no correlation and low agreement of imaging and inflammatory atherosclerosis’ markers in familial...

Copyright © 2008 Society for Heart Attack Prevention and Eradication. All Rights Reserved.

No correlation and low agreement of imaging and inflammatory

atherosclerosis markers in familial ’hypercholesterolemia

Lilton R.C. Martinez MD, Marcio H. Miname MD, Luiz A. Bortolotto MD, Ana P.M. Chacra MD, Carlos E. Rochitte MD, Andrei C.

Sposito MD, Raul D. Santos MD,PhD.Lipid Clinic Heart Institute InCor-University of Sao Paulo Medical

School Hospital Sao Paulo, Brazil

Martinez LRC et al . Atherosclerosis (2008), doi:10.1016/j.atherosclerosis.2007.12.014


Background

• Familial hypercholesterolemia (FH) is the most frequent

monogenic hereditary disorder in the general population.

• If left untreated, 85% of males and 50% of females with

FH will suffer a premature coronary heart disease (CHD)

event, and as many as 30% of these patients will not survive

their first myocardial infarction.



Background

• However, there is evidence indicating that the clinical course of

CHD in FH is variable in its onset and severity, with some

patients developing clinical manifestations earlier than others

despite elevated LDL-C levels.

• The use of inflammatory biomarkers, as well as imaging markers

of subclinical atherosclerosis has been proposed as tools to

improve CHD risk stratification in FH subjects.



Background

• So far the relation between inflammatory biomarkers like high

sensitivity C-reactive protein (CRP), white blood cell count (WBC)

and imaging markers of carotid and coronary subclinical

atherosclerosis e.g. carotid intima media thinckness (IMT),

coronary artery calcification (CAC) and markers of aortic

stiffness such as carotid-femoral pulse wave velocity was not

yet explored concomitantly in FH subjects.



Objective

• Our purpose was to study the determinants of coronary and

carotid subclinical atherosclerosis as well as aortic stiffness

and their relation in FH subjects.

• Furthermore, the agreement degree of imaging and

inflammatory biomarkers’ severity used to predict CHD risk

was evaluated.



Methods

• 89 FH (34 males, mean age 39 ± 14 years, range 14-69 years) and

31 normal subjects (NL) (16 males, 40 ± 12years) were studied.

• Coronary calcium score quantification was performed with the

AquillionR 16-64 multiple detector computerized tomography

(MDCT) scanner (Toshiba Medical Systems Corporation,

Otawara, Japan).

• Calcium scores were calculated by the Agatston’s method.



Methods

• Aortic stiffness was evaluated by carotid-femoral pulse wave

velocity (PWV) with Complior (Colson, Garges les Gonesses,

France).

• Carotid intima media thickness (IMT) was determined on the right

common carotid artery with an automated ultrasonographic

“echotracking” device, Wall-Track System2 (PIE MEDICAL,

Maastricht, Netherlands), with a probe of 7.5 MHz.



.


Methods

Clinical CHD risk stratification: CHD risk was calculated by 2 methods

• 1-Total 10-year CHD risk was calculated by Framingham risk scores (FRS).

• 2-Clinical and laboratory risk factors, proposed by Civiera et al. for FH subjects: age >30 years for men, and >45 years for women, smoking, high blood pressure, diabetes, early history of CHD in the family, HDL-C <40 mg/dl, LDL-C >330 mg/dl, Lp(a) >60 mg/dl.

• FH patients were considered at high risk for CHD if had >2 risk factors.


Methods

Imaging and inflammatory markers severity:

• CCS >75th% for age and sex

• IMT >900 μm

• PWV >12 m/s

• CRP levels >3 mg/l



Methods

Statistical analysis• The determinants of IMT, CAC and PWV were

evaluated by multivariate analysis.

• CAC was explored as both continuous Log(CCS+1) and categorical variables (CAC>0 vs CAC=0)

• The agreement degree of markers’ severity was determined by kappa statistics.



