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Association of Parental Hypertension With Concentrations of Select Biomarkers in Nonhypertensive Offspring

Originally published 2008;52:381–386


Children of parents with hypertension are at increased risk of developing high blood pressure. We hypothesize that circulating concentrations of putative biomarkers (that may play a role in development of high blood pressure) are higher in nonhypertensive offspring of parents with hypertension. We compared concentrations of 4 different biomarkers (urinary albumin:creatinine ratio, circulating C-reactive protein, aldosterone:renin ratio, and plasminogen activator inhibitor-1) in nonhypertensive Framingham offspring study participants with none (n=233), 1 (n=474), or both (n=322) parents with hypertension. Parental hypertension was defined as onset before age 60 years, based on longitudinal observations of the original Framingham cohort. Serum C-reactive protein concentrations were higher in nonhypertensive offspring with 1 (median: 1.7; Q1 to Q3: 0.8 to 3.6 mg/L) or both parents with hypertension (median: 1.8; Q1 to Q3: 0.7 to 3.6 mg/L) compared with offspring without parental hypertension (median: 1.4; Q1 to Q3: 0.7 to 3.2 mg/L). In multivariable analyses, parental hypertension was associated with higher serum C-reactive protein concentration in offspring (15% increase per parent with hypertension; P=0.004). Prospectively, the relation of parental hypertension to longitudinal changes in blood pressure in the nonhypertensive offspring was attenuated on adjustment for C-reactive protein (P=0.04 for attenuation). The levels of the other biomarkers evaluated did not significantly differ in offspring according to parental hypertension status. In conclusion, serum C-reactive protein concentrations are higher in nonhypertensive offspring of parents with hypertension. These data suggest that inflammation may partly mediate the familial influences on hypertension risk.

Elevated blood pressure (BP) is an important vascular risk factor associated with increased cardiovascular morbidity and mortality.1 Hypertension (HTN) is a condition with an enormous public health burden, affecting almost one third of all adults in the United States and is associated with substantial health care expenditure.2 Consequently, prevention of HTN is a public health priority.

The underlying pathophysiology of elevated BP, however, is incompletely understood. BP is considered a complex trait influenced by several environmental and genetic factors, with ≈30% to 60% of the interindividual variation in BP being attributed to additive genetic factors.3,4 It is well established that HTN clusters in families5 and that a positive family history represents a major risk factor for future HTN in nonhypertensive offspring.6

Recent studies have indicated that circulating concentrations of several biomarkers that represent distinct biological pathways are correlated with BP levels cross-sectionally and are associated with a greater incidence of HTN prospectively.7–11 For instance, a recent investigation from the Framingham Heart Study demonstrated that circulating concentrations of C-reactive protein (CRP), plasminogen activator inhibitor-1 (PAI-1), and the urinary albumin:creatinine ratio (UACR) predict incident HTN in nonhypertensive individuals during short-term follow-up.12 Framingham investigators have also reported that serum aldosterone concentrations and the aldosterone:renin ratio (ARR) predict incident HTN.8,9 Furthermore, there is evidence that these biomarker levels are heritable traits like BP,9,13,14 raising the possibility that genetic influences on HTN risk may be mediated in part via these putative biomarkers. One approach for evaluating this premise is to examine whether concentrations of candidate biomarkers (known to be associated with the risk of developing HTN) are higher in offspring of parents with HTN. Indeed, a recent study reported that nonhypertensive children of parents with HTN had higher circulating concentrations of CRP compared with children of parents without HTN.15 Other investigators have focused on circulating components of the renin-angiotensin-aldosterone system and urinary albumin excretion in offspring of parents with HTN, but the results have been conflicting.16–19 Previous studies were limited by the evaluation of only single biomarkers and by relatively small samples. To our knowledge, concentrations of multiple biomarkers have not yet been investigated systematically in nonhypertensive offspring of parents with HTN in a large community-based sample.

We hypothesized that, cross-sectionally, nonhypertensive offspring of parents with HTN will have higher levels of select biomarkers (that have been associated with HTN risk) compared with children of parents without HTN. We further postulate that the association of parental HTN with longitudinal BP tracking in the offspring is attenuated on adjustment for biomarkers that are related to parental HTN in the cross-sectional analysis.


Study Sample

The Framingham Heart Study was initiated in 1948 to investigate risk factors for cardiovascular disease in the community.20 Starting in 1971, the Framingham offspring study enrolled 5124 offspring of the original cohort and the spouses of the offspring.21 Participants of the Framingham offspring study cohort are examined at the heart study clinic approximately every 4 years. During these visits, participants undergo a targeted medical history and physical examination, including BP measurements (see below), and laboratory assessment of cardiovascular risk factors. The study protocols were approved by the Boston University Medical Center Institutional Review Board, and all of the participants gave written informed consent.

