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Research Article
Originally Published 2 November 2009
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Dissociation of Aortic Pulse Wave Velocity With Risk Factors for Cardiovascular Disease Other Than Hypertension: A Systematic Review

Marina Cecelja and Philip ChowienczykAuthor Info & Affiliations
Hypertension
Volume 54, Number 6
https://doi.org/10.1161/HYPERTENSIONAHA.109.137653
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Abstract

Carotid-femoral pulse wave velocity (cfPWV), a measure of large artery stiffness, is an important predictor of cardiovascular events. This has been attributed to it being an integrative measure of the impact of cardiovascular risk factors on the arterial wall. Pulse wave velocity is strongly associated with age and blood pressure. However, findings with regard to its relation with other risk factors have been inconsistent. We performed a systematic review of cross-sectional published literature reporting independent associations of cfPWV in multivariable regression models. Articles were selected from a PubMed search using a prespecified search strategy. Studies were included if they did the following: (1) measured cfPWV; (2) reported on associations with cfPWV from regression models; and (3) considered age and blood pressure in the model. From 637 retrieved articles, 65 met our inclusion criteria, and 12 studies were included from reference searches. Age and blood pressure were consistently independently associated with cfPWV (91% and 90% of studies, respectively). Diabetes mellitus was associated with cfPWV in 52% studies, but the strength of the association was low. The majority of studies found no independent association between cfPWV and sex, total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides, smoking, or body mass index. The contribution of risk factors other than age and blood pressure to cfPWV is, thus, small or insignificant. The prognostic value of cfPWV may relate to a process of arterial ageing unrelated to classic risk factors other than hypertension.
Carotid-femoral pulse wave velocity (cfPWV), a measure of the intrinsic stiffness of the aortic wall, is highly predictive of cardiovascular events.1–8 The prognostic importance of cfPWV has been attributed to it being an integrated measure of the impact of cardiovascular risk factors on the arterial wall9 and to adverse hemodynamic effects of aortic stiffening.10 The later include an increase in systolic blood pressure and pulse pressure with increased systolic load and decreased myocardial perfusion pressure.11–13 That cfPWV is closely associated with age and blood pressure is well established. Previous studies have also reported associations between cfPWV and blood pressure–independent risk factors, including dyslipidemia,14 smoking,15 obesity,16 sex,17 heart rate,18,19 and diabetes mellitus20 (see review by Benetos et al9). However, findings with respect to risk factors other than age and blood pressure have been inconsistent, and negative findings were not highlighted in many studies.21,22 The purpose of the present study was, thus, to perform a systematic review of published cross-sectional studies to examine the independent association of cfPWV with cardiovascular risk factors. We included only studies in which cfPWV was used as a measure of arterial stiffness, because there is considerable variability in agreement between other measures of stiffness23 and a lack of outcome data for measures other than cfPWV.1–8 cfPWV is, moreover, simple and relatively inexpensive to measure noninvasively with high reproducibility using currently available commercial equipment.24,25

Methods

Search Strategy

Studies, published up to December 2008, were searched using 2 strategies: a PubMed search and a manual search of citation lists of relevant publications. In PubMed, key words for the search were “PWV,” or “pulse wave velocity,” or “arterial stiffness,” or “aortic stiffness,” and these were combined, in turn, with “determin*” or “predict*.”

Selection Criteria

The list of titles and abstracts was initially screened for relevancy. Articles were rejected if they were as follows: (1) did not measure central PWV (between carotid and femoral arteries); (2) included children; (3) were animal studies; (4) were in vitro– or model-based studies; or (5) were review articles. Relevant articles were then checked in full to confirm eligibility and extract data. Studies were included if they fulfilled the following criteria: (1) involved performance of multivariable regression models for potential associates of cfPWV; (2) involved inclusion of age and blood pressure in the regression model; and (3) had sufficient detail of variables entered into the regression model and outcomes. Any blood pressure measure (ie, systolic, mean, or diastolic) or combination of measures was accepted. There were no restrictions on sample size or inclusion of mixed populations (but, where separate values were given for different groups, these were included). Articles by the same authors or groups were excluded unless it was clear that different populations were used. Studies were restricted to the English language. Additional studies were identified by a manual search of references from relevant publications.