Results• Table 1: Clinical characteristics of FH patients and NL subjects


0.0013 (9.6 %)80 (89.9 %)Family history of early CHD

0.0010 (0%)26 (29.2 %)Xanthomas, n (%)

0.00030 (0%)28 (31.5%)Previous statin use, n (%)

0.181 (3 %)12 (13.5 %)Metabolic Syndrome, n (%)

0.0023.2 ± 2.96.7 ± 5.7FRS (% 10 years)

0.5476 ± 677 ± 9DBP (mmHg)

0.14117 ± 8121 ± 14SBP (mmHg)

0.181 (3.2 %)12 (13.5 %)Hypertension, n (%)

0.223(9.6 %)13(14.6 %)Smoking habit, n (%)

0.0240.95 ± 0.050.92 ± 0.06Waist/hip

0.191 ± 1295 ± 10Hip (cm)

0.887 ± 1188 ± 12Waist (cm)

0.1424.7 ± 3.525.9 ± 4.9BMI (kg/m2)

1.024 (77.4 %)68 (76.4 %)Caucasians n (%)

0.1916 (51.6 %)34 (38.2 %)Male, n (%)

0.8540 ± 12 (19-69)39 ± 14 (14-69)Age, years (ranges)

PNL (n=31) FH (n=89)


Results• Table 2: Laboratorial characteristics of the FH patients and NL

subjects

< 0.0014,089 ± 1,67310,736 ± 4,809LYS (LDL-c x age)

0.0466,452 ± 1,5467,198 ± 2,083White blood cells 103/mm3

0.391.3( 0.2-8)1.7 (0.2-34)CRP (mg/l) median (range)

< 0.00111 (1-127)39 (1-282)Lp(a) (mg/dl) median (range)

< 0.0010.5 ± 0.21.3 ± 0.5Apolipoprotein B/Apolipoprotein A-I

< 0.0010.8 ± 0.21.6 ± 0.5Apolipoprotein B (g/l)

0.0081.48 ± 0.21.33 ± 0.3Apolipoprotein A-I (g/l)

0.1488 ± 1194 ± 29Glucose (mg/dl)

< 0.0011.6 ± 1.12.9 ± 1.7TG/HDL-cholesterol

< 0.00183 ± 36133 ± 58TG (mg/dl)

< 0.001119 ± 29309 ± 99Non HDL-cholesterol (mg/dl)

< 0.001 2.0 ± 0.86.0 ±2.8LDL-cholesterol/HDL-cholesterol

< 0.001102 ± 26279 ± 97LDL -cholesterol (mg/dl)

0.0855 ± 1350 ± 13HDL - cholesterol (mg/dl)

< 0.001174 ± 27359 ± 97TC (mg/dl)

PNL (n=31)FH (n=89)



Results

In comparison with NL FH patients presented (see table 3):

• almost three times more CAC than NL (p = 0.024), • almost six times more subjects with CCS > 75th% for

age and gender (p = 0.041), • higher CCS than NL (p = 0.026). • higher Carotid IMT (p = 0.027),• higher aortic PWV values (p = 0.007)



Table 3: CAC, IMT and PWV in FH patients and NL subjects.

0.0260.02

0 (0-54) 4.5 ± 13

0 (0-798) 46 ± 140

CCS Agatston units median (ranges) mean ± SD

0.876623 ± 7966596 ± 772Carotid diameter (μm)

0.99460 ± 178461 ± 194Carotid distension (μm)

0.027593 ± 111653 ± 160Carotid IMT (μm)

0.0078.5 ± 19.2 ± 1.5PWV (m/s)

0.0411 (4%)21 (23%)CCS ≥ 75th %

0.0243 (12%)30 (34%)CAC prevalence n (%)

PNL (n=31)FH (n=89)



Table 4: Univariate determinants of CAC as continuous and dichotomous variable, IMT and PWV in FH patients

0.08-----Male gender

CAC dichotomous p=p =

Log(CCS+1)r =p =

PWVr =p =

IMTr =

Determinants

0.0010.0020.33--0.00010.55Carotid diameter (μm)0.0140.0070.29----PWV (m/s)

-0.020.260.00080.35--IMT (μm)---0.0030.320.020.26Log (CCS+1)

-0.040.23--Apolipoprotein A-I (g/l)0.00360.0080.280.020.26--Lp(a) (mg/dl)