Offspring study participants who were nonhypertensive (BP <140/90 mm Hg and not on antihypertensive medications) and free of prevalent cardiovascular disease at the sixth examination cycle (1995–1998) were eligible for the present investigation if they had both parents in the original cohort (n=1057) and nonmissing marker values (n=1029). A total of 1804 participants with both parents in the original cohort attended examination 6 (77% of offspring cohort participants with both parents in the original cohort who were alive in 1995). A total of 1582 of those who attended examination 6 were free of cardiovascular disease and had nonmissing marker values. Of these, 1029 were nonhypertensive and included in the present analyses. These 1029 individuals belong to 662 families, with an average of 1.6 (range: 1.0 to 6.0) offspring per family. Parental HTN was defined as a BP ≥140/90 mm Hg or antihypertensive treatment at any time in life before the age of 60 years; we chose to define parental HTN before age 60 years, because the lifetime risk of developing HTN is very high (90%)22; as such, few offspring will have parents who do not eventually develop HTN.

BP Measurement

During the visits at the Framingham Heart Study clinic, BP is measured by a physician on the participants’ left arm using a mercury column sphygmomanometer and a cuff of appropriate size after the individual has been seated in a chair for ≥5 minutes. After another 5 minutes, a second BP reading is obtained using the same protocol. The mean of both measurements is considered the examination BP.

Biomarker Measurements

At the sixth examination cycle, blood was drawn in the morning after an overnight fast with the participant in a supine position for ≈5 to 10 minutes. Samples were immediately centrifuged, and plasma and serum were stored at −80°C until the biomarkers were measured. Of biomarkers measured at examination cycle 6, UACR, CRP, ARR, and PAI-1 have been associated with HTN incidence in this cohort.9,12 So, the present investigation focused on these biomarkers.

The UACR was measured on a spot urine sample obtained in the morning. Urine albumin was assessed quantitatively using an immunoturbidimetric test (Tinaquant Albumin assay, Roche Diagnostics), and urinary creatinine was determined with a modified Jaffe method. Interassay coefficients of variation for urinary albumin and urinary creatinine assays were 7.2% and 2.3%, respectively. High-sensitivity CRP was measured with a nephelometer (Dade Behring BN100) with an average interassay coefficient of variance of 2.2%. Serum aldosterone was measured using a radioimmunoassay (Quest Diagnostics) with an average interassay variation coefficient of 4.0% for high concentrations and 9.8% for low concentrations. Plasma renin was measured using an immunochemiluminometric assay (Nichols assay, Quest Diagnostics) with an average coefficient of variation of 2.0% for high concentrations and 10.0% for low concentrations. Plasma levels of PAI-1 were measured with a commercially available ELISA, as described previously (TintElize PAI-1, Biopool AB).23 The coefficient of interassay variation was 7.7%.

Statistical Analyses

Biomarkers with skewed distributions were natural logarithmically transformed before analyses. Clinical characteristics were descriptively compared between offspring with none, 1, or 2 parents with HTN using general estimating equations to account for correlations within families. A general estimating equation was also used to compare biomarker concentrations among offspring with 1 and 2 parents with HTN with levels in offspring of nonhypertensive parents adjusting for relevant covariates (model 1: age and sex; model 2: age, sex, body mass index [BMI], systolic and diastolic BP, total:high-density lipoprotein [HDL] cholesterol ratio, triglycerides, lipid lowering treatment, hormone replacement therapy, and smoking) that have been previously related to biomarker levels in our cohort.24 We used a trend test that models parental HTN as a 0, 1, and 2 variable because it maximizes statistical power and because previous Framingham data indicate a linear trend for increasing HTN incidence according to the number of parents with HTN.6

To test the hypothesis that the higher risk of HTN in offspring with parental HTN was mediated by higher levels of a biomarker, we conducted additional analyses. First, we related parental HTN to change in systolic BP (SBP) during follow-up (ΔSBP; from examination cycle 6 to examination cycle 7) in the offspring who attended examination cycle 7 (n=963) using censored normal regression models,25 adjusting for age, sex, BMI, systolic and diastolic BP, total:HDL cholesterol ratio, triglycerides, lipid-lowering treatment, hormone replacement therapy, and smoking at baseline. The approach proposed by Levy et al4 and Tobin et al25 was used to account for antihypertensive treatment on follow-up in some individuals. We evaluated the change in SBP alone (as opposed to systolic and diastolic BP), because systolic HTN is the most common form of HTN in the community in middle-aged-to-elderly adults (such as in our sample). Next, we adjusted for the biomarkers that were associated with parental HTN in the principal cross-sectional analyses detailed above. We evaluated whether the regression coefficient for parental HTN (for predicting longitudinal change in offspring SBP on follow-up) was attenuated by adjustment for the putative biomarkers. Significance level of the attenuation was tested using a nonparametric bootstrap with 4999 replications, as described in detail elsewhere.26