Data Extraction

Data extraction was standardized by use of a single form, which included publication date and author, sample size (number and percentage of men), age, method of cfPWV measurement, mean cfPWV, blood pressure, variables included in multivariable regression analysis, outcomes, and R2 values. When a variable was not included in a regression model because it was not significantly associated with cfPWV on univariate analysis, it was regarded as having no independent association with cfPWV.

Results

The initial search identified 2275 potential articles. Of these, 1638 were excluded on initial screen of title and abstract. The remaining 637 were retrieved in full, and a further 572 were excluded because of ineligibility or overlapping subject cohorts from a previous publication (see Figure S1 in the online Data Supplement, available at http://hyper.ahajournals.org). A further 12 studies were identified and included in the review from a reference search, giving a total of 77 included publications. Thirteen of these reported on ≥2 separate groups, giving 97 subject groups in total (including a total of 26 970 subjects; see online Supplemental Data for further details).

Independent Predictors of PWV

Age and blood pressure were significantly independently associated with cfPWV in 91% and 90% of studies, respectively. The majority of studies used only systolic blood pressure (n=43; 44%) or mean arterial pressure (n=30; 31%) as the measure of blood pressure, and only 4 (4%) used a combination of these blood pressure measures. The Figure shows the number of studies in which heart rate and other risk factors were included and the proportion of these in which the risk factor was significantly associated with cfPWV. A total of 51 studies evaluated the predictive value of heart rate, of which 26 (51%) found a significant association. The presence of diabetes mellitus and sex was associated with cfPWV in 12 (52%) of 23 and 15 (27%) of 54 studies, respectively. Smoking and body mass index were associated with cfPWV in 6 (14%) of 44 and 7 (13%) of 53 studies, respectively. Inclusion of measures of cholesterol differed: total cholesterol was considered in 41 studies, of which only 2 (5%) found a significant association. Low-density lipoprotein cholesterol and high-density lipoprotein cholesterol were significantly associated in only 1 (5%) of 21 and 4 (11%) of 37 studies, respectively. Only 1 (3%) of 38 reported a significant association with triglyceride levels. When only studies including healthy, hypertensive, or population cohorts were considered, associations were similar (Figure). Studies excluded (n=66; including a total of 22 986 subjects) because of possible replication in the same population or not fully reporting outcomes of regression models are described in the online Data Supplement.
Figure. The number of studies in which classic risk factors and heart rate were included (bars) and the proportion of these (solid line) in which the risk factor was significantly independently associated with PWV. A, All studies. B, Studies including only healthy, hypertensive, or population cohorts. BP indicates blood pressure; HR, heart rate; DM, diabetes mellitus; TC, total cholesterol; LDL, low-density lipoprotein cholesterol; HDL, high-density lipoprotein cholesterol; TG, triglycerides; BMI, body mass index.

