (advanced glycation end-products) and collagen cross-linking associated with arterial stiffening, seen in conditions such as diabetes, aging and isolated systolic hypertension. A recent study in middle-aged untreated subjects with hypertension (n=30) demonstrated significantly higher plasma AGE levels compared with age-matched controls (n=16) [145]. The plasma AGE levels in that study also associated with aortic PWV independent of age and BP level, suggesting a direct effect of circulating AGE levels on large arteries. Hence a thiazolium derivative, ALT-711, that interferes with the formation of AGEs and/or breaks down established AGE cross-links between proteins, such as elastin and collagen, can reduce arterial stiffness and also improve endothelial function in older individuals with increased arterial stiffness [146]. These findings need replication and testing in other patient populations, but represent a new avenue for the pharmacotherapy of the stiff aorta.

PERSPECTIVES

Arterial stiffness is an important and epidemiologically independent determinant of CV risk. Stiffness can be assessed by a number of methods and reflects both structural and functional elements within the wall itself as well as effects of age, hypertension, smoking, hypercholesterolaemia and other factors. In recent years, it has become increasingly clear that arterial stiffness is highly heritable and a number of genes are involved, although the precise molecular pathways regulating stiffness are still largely unknown. Nonetheless, interest in these genetic determinants of stiffness is rapidly growing thanks to the plunging costs of genotyping, the availability of well-validated SNPs and high-throughput technologies (such as gene chips) for genotyping even very large cohorts of subjects. Although significant challenges remain in this field, identification of these genetic markers should help us to stratify individual risk and identify people who might benefit from early aggressive intervention. This knowledge may also identify novel drug targets that could be exploited to pharmacologically modify arterial wall stiffening in the future.

Abbreviations

     
  • ACE

    (ACE), angiotensin-converting enzyme (gene)

  •  
  • AGE

    advanced glycation end-products

  •  
  • AGT

    angiotensinogen gene

  •  
  • AGTR1

    angiotensin II type 1 receptor gene

  •  
  • AIx

    augmentation index

  •  
  • β2-AR

    β2-adrenoreceptor (encoded by ADRB2)

  •  
  • BMI

    body mass index

  •  
  • BP

    blood pressure

  •  
  • CAD

    coronary artery disease

  •  
  • COL1A

    collagen type 1A gene

  •  
  • CV

    cardiovascular

  •  
  • CVD

    cardiovascular disease

  •  
  • CYP11B2

    aldosterone synthase gene

  •  
  • ECM

    extracellular matrix

  •  
  • ELN

    elastin gene

  •  
  • ET

    endothelin

  •  
  • EDN1

    ET1 gene

  •  
  • ETAR

    ETA receptor (encoded by EDNRA)

  •  
  • ETBR

    ETB receptor (encoded by EDNRB)

  •  
  • FBN1

    fibrillin 1 gene

  •  
  • GNB3

    G-protein β3 subunit gene

  •  
  • I/D

    insertion/deletion

  •  
  • IMT

    intima-media thickness

  •  
  • LOD

    logarithm of the odds

  •  
  • MMP

    matrix metalloproteinase

  •  
  • NOS

    NO synthase

  •  
  • eNOS

    endothelial NOS (encoded by NOS3)

  •  
  • PP

    pulse pressure

  •  
  • PWV

    pulse wave velocity

  •  
  • RAAS

    renin–angiotensin–aldosterone system

  •  
  • SNP

    single nucleotide polymorphism

  •  
  • VNTR

    variable nucleotide tandem repeat

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