Baseline Characteristics

The clinical characteristics, as well as biomarker concentrations, of the study sample stratified by parental HTN status are displayed in Tables 1 and 2. Although all of the offspring had BP levels within the nonhypertensive range (by definition), offspring who had both parents with HTN displayed slightly higher levels for systolic and diastolic BPs compared with offspring of whom both parents were nonhypertensive. Furthermore, the mean age of nonhypertensive offspring participants decreased as the number of parents with HTN increased. Specifically, offspring with no parental HTN were, on average, 58.2 years old (range: 33 to 75 years); offspring with 1 or 2 hypertensive parents had a mean age of 53.9 years (range: 33 to 78 years) and 52.3 years (range: 35 to 71 years), respectively. Offspring mean levels of BMI, total cholesterol, and blood sugar and the offspring prevalence of obesity (BMI: ≥30 kg/m2), current smoking, and diabetes did not differ by parental HTN status (Table 1).

Table 1. Clinical Characteristics Stratified by Parental HTN Status

CharacteristicsNo Parental HTN (n=233)1 Parent With HTN (n=474)2 Parents With HTN (n=322)P*
Values for clinical features are means (SD) or percentages.
*Data show the P value for trend in the number of parents with HTN adjusted for age and sex (except for age and sex characteristics).
Mean age, y58.2 (9.1)53.9 (8.7)52.3 (7.2)<0.0001
Women, %59.751.954.00.30
Systolic BP, mm Hg117 (12)117 (11)120 (11)<0.0001
Diastolic BP, mm Hg71 (8)73 (8)75 (7)<0.0001
BMI, kg/m227.0 (4.7)26.9 (4.7)27.1 (4.5)0.73
BMI ≥30 kg/m2, %21.520.323.70.66
Total cholesterol, mg/dL212 (60)206 (38)206 (40)0.88
Total:HDL cholesterol ratio4.6 (3.6)4.3 (1.5)4.2 (1.5)0.16
Triglycerides, mg/dL, median (Q1, Q3)111 (75, 158)106 (73, 146)106 (75, 161)0.70
Lipid-lowering treatment, %
Current smoker, %13.715.419.30.24
Hormone replacement therapy, %20.927.220.70.92
Blood sugar, mg/dL98 (15)98 (15)98 (24)0.69
Diabetes, %

Table 2. Biomarker Levels in the Study Sample Stratified by Parental HTN Status

BiomarkerNo Parental HTN (n=233)1 Parent With HTN (n=474)2 Parents With HTN (n=322)
Values for biomarkers are medians (Q1, Q3).
*Data are available in 872 individuals.
CRP, mg/L1.4 (0.7, 3.2)1.7 (0.8, 3.6)1.8 (0.7, 3.6)
PAI-1, ng/mL19.8 (14.0, 29.0)18.2 (11.7, 29.2)19.3 (11.7, 30.5)
ARR0.82 (0.47, 1.33)0.80 (0.50, 1.29)0.83 (0.51, 1.31)
UACR, mg/g*5.1 (1.8, 11.5)5.3 (2.2, 11.7)4.4 (1.8, 9.5)

Association of Parental HTN With Offspring Biomarker Levels

Mean CRP concentrations were higher in offspring with 1 or 2 parents with HTN compared with offspring of parents without HTN (Table 2). Regression analyses revealed a 15% increase in adjusted mean CRP concentrations per parent with premature HTN (P=0.004 for trend in a multivariable model adjusting for age, sex, BMI, systolic and diastolic BP, total:HDL cholesterol ratio, triglycerides, lipid-lowering treatment, hormone replacement therapy, and smoking; Table 3). Median and interquartile range for offspring ARR did not differ by parental HTN status (Table 2). However, regression analyses demonstrated a borderline significant ≈7% increase in offspring log-ARR levels per parent with HTN (Table 3). By contrast, concentrations of PAI-1 and UACR did not differ among the offspring according to parental HTN status (Tables 2 and 3). The power to detect a contribution to model R2 of the magnitude observed for CRP was as follows: 90% for PAI-1, 82% for ARR, and 74% for UACR.