Coefficient of Variation (R2) Values

Twenty-three studies reported individual R2 values, representing the amount of variability in cfPWV accounted for by correlates of cfPWV (see Figure S2). Age accounted for 2.0% to 53.0% (mean: 23.5%) and blood pressure 1.8% to 41.0% (mean: 13.8%) of variance in cfPWV. R2 values for all of the other variables reported were much lower, with heart rate only accounting for 0.6 to 3.4%, sex accounting for 1.0% to 13.0%, diabetes mellitus accounting for 1.0% to 8.0%, and smoking accounting for 0.3 to 2.2%. R2 values for body mass index and total cholesterol were reported in only 1 study and accounted for only 1.4% and 1.0%, respectively, of variance in cfPWV.
Other variables accounting for >5% of cfPWV variance in individual studies included angiotensin II type 1 receptor gene polymorphism (A1166C; R2=0.12),26 although in a separate study a more modest contribution was noted (R2=0.05)27; as well as C-reactive protein (R2=0.05)28; forced expiratory volume in 1 second (R2=0.12)29; HIV status (R2=0.12)30; respiratory disturbance index (R2=0.12)31; C3 (complement component; R2=0.17)32; carotid plaque (R2=0.07)32; family history of cardiovascular disease (R2=0.06)32; and target organ damage (R2=0.06).32 Several single nucleotide polymorphisms other than A1166C were associated with cfPWV but accounted for <5% of the variance in PWV, including angiotensin-converting enzyme insertion/deletion polymorphism (R2=0.02)26 and matrix metalloproteinase 9 polymorphisms C-1562T (R2=0.01) and R279Q (R2=0.01).33 A number of other factors correlated with cfPWV but accounted for <5% of the variance in cfPWV (Table).
Table. Characteristics of Studies Included in Systematic Review
ReferencesSample, nMen, %Age, yPWV, MethodPWV, m/sBP, mm HgR2Variable Significantly Associated With PWVOther Significant Variables
AgeBPHRTCLDLHDLTGSexDMSmokingBMI
Taquet et al 1993S1Healthy, 429049n…130/8231NSu√+√+NSu……NSu………NSuLeucocyte count, family history of DM
Asmar et al 1995S2NT, 178…18–77c………√+√+NSNS…NS………NS… 
HT, 240…18–77c………√+√+NSNS…NS………NS… 
Tanokuchi et al 1995S3T2DM, 1075459h9.4149/82…√+√*…NS…NSNSNS…NS… 
Dart et al 1995S4Chinese migrants, 83……u♂: 6.6; ♀: 6.1…85√+√+……√−……NS……NSMigrant status
Benetos et al 1996S5Untreated HT, 3116949n12.4158/9537√√*……………NS……√ACE (I/D) and AGTR1 (A1166C) polymorphism
 Healthy, 1286344n9.1123/7622√√*……………√……NS 
Lehmann et al 1998S6PVD, 110, and controls, 517364u9.3138/77…√√…NS………NSNSNSNSPrevious MI
Ferreira et al 1999S7Healthy, 12010026c…132/85…√+√+NSuNSu………………NS 
Taniwaki et al 1999S8DM, 2714451h9138/7633√+NS…NS…NSNS…………Duration of DM
Healthy, 2855150h7.2124/7441√+NS…NS NSNS………… 
Sytton-Tyrell et al 2001S9Population, 24884874u9.0…14√+√+√+…………NS…√+…Hemoglobin A1c, HT, visceral fat
Selzer et al 2001S10Premenopausal ♀ SLE, 124039u5.4117/7426NSNS………………………Carotid plaque, C3, hydroxychloroquine use
Postmenopausal ♀ SLE, 96054u6.9129/7759√+√+……………………NSFamily history of CVD glucose, creatinine, WBC organ damage score
Havlik et al 2001S11Healthy sedentary, 530…51u…121/7922√+NS………√−…NSNS…NS 