----0.050.22Apolipoprotein B (g/l)

----0.010.28CRP (mg/l)---0.010.260.020.26Glucose (mg/dl)

0.0240.020.25--0.030.24TG / HDL- cholesterol 0.020.010.270.030.240.030.23TG (mg/dl)

-0.040.22----LDL-cholesterol /HDL- cholesterol 0.0440.020.25----LDL-cholesterol (mg/dl)

0.020.25----Total cholesterol (mg/dl)

<0.0010.00010.510.00010.520.0030.32LYS

<0.0010.00010.480.00020.390.0060.29Civiera (high risk)

<0.0010.00010.540.00010.440.00010.40FRS

----0.0050.31PP (mmHg)

--0.010.270.0090.28DBP. (mmHg)

--0.020.260.00030.39SBP (mmHg)0.04------Xanthoma0.001------Metabolic Syndrome

<0.0010.00010.430.00010.620.0020.33Age (years)


Carotid IMT determinants

• Parameters associated with carotid IMT in univariate analyses are shown in table 4.

• The following parameters were independently associated with IMT in multivariate linear regression analyses: FRS (r2 = 0.36 p = 0.0001), Apo B (r2 = 0.032, p = 0.02) systolic blood pressure (r2 = 0.26, p = 0.0045).

• Considered these three variables explained only one third of IMT variability in FH subjects (r2 = 0.33, p = 0.001).



Aortic stiffness determinants

Parameters associated with PWV in univariate analyses are shown in table 4.

Multivariate linear regression analyses: • only age was independently correlated with PWV• (r2 = 0.37, p = 0.0001), explaining 37% of its variability.



CAC determinants


Parameters associated with presence of CAC as dichotomous in univariate analyses (table 4).

Multivariate logistic analyses:• FRS (p = 0.0027),

•FRS > 5.5% had an odds ratio = 6.15 (95% CI: 2.28-6.56)(sensitivity = 74% and specificity = 69%).

•LYS (LDL x year score) (p = 0.0228)•LYS > 10,797 (in a mean age of 38.5 years correspond a LDL-C of 280 mg/dl, for example) had an odds ratio = 9.86 (95% CI: 3.48–27.89)

•ROC analysis, showed areas under the curve for

•LYS 0.82 •FRS 0.80


CAC Intensity

•Parameters associated with intensity of CAC e.g. log (CCS + 1) as a continuous variable in univariate analyses (table 4).

•Multivariate regression analyses, male gender (r2 = 0.29, p = 0.0001) LYS (r2 = 0.36, p = 0.0027).

•Considering these two variables, it was possible to explain 31% of the CAC intensity variability (r2 = 0.31, p = 0.0009).



Table 5: Agreement degree of imaging and inflammatory markers severity in FH subjects


0.031CRP > 3 (mg/l)PWV > 12 (m/s)

0.064CRP > 3 (mg/l)IMT > 900 (μm)

0.517PWV > 12 (m/s)IMT > 900 (μm)

0.16CRP > 3 (mg/l)CCS > 75th%

0.004PWV > 12 (m/s)CCS > 75th%

0.109IMT > 900 (μm)CCS > 75th%

kappa

With exception of moderate agreement between IMT and PWVseverity (kappa = 0.517) all other markers of severity presented onlya slight agreement (kappa < 0.1).


Conclusions• To our knowledge, this is the first study evaluating

simultaneously subclinical coronary and carotid atherosclerosis,

aortic stiffness and inflammatory biomarkers in FH subjects.

• Notwithstanding that CAC, PWV, and IMT values were higher in

FH subjects than in NL, these markers poorly correlated among

each other in univariate analysis and this correlation disappeared

after adjustment for confounders.

• Furthermore inflammatory markers did not correlate with IMT,

CAC or PWV.



Conclusions (cont)

• With exception of moderate agreement between severity of IMT

and PWV all other markers of severity presented only a slight

agreement.

• The poor or absent correlation among imaging markers and

the low agreement degree of their severity might have

prognostic implications


no correlation and low agreement of imaging and inflammatory atherosclerosis’ markers in familial...

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