Table 3. Association of Parental HTN With Offspring Biomarkers

Log BiomarkerAge- and Sex-Adjusted Model: Fold-Increase in Marker When Parental HTN Present*PMultivariable-Adjusted Model: Fold-Increase in Marker When Parental HTN Present*P
The values in the parentheses are the 95% CI of the exponentiated regression coefficient. Multivariable model is adjusted for age, sex, BMI, SBP, diastolic BP, total:HDL cholesterol ratio, triglycerides, lipid-lowering treatment, hormone replacement therapy, and smoking.
*Data indicate the fold-increase in biomarker level per parent with HTN.
C-reactive protein1.13 (1.01 to 1.26)0.031.15 (1.04 to 1.26)0.004
PAI-11.00 (0.94 to 1.06)0.981.00 (0.95 to 1.05)0.97
Aldosterone/renin ratio1.08 (1.00 to 1.15)0.041.07 (1.00 to 1.15)0.06
UACR0.91 (0.77 to 1.07)0.250.86 (0.72 to 1.02)0.08

Attenuation of Relation of Parental HTN to Longitudinal Change in Offspring BP on Adjustment for CRP

In the Framingham Offspring Study, parental HTN predicts incident HTN in the offspring.6 Consistent with this finding, we demonstrated in the present analyses that parental HTN was related to the change in SBP in the offspring (Table 4, model A). The mean increase in SBP during follow-up was 3.6 mm Hg (95% CI: 2.0 to 5.3 mm Hg), 2.0 mm Hg (95% CI: 0.8 to 3.1 mm Hg), and 4.7 mm Hg (95% CI: 3.3 to 6.0 mm Hg) in offspring with 0, 1, or 2 parents with HTN, respectively, after adjustments for baseline BP levels and antihypertensive treatment at examination cycle 7 (end of follow-up). Likewise, CRP at baseline was positively associated with ΔSBP during follow-up in the offspring (Table 4, model B). Importantly, the relation of parental HTN to ΔSBP in the offspring was attenuated on adjustment for CRP (Table 4, model C; P for attenuation=0.042).

Table 4. Association of Parental HTN With Change in Offspring SBP on Follow-Up: Impact of Adjustment for CRP

Exposure of Interestβ (SE)*95% CI of βP
Dependent variable is the change in SBP in millimeters of mercury during a 3.3-year follow-up in initially normotensive offspring.
*All of the models are adjusted for age, sex, BMI, SBP, diastolic BP, total:HDL cholesterol ratio, triglycerides, lipid-lowering treatment, hormone replacement therapy, and smoking at baseline.
Model A: Parental HTN*1.32 (0.62)0.10 to 2.530.034
Model B: log CRP*1.31 (0.55)0.23 to 2.390.017
Model C: Parental HTN*1.16 (0.61)−0.04 to 2.360.058
Model C: Log CRP1.21 (0.55)0.14 to 2.280.027


Principal Findings

We evaluated the association of parental HTN status with circulating biomarker concentrations in nonhypertensive offspring in a large, community-based sample. Compared with nonhypertensive offspring of parents without HTN, offspring with 1 or 2 parents with HTN (before the age of 60 years) had higher mean CRP concentrations. This association remained statistically significant even after a conservative Bonferroni correction for testing multiple biomarkers. In absolute terms, we found an ≈15% increase in offspring mean CRP concentrations per parent with HTN. Furthermore, we demonstrated that the relation of parental HTN to change in SBP in offspring on prospective follow-up is attenuated on adjustment for CRP. These data suggest that the familial risk for the increase in offspring SBP during follow-up may be partially mediated via their higher antecedent CRP concentrations. However, mean concentrations of the other biomarkers tested (PAI-1, UACR, and ARR) did not differ among offspring with versus without parental HTN.

Comparison With Previous Findings


Our findings regarding the association of offspring mean CRP concentrations with parental HTN status are consistent with results of a much smaller study in children (n=120) reported by Diaz et al.15 The latter study evaluated adolescents (mean age: ≈18 years) from families recruited through hypertensive parents and did not analyze levels according to the number of parents with HTN. We confirm this association in a larger community-based sample of middle-aged men and women. Furthermore, we extend these finding by demonstrating that the mean CRP concentrations in nonhypertensive offspring increase with the number of parents with HTN.

We have reported previously that parental HTN predicts incident HTN.6 Consistent with these findings, we demonstrate that parental HTN predicts change in offspring SBP during follow-up. Of note, the association of parental HTN with change in SBP during follow-up was attenuated when CRP was incorporated into the multivariable model. This is consistent with the notion that the risk of an increase in offspring SBP on follow-up conferred by parental HTN may be mediated in part by the association of parental HTN with mean CRP concentrations in the offspring.