Amar et al 2001S12Healthy, 7465348c8.8127/7927√+√+√+NSNSNSuNS√†…NSuNS 
Treated HT, DM, HC, 2475254c9.8142/83 √+√+√+………NS…………Apolipoprotein B
Asmar et al 2001S13HT, 10875758c12.6144/8232√+√+√+……NS…√+…√+…Creatinine, glucose
Boutouyrie et al 2002S14HT, 10456553c12.1153/92…√√NS…………NS√NS…HC
Benetos et al 2002S15Treated HT, 1876357n11.4144/88…√√√NS…NS………NS… 
NT, 2966548n9.8128/78…√√…NS…NS………NS√ 
Lebrun et al 2002S16Postmenopausal ♀, 385066s9.2147/76…√+√+√+……√−………√+NS 
Achimastos et al 2002S17HT, 16210065c12.2150/9743√+√+√+NS…NSNS……NS…Country (Greek vs French)
Lantelme et al 2002S18HT, 1935553c/n12.7149/92…√+√+√+NS……NSNS…NS…HT treatment, glucose
Mackey et al 2002S19Men, 16610074u8.7129/7332NS√+√+…………………… 
Women, 190073u8.4131/7021NS√+√+………NS…………Waist circumference, HT treatment
Oren et al 2003S20Young adults, 5244628s6125/7224√+√+……NS……√+……NS 
Nurnberger et al 2003S21Healthy, 10210027n5.9120/73…√+√+NS……………………Left ventricular ejection time
Blacher et al 2003S22ESRD, 2426152u……57√+√+……NSNS…√‡NSNSNSHeart period
Healthy, 469…50u……65√+√+……NSNS…√‡NSNSNSHeart period
Stompór et al 2003S23ESRD, 435651u10.7138/8642√+√+………………………Basic fibroblast growth factor
Kimoto et al 2003S24T2DM, 161 and controls, 1294860n…123/7647√+√+……NSNS…NS√+NS… 
Mitchell et al 2004S25Healthy, 5213657n8.5115/6951√+√+√+………√§NS……NSWalk test
(Continued)
Table. Continued
ReferencesSample, nMen, %Age, yPWV, MethodPWV, m/sBP, mm HgR2Variable Significantly Associated With PWVOther Significant Variables
AgeBPHRTCLDLHDLTGSexDMSmokingBMI
Gardier et al 2004S26HT, 1855753c12.2174/10044√+√+…NS………NS………AGTR1 (A1166C) polymorphism
Bahous et al 2004S27Kidney transplant, 1066943c11.1121/7045√+√+…………………√+…Acute rejection
Lacy et al 2004S28DM and controls, 1326855s8.5134/7973√+√*√+NS……NSNS√+NS…Previous CVD
Hansen et al 2004S29Healthy, 24205054n11.3129/8252√+√+√+…NSNSNS√∥NSNSNSLog insulin
Booth et al 2004S30Vasculitis and controls, 634354s8.2…60√+√+……NS……NS……NSLog CRP
Silva et al 2004S31NT 132,4541c8.9124/79…√√…NSu……NSu………NSWaist circumference
White-coat NT, 395150c11.5131/82…√√…NSu……NSu………NSu 
White-coat HT, 874545c9.9151/92…√√…NSu……NSu………NSWaist circumference
Untreated HT, 1544647c11.9163/100…√√…NSu……NSu………NSu 
Treated HT, 1714054c11.4161/97…√√…NSu……NSu………NSu 
DM, 1023755c12.6156/93…√√…NSu……NSu………NSu 
Pirro et al 2004S32Untreated HC, 604757s8.8131/78…NSNSNSNSNSNSNSNS……NSWaist circumference CRP
Shinohara et al 2004S33ESRD, 2155161h…148/8329√+√+………NS…NS…NSNSHemodialysis, HOMA-IR
McEniery et al 2005S34Young adults, 10084320s6.0134/8123√+√+√+…………√−……… 
Mahmud et al 2005S35Untreated HT, 765547n…152/9257√+√+NS…NSNS…NS…NSNSAdiponectin
Kullo et al 2005S36Community, 2145359s9.8126/7341√+√+√+NS…√−…NSNSNSNS 
Filipovski et al 2005S37Population, 2914925–65s♂ 7.8; ♀ 7.4128/82; 123/7814√+√+ NS………NS…NSNSGlucose
Smith et al 2005S38T2DM, 1346661s10.2137/7755√+√+……………√+………Duration of DM, HT drugs, ACEI/ARB use
Wang et al 2005S39CKD, 1026360s10138/78…NS√……………NSuNSNSuNSGFR
Briet et al 2006S40CKD, 95; CKD and HT 121; HT, 576458…10.5128/9252√+√+√+…………√−………GFR