In previous cross-sectional and longitudinal studies, CRP concentrations have been shown to strongly correlate with BP levels27 and the incidence7 of HTN. Recently, using a multimarker approach to predict new-onset HTN, Wang et al12 demonstrated that CRP, UACR, and PAI-1 concentrations were significant correlates of incident HTN of a panel of biomarkers tested. In addition to being a marker of HTN risk, a causal role for CRP in the pathogenesis of high BP is supported by experimental studies.28 For instance, CRP has been shown to reduce the expression and bioactivity of the endothelial NO synthase and release of prostacyclin in human aortic endothelial cells.28–30 Endothelial NO synthase catalyzes endothelial synthesis of NO, which is a potent vasodilator.31 Furthermore, CRP leads to increased PAI-1 expression and activity in human aortic endothelial cells.32 In addition, CRP upregulates angiotensin type 1 receptors in vascular smooth muscle cells in vivo and in vitro.33 Importantly, the BP-modulating effects of the renin-angiotensin- aldosterone system are mediated through this receptor.34

The increased CRP concentrations in nonhypertensive offspring of parents with HTN suggest that CRP might be an important heritable intermediate phenotype for HTN. This is further supported by twin and population-based studies providing heritability estimates for CRP ranging from 20% to 52%.35,36

Albuminuria and HTN

Recent studies have demonstrated that UACR concentrations are positively associated with BP progression and the incidence of HTN in nonhypertensive individuals without diabetes in the community.11 In nonhypertensive offspring of parents with HTN, urinary albumin excretion has been found to be increased in some18 but not in other studies.19 In the present analyses, UACR measured in a spot urine was not related to the parental HTN status. This finding does not exclude the possibility that UACR may be a valuable marker of HTN risk.

Renin-Angiotensin-Aldosterone-System and HTN

Framingham investigators have shown previously that serum aldosterone concentrations and the ARR predict incident HTN8,9 and that the ARR has a substantial heritable component (h2=0.40).9 Data on plasma concentrations of circulating components of the renin-angiotensin-aldosterone system in offspring of hypertensive parents are sparse and have yielded inconsistent results.16,17 We observed a borderline statistically significant association of offspring ARR with parental HTN. However, considering the number of biomarkers tested and the level of significance, these findings have to be interpreted with caution.

PAI-1 and HTN

Framingham investigators and others have reported that PAI-1 concentrations also correlate positively with SBP cross-sectionally10,37 and are associated with incident HTN prospectively.12 In the present investigation, concentrations of PAI-1 in offspring did not vary according to parental HTN status. However, this finding does not exclude an important role for PAI-1 in the development of HTN.

Strengths and Limitations

The strengths of the present study include the large community-based design, the availability of a panel of biomarkers, and the standardized assessment of BP and clinical covariates. However, some limitations should be noted. We focused on biomarkers that have been associated previously with incident HTN in the Framingham offspring sample. Therefore, several other biomarkers linked to HTN in other samples (eg, fibrinogen38) were not included in the present analyses, because these biomarkers were not associated with incident HTN or with BP progression in our sample.10,12 Furthermore, several other biomarkers that have previously been associated with parental HTN status in smaller studies (eg, leptin39) were not measured in our cohort. In addition, all of the biomarkers were measured only on a single occasion, raising the possibility of misclassification. We did not have information regarding the presence of systemic inflammatory conditions in our participants at the baseline examination 6. Although such conditions can potentially alter biomarker concentrations, it is unlikely that the prevalence of these conditions will vary according to parental HTN status. Therefore, we would expect that a lack of adjustment for inflammatory conditions would result in nondifferential misclassification, biasing the results toward a null hypothesis of no association of parental HTN with offspring CRP levels.

The UACR was measured in a spot urine sample and not in a 24-hour urine collection. However, urinary albumin excretion from spot urine has been shown to serve as an excellent predictive marker in previous studies.40 Good correlation between urinary albumin excretion measured in a 24-hour urine collection and in a spot urine have been reported.41 Lastly, our sample was composed of white individuals of European descent; the generalizability of our findings to other races and/or ethnicities is unknown.


Given the public health burden posed by high BP, it is important to identify nonhypertensive individuals who are at greatest risk of developing the condition and to elucidate biological mechanisms that underlie disease susceptibility. Circulating biomarkers offer a potential approach in this regard. Given the substantial heritability of HTN, we investigated whether offspring of individuals with high BP have an altered biomarker profile antedating the development of high BP. We examined the cross-sectional association of concentrations of 4 biomarkers, associated previously with incident HTN, in nonhypertensive offspring according to their parental HTN status. Compared with offspring without parental HTN, offspring with parental HTN had higher CRP concentrations. These data are consistent with the notion that inflammation may mediate, in part, the familial influences on HTN risk. Additional studies are warranted to confirm our findings and to investigate a larger panel of biomarkers in individuals with and without parental HTN.

Sources of Funding

This work was supported by research grants (National Heart, Lung and Blood Institute contracts N01-HC-25195, K23-HL-074077 [to T.J.W.], and 2K24 HL04334 [to R.S.V.]) from the National Heart, Lung and Blood Institute; R01 AG028321 from the National Institute of Aging (National Institutes of Health, Bethesda, Md); an American Diabetes Association Research grant; and by Roche Diagnostics, who donated assay reagents for measurement of urinary albumin and creatinine. J.B.M. was supported by a Career Development Award from the American Diabetes Association and by National Institute of Diabetes and Kidney Diseases grant K24 DK080140. C.N.-C. is supported by HL080025, a Doris Duke Charitable Foundation Clinical Scientist Development Award, and a Burroughs Wellcome Fund Career Award for Medical Scientists.




Correspondence to Ramachandran S. Vasan, Framingham Heart Study, 73 Mount Wayte Ave, Framingham, MA 01702-5803. E-mail


  • 1 Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr, Jones DW, Materson BJ, Oparil S, Wright JT Jr, Roccella EJ. Seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure. Hypertension. 2003; 42: 1206–1252.LinkGoogle Scholar
  • 2 Rosamond W, Flegal K, Friday G, Furie K, Go A, Greenlund K, Haase N, Ho M, Howard V, Kissela B, Kittner S, Lloyd-Jones D, McDermott M, Meigs J, Moy C, Nichol G, O'Donnell CJ, Roger V, Rumsfeld J, Sorlie P, Steinberger J, Thom T, Wasserthiel-Smoller S, Hong Y. Heart disease and stroke statistics–2007 update: a report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Circulation. 2007; 115: e69–e171.LinkGoogle Scholar
  • 3 Hottenga JJ, Boomsma DI, Kupper N, Posthuma D, Snieder H, Willemsen G, de Geus EJ. Heritability and stability of resting blood pressure. Twin Res Hum Genet. 2005; 8: 499–508.CrossrefMedlineGoogle Scholar
  • 4 Levy D, DeStefano AL, Larson MG, O'Donnell CJ, Lifton RP, Gavras H, Cupples LA, Myers RH. Evidence for a gene influencing blood pressure on chromosome 17. Genome scan linkage results for longitudinal blood pressure phenotypes in subjects from the Framingham Heart Study. Hypertension. 2000; 36: 477–483.CrossrefMedlineGoogle Scholar
  • 5 Stamler R, Stamler J, Riedlinger WF, Algera G, Roberts RH. Family (parental) history and prevalence of hypertension. Results of a nationwide screening program. JAMA. 1979; 241: 43–46.CrossrefMedlineGoogle Scholar
  • 6 Parikh NI, Pencina MJ, Wang TJ, Benjamin EJ, Lanier KJ, Levy D, D'Agostino RB Sr, Kannel WB, Vasan RS. A risk score for predicting near-term incidence of hypertension: the Framingham Heart Study. Ann Intern Med. 2008; 148: 102–110.CrossrefMedlineGoogle Scholar
  • 7 Sesso HD, Buring JE, Rifai N, Blake GJ, Gaziano JM, Ridker PM. C-reactive protein and the risk of developing hypertension. JAMA. 2003; 290: 2945–2951.CrossrefMedlineGoogle Scholar
  • 8 Vasan RS, Evans JC, Larson MG, Wilson PW, Meigs JB, Rifai N, Benjamin EJ, Levy D. Serum aldosterone and the incidence of hypertension in nonhypertensive persons. N Engl J Med. 2004; 351: 33–41.CrossrefMedlineGoogle Scholar
  • 9 Newton-Cheh C, Guo CY, Gona P, Larson MG, Benjamin EJ, Wang TJ, Kathiresan S, O'Donnell CJ, Musone SL, Camargo AL, Drake JA, Levy D, Hirschhorn JN, Vasan RS. Clinical and genetic correlates of aldosterone-to-renin ratio and relations to blood pressure in a community sample. Hypertension. 2007; 49: 846–856.LinkGoogle Scholar
  • 10 Poli KA, Tofler GH, Larson MG, Evans JC, Sutherland PA, Lipinska I, Mittleman MA, Muller JE, D'Agostino RB, Wilson PW, Levy D. Association of blood pressure with fibrinolytic potential in the Framingham offspring population. Circulation. 2000; 101: 264–269.CrossrefMedlineGoogle Scholar