Mäki-Petäjä et al 2006S41Rheumatoid arthritis, 771957s8.4132/8271√+√+NSNS………NS……NSCRP
Schillaci et al 2006S42Untreated HT, 3055848s9.1151/9534√+√+NSNS………NS…NSNSGFR
Yasmin et al 2006S43Population, 8655154s8.7133/7957√+√+NS√+……NSNS………MMP-9 (C-1562T and R279Q) polymorphism
McEniery et al 2006S44Healthy, 894641s7.4119/7281√+NSNSNS……NSNS……NSEndothelial function, glucose
Bonapace et al 2006S45Dilated cardiomyopathy, 898063u5.7133/81…√NSuNS………………NSu…Type III collagen
van Trijp et al 2006S46Healthy, 29910059s9.3143/8148√+√+√+…NS………√+NS… 
Alecu et al 2006S47Population, 2075567p9.4137/7532√+√+……………√‡√+…NS 
Paini et al 2006S48NT, 94…53c12.8119/6941√√……………NS……NS 
HT, 2436253c14.2150/2145√√……………………NS 
T2DM, 1265863c18.3151/8233√√……………NS…NS√ 
Otsuki et al 2006S49Athletes, 22 and controls, 1210021n…121/6561√√NSNSNSNSNS………√Endothelin 1
Perkins et al 2006S50Healthy, 11510051c8.5130/8131√+√+NS…………………NS 
(Continued)
Table. Continued
ReferencesSample, nMen, %Age, yPWV, MethodPWV, m/sBP, mm HgR2Variable Significantly Associated With PWVOther Significant Variables
AgeBPHRTCLDLHDLTGSexDMSmokingBMI
Kimoto et al 2006S51T2DM with and without CKD, 434; and controls, 1925662h12.5137/8055√+√+………NS…√√+NS…Non-HDL cholesterol, GFR
Strain et al 2006S52European, 1004355c11127/79…√+√+NS……NSNS…………Weight, waist:hip ratio, waist circumference
European T2DM, 514957c14147/84…√+√+√+……NSNS…………Waist:hip ratio
African Caribbean, 884953c12134/83…√+√+NS……NSNS…………Weight
African Caribbean T2DM, 663657c15155/87…√+√+NS……NSNS………… 
Podolec et al 2007S53Angina undergoing angiography, 1076461c10.7126/78…√+√+……………NSNSNS… 
Ng et al 2006S54Takayasu’s arteritis, 10 and controls, 11040c10128/72…NS√……………………√Takayasu’s arteritis
Lemos et al 2007S55CKD, 1045954c12.2… √+√+…√+……NSNS√+…… 
Noma et al 2007S56Healthy male, 5110046n…124/6679√+NS…NS……………NS…Rho-associated kinases
Zhou et al 2007S57Untreated HT, 2155046c10.1153/9048√+√+√+NS…NSNSNS…NSNSMMP-9 (C-1562T) polymorphism
Park et al 2007S58HT, 4385857h9.9131/8052√+√+√+…NSNSNS√……√−Log aldosterone
Karakitsos et al 2007S59ESRD, 1604861u11.6130/62…√+√+………………√+……Body surface area, HT, plasma endothelin
Kim et al 2007S60HT and NT, 1747059’i11.6147/79…√+√+………………√+…… 
Ronnback et al 2007S61Healthy, 5410058s7.9140/8551√+√+……NSNSNS……NS√+ 
Weber et al 2007S62Cardiomyopathy, 21 and controls, 427664i…124/7573√+√+NSNS………NS√+NS… 
Sabit et al 2007S63COPD, 75 and control, 425663s10.2141/8239√+√+NS…NS……NS…NSNSForced expiratory volume, interleukin 6
Tan et al 2007S64HT, 2027960c11.4144/8946√+√+√+…………………NSTissue inhibitor of metalloproteinase 1
Martinez et al 2008S65Familial HC, 893839c9.2121/7737√+NS…NSuNSu…NSNSu……… 
Matsumae et al 2008S66Hemodialysis with DM, 945965h11.0166/8932NSu√+NSuNSuNSuNSuNSu……NSuNSuHemoglobinA1c, duration of DM
Hemodialysis without DM, 1486064h9.2146/8944√+√+√+NSuNSuNSNSu……NSuNSuHemodialysis duration, hemoglobin A1c
Frost et al 2008S67Postmenopausal ♀, 54063s10.4…59√+√+…NSNSNSNS…………Bone mineral density at the hip
Schillaci et al 2008S68HIV, 39; healthy controls, 786737s 120/7946√+√+NSNS…NSNSNS…NSNSHIV infection