  • 11 Wang TJ, Evans JC, Meigs JB, Rifai N, Fox CS, D'Agostino RB, Levy D, Vasan RS. Low-grade albuminuria and the risks of hypertension and blood pressure progression. Circulation. 2005; 111: 1370–1376.LinkGoogle Scholar
  • 12 Wang TJ, Gona P, Larson MG, Levy D, Benjamin EJ, Tofler GH, Jacques PF, Meigs JB, Rifai N, Selhub J, Robins SJ, Newton-Cheh C, Vasan RS. Multiple biomarkers and the risk of incident hypertension. Hypertension. 2007; 49: 432–438.LinkGoogle Scholar
  • 13 Best LG, North KE, Tracy RP, Lee ET, Howard BV, Palmieri V, Maccluer JW. Genetic determination of acute phase reactant levels: the strong heart study. Hum Hered. 2004; 58: 112–116.CrossrefMedlineGoogle Scholar
  • 14 Fox CS, Yang Q, Guo CY, Cupples LA, Wilson PW, Levy D, Meigs JB. Genome-wide linkage analysis to urinary microalbuminuria in a community-based sample: the Framingham Heart Study. Kidney Int. 2005; 67: 70–74.CrossrefMedlineGoogle Scholar
  • 15 Diaz JJ, Arguelles J, Malaga I, Perillan C, Dieguez A, Vijande M, Malaga S. C-reactive protein is elevated in the offspring of parents with essential hypertension. Arch Dis Child. 2007; 92: 304–308.CrossrefMedlineGoogle Scholar
  • 16 Van Hooft IM, Grobbee DE, Derkx FH, de Leeuw PW, Schalekamp MA, Hofman A. Renal hemodynamics and the renin-angiotensin-aldosterone system in normotensive subjects with hypertensive and normotensive parents. N Engl J Med. 1991; 324: 1305–1311.CrossrefMedlineGoogle Scholar
  • 17 Horky K, Jachymova M, Jindra A, Savlikova J, Peleska J, Umnerova V, Linhart A. Metabolic, humoral and haemodynamic characteristics of normotensive offspring from hypertensive families. J Hum Hypertens. 1996; 10 (suppl 3): S85–S87.Google Scholar
  • 18 Grunfeld B, Perelstein E, Simsolo R, Gimenez M, Romero JC. Renal functional reserve and microalbuminuria in offspring of hypertensive parents. Hypertension. 1990; 15: 257–261.LinkGoogle Scholar
  • 19 Purzycki Z, Wyrzykowski B, Gockowski K, Winnicki MM, Kazmirowicz M, Krupa-Wojciechowska B, Sowers JR. The influence of exercise on albumin excretion rate in borderline hypertensives and in offspring of hypertensive parents. J Hum Hypertens. 1997; 11: 119–123.CrossrefMedlineGoogle Scholar
  • 20 Dawber TR, Kannel WB, Revotskien, Stokes J III, Kagan A, Gordon T. Some factors associated with the development of coronary heart disease: six years’ follow-up experience in the Framingham study. Am J Public Health Nations Health. 1959; 49: 1349–1356.CrossrefMedlineGoogle Scholar
  • 21 Kannel WB, Feinleib M, McNamara PM, Garrison RJ, Castelli WP. An investigation of coronary heart disease in families. The Framingham Offspring Study. Am J Epidemiol. 1979; 110: 281–290.CrossrefMedlineGoogle Scholar
  • 22 Vasan RS, Beiser A, Seshadri S, Larson MG, Kannel WB, D'Agostino RB, Levy D. Residual lifetime risk for developing hypertension in middle-aged women and men: the Framingham Heart Study. JAMA. 2002; 287: 1003–1010.CrossrefMedlineGoogle Scholar
  • 23 Declerck PJ, Alessi MC, Verstreken M, Kruithof EK, Juhan-Vague I, Collen D. Measurement of plasminogen activator inhibitor 1 in biologic fluids with a murine monoclonal antibody-based enzyme-linked immunosorbent assay. Blood. 1988; 71: 220–225.CrossrefMedlineGoogle Scholar
  • 24 Kathiresan S, Larson MG, Vasan RS, Guo CY, Gona P, Keaney JF Jr, Wilson PW, Newton-Cheh C, Musone SL, Camargo AL, Drake JA, Levy D, O'Donnell CJ, Hirschhorn JN, Benjamin EJ. Contribution of clinical correlates and 13 C-reactive protein gene polymorphisms to interindividual variability in serum C-reactive protein level. Circulation. 2006; 113: 1415–1423.LinkGoogle Scholar
  • 25 Tobin MD, Sheehan NA, Scurrah KJ, Burton PR. Adjusting for treatment effects in studies of quantitative traits: antihypertensive therapy and systolic blood pressure. Stat Med. 2005; 24: 2911–2935.CrossrefMedlineGoogle Scholar