Saez et al 2008S69Renal transplant with and without DM, 3184952s9.0149/83…√+√+NSuNSu…………√+…NS 
Zhe et al 2008S70CAPD, 1484360c11.4147/8324√NS…NSu…NSu…NS……NSuMetabolic syndrome
Lee et al 2008S71HT, 626259h…132/80…NS√+NSu…………NSuNSuNSuNSuAtrial fibrillation
Papaioannou et al 2008S72HT and NT, 425…47c7.1133/8149√√NS…………√………Tr
(Continued)
Table. Continued
ReferencesSample, nMen, %Age, yPWV, MethodPWV, m/sBP, mm HgR2Variable Significantly Associated With PWVOther Significant Variables
AgeBPHRTCLDLHDLTGSexDMSmokingBMI
R2 indicates coefficient of determination; BP, blood pressure; HR, heart rate; TC, total cholesterol; LDL, low-density lipoprotein cholesterol; HDL, high-density lipoprotein cholesterol; TG, triglycerides; DM, diabetes mellitus; BMI, body mass index; √, significant; √+, significant positive association; √−, significant negative association; NS, nonsignificant; NSu, nonsignificant in univariate analysis. … denotes that variable was not included in model. Sample characteristics: HT indicates hypertensive; NT, normotensive; HC, hypercholesterolemia; MI, myocardial infarction; SLE, systemic lupus erythematosus; CVD, cardiovascular disease; WBC, white blood cells; ESRD, end-stage renal disease; CRP, C-reactive protein; HOMA-IR, homeostasis model assessment for insulin resistance; ACE, angiotensin-converting enzyme; ACEI, ACE inhibitor; ARB, angiotensin receptor blocker; AGTR1, angiotensin II type 1 receptor; CKD, chronic kidney disease; MMP, metalloproteinase; GFR, glomerular filtration rate; Tr, travel time of the pressure wave from the heart to the reflection site and back to the aorta; C3, complement component; T2DM, type 2 diabetes mellitus; PVD, peripheral vascular disease; COPD, chronic obstructive pulmonary disease; CAPD, continuous ambulatory peritoneal dialysis; CAD, coronary artery disease. Methods: n indicates noninvasive pressure recordings; i, invasive pressure recordings; c, complier; s, SphygmoCor; p, pulse pen; u, ultrasound; h, Hasegawa method.
*Data show a positive association with systolic BP and negative association with diastolic BP.
†Data show a negative association for women vs men.
‡Data show a negative association where 1 is assigned to men and 2 is for women.
§Data show a negative association for women.
∥Data show a positive association for men vs women.
¶Data show a positive association with men.
#Data show a negative association with absence of diabetes mellitus.
sReference in online data supplement, available at http://hyper.ahajournals.org.
Delles et al 2008S73CAD and controls, 1036556s7.2134/7535√+√+√+…………NSNS…NSCAD
Nguyen et al 2008S74White, 7134536u…115/7818√+√+√+…NSNSNSNS…√+… 
Black, 2783736u…124/8323√+√+√+…NSNSNSNS…√+…Adiponectin
Protogerou et al 2008S75Obstructive sleep apnea, 384457s9.1139/8550√+√+NSNS………NSNSNS…Respiratory disturbance index
Tsioufis et al 2008S76HT, 6515254c8.1147/92…√+√+………√−NS√+…NSNS 
Bellasi 2008S77Black/white hemodialysis, 1425155s…145/7932√+√+……………NS√#NSNSACEI/ARBs, vitamin D3 and analogs

Discussion

As far as we are aware, this is the first systematic review to examine the association of cfPWV with risk factors for atherosclerosis. We included only studies that performed a multiple regression analysis to identify associations independent of age and blood pressure. The systematic nature of the review avoided bias in study selection. Our findings confirm the well-established association of cfPWV with age and blood pressure.34,35 Only a few studies failed to show such associations, and this could be explained by their relatively small sample size and/or relatively narrow spread of age/blood pressure. A relatively high proportion of studies also reported an independent association between PWV and heart rate, although the strength of the association was weak. These findings are consistent with studies in which heart rate has been manipulated by pacing,18,19,36–38 although it should be noted that others have found no effect.39,40 Heart rate may be a confounding factor that should be incorporated into any analysis relating to cfPWV.
Fifty-two percent of studies in which diabetes mellitus was included as a risk factor reported a positive association of cfPWV with the presence of diabetes mellitus. However, even within the studies in which a positive association with diabetes mellitus was seen, the strength of the association between cfPWV and diabetes mellitus was weak, with the presence of diabetes mellitus accounting for a mean of 5% of the variation in cfPWV. One possibility to explain the variable association of cfPWV with diabetes mellitus is that it is sex dependent, with a stronger association in women than in men.41
The major finding of the present review is that, with the exception of age and hypertension, cfPWV is largely independent of classic risk factors for atherosclerosis, with the vast majority of studies showing no association with sex, smoking, and lipids. The association with diabetes mellitus, although positive in a higher proportion studies, is, as discussed above, weak. These results are mainly in agreement with prospective studies, where risk factors other than hypertension are not associated with the progression of cfPWV.16,42 In the case of cholesterol, it is interesting to note that trials of statin therapy have shown both positive43 and negative effects on cfPWV, with 1 study showing a significant increase in cfPWV after treatment.44 Lack of association of cfPWV with sex, smoking, and lipids, all powerful risk factors for atherosclerosis, is somewhat puzzling in view of the reported association of cfPWV with atherosclerotic plaque.45–48 However, this could be explained by a lack of effect of risk factors, per se, and early stages of atherosclerosis on stiffness of the arterial wall, but advanced plaque, particularly calcified plaque, increasing stiffness.47 Indeed, this is supported by animal studies, where PWV appears to decrease during early stages of cholesterol-rich diets and increase as atherosclerotic plaques develop in cynomolgus monkeys.49 It is possible that, in subjects with advanced plaque, where plaque volume might relate to risk factors, the relationship of PWV to risk factors may differ.50
The dissociation of cfPWV with classic risk factors other than blood pressure for atherosclerosis and cardiovascular events in the majority of studies in this review suggests that, at least in its early stages, aortic stiffening is not driven by an atherosclerotic process but by an alternative pathology in which blood pressure is one of the most important factors. It is well recognized that arterial stiffness depends on mechanical stretch of the arterial wall and, hence, on blood pressure at the time of the measurement.51 Stretch is thought to transfer loading to stiffer elements within the wall that are of greater tensile strength (eg, from elastin to collagen) and, hence, result in an overall stiffening of the wall. It is difficult to separate effects of a sustained elevation of blood pressure (ie, hypertension) from the level of blood pressure at the time of study. It is possible that hypertension results in structural alterations within the wall, possibly by accelerating age-related changes, such as decreased elastin content, increased collagen content, change in type of collagen, and collagen cross-links from advanced glycation end products.52,53 That an acute reduction of blood pressure does not normalize elevated cfPWV in hypertension54 supports this hypothesis. However, other studies using mathematical techniques to compare hypertensive and controls groups at a common pressure do not show a difference in isobaric PWV between hypertensive and normotensive groups.55,56 Similarly, other studies have demonstrated no difference in PWV between hypertensive and normotensive groups when blood pressure is adjusted pharmacologically at the time of the study.57
The present review cannot determine whether cfPWV is associated with hypertension or merely the blood pressure at the time of study. However, given the predictive power of cfPWV for cardiovascular events over and above conventional measures of blood pressure (including ambulatory blood pressure),8 it is important to identify factors responsible for increased stiffening. It is possible that cfPWV relates more closely to the duration of hypertension and its severity (ie, integration of blood pressure over time) that is not captured by a simple measure of chronological age and blood pressure at the time of study. In this regard, cfPWV could be a “better” measure of blood pressure than the conventional office measurement. Alternatively or additionally, there may be other factors independent of classic risk factors and blood pressure or interacting with blood pressure that lead to arterial stiffening. PWV has been noted to be of high heritability58–61 independent of blood pressure, and several studies within this review demonstrated an association of PWV with genetic polymorphisms.21,26,27,33 A genetic component to arterial stiffening is, thus, likely.62
This review is subject to a number of important limitations. First, all of the studies were cross-sectional, and, as such, they highlight associations, and they do not necessarily imply causality. Second, only studies reporting cfPWV as a measure of arterial stiffness were included. However, this measure is clinically the most relevant, because it has been shown to be predictive of cardiovascular morbidity and mortality. The diversity in the description of statistical procedures and results limits the retrieval of publications to the search terms used. We cannot entirely exclude the possibility of publication bias in this systematic review. However, by using a prespecified search strategy and including studies that were not specifically designed to test associations with particular risk factors, bias should be minimized. It is notable that, when we performed the same analysis on excluded studies, we reached similar conclusions. Reported R2 values for individual contributions of variables may have been underestimated, because some variability may be explained by interactions with age and blood pressure. Finally, the majority of studies did not include a measure of atherosclerotic plaque burden or calcification, so we were unable to distinguish between effects of risk factors, per se, and plaque burden/calcification.