  • 26 Hall P, Wilson SR. The Consultant’s Forum: two guidelines for bootstrap hypothesis testing. Biometrics. 1991; 47: 757–762.CrossrefGoogle Scholar
  • 27 Bermudez EA, Rifai N, Buring J, Manson JE, Ridker PM. Interrelationships among circulating interleukin (IL)-6, C-reactive protein, and traditional cardiovascular risk factors in women. Arterioscler Thromb Vasc Biol. 2002; 22: 1668–1673.LinkGoogle Scholar
  • 28 Venugopal SK, Devaraj S, Jialal I. Effect of C-reactive protein on vascular cells: evidence for a proinflammatory, proatherogenic role. Curr Opin Nephrol Hypertens. 2005; 14: 33–37.CrossrefMedlineGoogle Scholar
  • 29 Venugopal SK, Devaraj S, Yuhanna I, Shaul P, Jialal I. Demonstration that C-reactive protein decreases eNOS expression and bioactivity in human aortic endothelial cells. Circulation. 2002; 106: 1439–1441.LinkGoogle Scholar
  • 30 Venugopal SK, Devaraj S, Jialal I. C-reactive protein decreases prostacyclin release from human aortic endothelial cells. Circulation. 2003; 108: 1676–1678.LinkGoogle Scholar
  • 31 Yetik-Anacak G, Catravas JD. Nitric oxide and the endothelium: history and impact on cardiovascular disease. Vascul Pharmacol. 2006; 45: 268–276.CrossrefMedlineGoogle Scholar
  • 32 Devaraj S, Xu DY, Jialal I. C-reactive protein increases plasminogen activator inhibitor-1 expression and activity in human aortic endothelial cells: implications for the metabolic syndrome and atherothrombosis. Circulation. 2003; 107: 398–404.LinkGoogle Scholar
  • 33 Wang CH, Li SH, Weisel RD, Fedak PW, Dumont AS, Szmitko P, Li RK, Mickle DA, Verma S. C-reactive protein upregulates angiotensin type 1 receptors in vascular smooth muscle. Circulation. 2003; 107: 1783–1790.LinkGoogle Scholar
  • 34 Crowley SD, Gurley SB, Coffman TM. AT(1) receptors and control of blood pressure: the kidney and more. Trends Cardiovasc Med. 2007; 17: 30–34.CrossrefMedlineGoogle Scholar
  • 35 de Maat MP, Bladbjerg EM, Hjelmborg JB, Bathum L, Jespersen J, Christensen K. Genetic influence on inflammation variables in the elderly. Arterioscler Thromb Vasc Biol. 2004; 24: 2168–2173.LinkGoogle Scholar
  • 36 MacGregor AJ, Gallimore JR, Spector TD, Pepys MB. Genetic effects on baseline values of C-reactive protein and serum amyloid a protein: a comparison of monozygotic and dizygotic twins. Clin Chem. 2004; 50: 130–134.CrossrefMedlineGoogle Scholar
  • 37 Eliasson M, Jansson JH, Nilsson P, Asplund K. Increased levels of tissue plasminogen activator antigen in essential hypertension. A population-based study in Sweden. J Hypertens. 1997; 15: 349–356.CrossrefMedlineGoogle Scholar
  • 38 Letcher RL, Chien S, Pickering TG, Sealey JE, Laragh JH. Direct relationship between blood pressure and blood viscosity in normal and hypertensive subjects. Role of fibrinogen and concentration. Am J Med. 1981; 70: 1195–1202.CrossrefMedlineGoogle Scholar
  • 39 Papadopoulos DP, Makris TK, Poulakou M, Papazachou UG, Hatzizacharias AN, Perrea DN, Votteas VE. Human soluble leptin receptor concentration in healthy offspring of hypertensive parents. J Clin Hypertens (Greenwich). 2006; 8: 797–802.CrossrefMedlineGoogle Scholar
  • 40 Nelson RG, Knowler WC, Pettitt DJ, Saad MF, Charles MA, Bennett PH. Assessment of risk of overt nephropathy in diabetic patients from albumin excretion in untimed urine specimens. Arch Intern Med. 1991; 151: 1761–1765.CrossrefMedlineGoogle Scholar
  • 41 Eshoj O, Feldt-Rasmussen B, Larsen ML, Mogensen EF. Comparison of overnight, morning and 24-hour urine collections in the assessment of diabetic microalbuminuria. Diabet Med. 1987; 4: 531–533.CrossrefMedlineGoogle Scholar


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