Perspectives

The present systematic review reinforces age and blood pressure as being strongly associated with cfPWV. The contribution of other cardiovascular risk factors is small or nonsignificant. The prognostic value of cfPWV is likely to relate to a process of arterial ageing unrelated to classic risk factors other than hypertension. As well as seeking novel environmental/genetic factors that determine arterial stiffness, future studies should include prospective studies in sufficiently large cohorts to elucidate the contribution of hypertension over time to arterial stiffening.

Acknowledgments

Sources of Funding
This work was supported by British Heart Foundation Project grant PG/06/032. We also acknowledge financial support from the Department of Health via the National Institute for Health Research comprehensive Biomedical Research Centre award to Guy’s and St. Thomas' National Health Service Foundation Trust in partnership with King’s College London and King’s College Hospital National Health Service Foundation Trust.
Disclosures
None.

Supplemental Material

File (sup_zhy137653-s1.pdf)

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On the cover: Immunofluorescene single or double labeling of transient receptor potential vanilloid 1 (TRPV1) and endothelin B (ETB) receptors in the renal pelvis of wild-type or TRPV1–/– mice. TRPV1 was labeled with fluorescein isothiocyanate (green fluorescence, arrow) in the left column, while the ETB receptors were labeled with Cy3 (red fluorescence, arrows) in the middle column. The overlay of TRPV1 and ETB is shown in the right column (yellow staining, arrows). The controls by preabsorption of primary antibodies are negative (not shown). (See page 1298.)

Hypertension
Volume 54 • Number 6 • 1 December 2009
Pages: 1328 - 1336
PubMed: 19884567

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Received: 13 June 2009
Revision received: 2 July 2009
Accepted: 6 October 2009
Published online: 2 November 2009
Published in print: 1 December 2009

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Keywords

  1. pulse wave velocity
  2. aortic stiffness
  3. risk factors
  4. atherosclerosis
  5. arteriosclerosis

Subjects

  1. Atherosclerosis
  2. Vascular Biology

Authors

Affiliations

Marina Cecelja
From the King’s College London British Heart Foundation Centre, Cardiovascular Division, Department of Clinical Pharmacology, St. Thomas’ Hospital, London, United Kingdom.
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Philip Chowienczyk
From the King’s College London British Heart Foundation Centre, Cardiovascular Division, Department of Clinical Pharmacology, St. Thomas’ Hospital, London, United Kingdom.
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Notes

Correspondence to Philip Chowienczyk, Department of Clinical Pharmacology, St. Thomas’ Hospital, Lambeth Palace Rd, London SE1 7EH, UK. E-mail [email protected]

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    The Responses of Arterial Stiffness Parameter Beta-Derived Index of the Aorta and Illiac-Femoral Artery to Acute Hypovolemia in Rabbits, Pulse, 12, 1, (76-84), (2024).https://doi.org/10.1159/000539480
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Dissociation of Aortic Pulse Wave Velocity With Risk Factors for Cardiovascular Disease Other Than Hypertension
Hypertension
  • Vol. 54
  • No. 6

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Hypertension
  • Vol. 54
  • No. 6
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