Comparison of Apolipoprotein (ApoB/ApoA-1) and Lipoprotein (Total Cholesterol/HDL) Ratios in Obese Adolescents

Abstract

Background:

Serum (ApoB/ApoA-1) ratio is considered a stronger predictor of systemic inflammation and atherosclerosis than serum total cholesterol/HDL (TC/HDL) ratio among adults. We evaluated the relationships between ApoB/ApoA-1 and TC/HDL ratios with surrogate markers of inflammation and insulin resistance (IR) among obese adolescents.

Methods:

Body mass index z-score (BMI-z), body composition, fasting glucose, insulin, lipids, high-sensitive c-reactive protein (hs-CRP), hemoglobin A_1c (HbA_1c), and homeostatic model assessment for insulin resistance (HOMA-IR) were evaluated in 143 obese adolescents.

Results:

Male subjects had higher BMI-SDS, fat-free mass (FFM), and glucose than female subjects (P < 0.01). Furthermore, 54.5% met diagnostic criteria for metabolic syndrome (MS) and displayed higher SBP, BMI-SDS, fat mass (FM), HOMA-IR, hs-CRP, TG, TC/HDL, TG/HDL, ApoB/ApoA-1, and HbA_1c, but lower HDL and ApoA-1 than the non-MS group (P < 0.05) with similar gender distribution. In the entire cohort, TC/HDL and ApoB/ApoA-1 ratios were strongly correlated (r = 0.81, P < 0.0001). Receiver operating characteristic analysis indicated that the area under the curve in MS subjects for ApoB/ApoA-1 and TC/HDL-C ratios was not statistically different. ApoB/ApoA-1 and TC/HDL-C ratios were positively correlated with SBP (r = 0.29; P = 0.0004) and (r = 0.43; P < 0.0001), respectively. Finally, ApoB/ApoA-1 and TC/HDL-C ratios were correlated with hs-CRP (r = 0.21; P = 0.014) and (r = 0.26; P = 0.0016), respectively. However, the relationships between ApoB/ApoA-1 and TC/HDL ratios with HOMA-IR were not statistically significant.

Conclusions:

Unlike in the adult population, serum ApoA-1, ApoB, and ApoB/ApoA-1 ratio may not have significant advantage over conventional lipoproteins in evaluating the presence of systemic inflammation, MS, and risk of atherosclerosis in obese adolescents.

Introduction

Metabolic syndrome (MS) is strongly associated with cardiovascular risk factors such as visceral obesity, insulin resistance, hypertension, hypertriglyceridemia, a low level of high-density lipoprotein cholesterol (HDL-C), and impaired glucose tolerance in adolescents and adults.^1,2 An insulin resistance state is also associated with low-grade inflammatory response due to abnormal production of cytokines and the activations of prothrombotic and proinflammatory signaling pathways, which result in an increased risk of T2DM, myocardial infarction, and stroke in adults.^3

–6

Dyslipidemia is an independent major risk factor for progression of cardiovascular disease (CVD)⁷ and serum levels of low-density lipoprotein cholesterol (LDL-C) HDL-C and total cholesterol to HDL-C (TC/HDL-C) ratio have been utilized for determination of risk of CVD in adults.^8,9 Indeed, Castelli suggested that the total cholesterol to HDL-C ratio or Castelli index (CI) was a strong predictor of coronary risk based on preliminary analysis of the Framingham study.⁸ Furthermore, elevated TC/HDL-C ratio has been associated with a proinflammatory state in adults and adolescents.^10,11

On the contrary, it has been suggested that apolipoproteins (Apo), ApoB and ApoB/ApoA-1 ratio, may be better markers of CVD than conventional LDL-C, HDL-C, and TC/HDL-C ratio.^12
–14 Indeed, Juonala et al. suggested that serum levels of ApoB and ApoA-1 measured in children and adolescents reflect a lipoprotein profile predisposing to the development of subclinical atherosclerosis in adulthood.¹⁵ In addition, several studies have reported a strong association of systemic inflammation with the serum ApoA-1 and ApoB/ApoA-1 ratio as in adults and children.^16
–18 However, the apolipoproteins superiority to conventional lipoproteins in assessing CVD risk factor and inflammatory state has not been confirmed in other studies.^19
–21 To date, there has been no comparison of standard lipoprotein levels with apolipoproteins in relationship with low-grade inflammation in adolescents with and without MS. Therefore, we compared the relationship between TC/HDL-C ratio and ApoB/ApoA-1 ratios and some of the components of MS and high-sensitivity c-reactive protein, a biomarker of low-grade inflammation in a group of obese adolescents with and without MS.

Subjects and Methods

Subjects and design

One hundred forty-three adolescents (age: 12.1–17.4 years) who met the criteria for obesity [body mass index (BMI) >95th percentile for age]²² were included in the study. Participants were evaluated at the Children's Hospital of Wisconsin (CHW) Endocrine Clinic for evaluation of MS between May 2008 and April 2011. Race/ethnicity was self-assigned: Caucasian (C, n = 61; 42.7%), Mexican American [Hispanic (H), n = 44; 30.8%], and African American (AA, n = 38; 26.6%). Children were excluded if they had hepatic or renal disease, metabolic rickets, malabsorptive disorders (Crohn's disease, cystic fibrosis, and celiac disease) or cancer, or were taking multivitamin supplements, anticonvulsants, or systemic glucocorticoids. The CHW Institutional Review Board (IRB) approved the retrospective review of patients' clinical charts; therefore, informed consent was not required.

As a part of routine care, participants and/or their guardians completed a questionnaire detailing their medical history and medications. Two well-trained clinicians determined pubertal maturation (Tanner stage). Data were collected on patients, including age, gender, and self-declared ethnicity, height, weight, blood pressure, and body composition analysis by bioelectrical impedance (TANITA-TBF-410; TANITA Corporation of America, Inc., Arlington Heights, IL) for evaluation of fat mass (FM), fat-free mass (FFM), and total body water (TBW).^23,24 Fasting serum samples were obtained for glucose, insulin, hemoglobin A_1c (HbA_1c), lipid profiles, and high-sensitivity c-reactive protein (hs-CRP).

Laboratory studies and calculations

All blood samples were obtained between 0800 and 1100 h after an overnight fast. Serum glucose was measured by an autoanalyzer (Orthodiagnostics Fusion 5.1; Ortho-Diagnostics, Rochester, NY). The hs-CRP assays were carried out at Quest Diagnostics (San Jose, CA) using a polystyrene particle-enhanced immunonephelometric method (Dade Behring BNII). The detection limit of this assay was 0.20 mg/L, with measuring range of 0.18–1150 mg/L, and with intra-assay and interassay coefficients of variance of 2.65% and 3.6%, respectively. The hs-CRP values >10 mg/L were excluded to avoid influence of acute infection.²⁵ HbA1c was determined by the Bayer DCA (Bayer Diagnostics, Inc., Tarrytown, NY) 2000 instrument (nondiabetic range of 4.5%–5.7%).

Fasting serum insulin was measured by Nichols radio-immunoassay (RIA) (Nichols Institute, San Clemente, CA) with intra-assay and interassay coefficients of variation (CV) of 2.4%–6.3% and 5.2%–13.0%, respectively. The homeostatic model assessment estimates for insulin resistance (HOMA-IR) [(blood glucose mM × insulin μU/mL)/22.5) was calculated.²⁶

Total cholesterol (TC), HDL-C, and triglycerides (TG) were determined by colorimetric methods (Beckman spectrophotometer, Fullerton, CA). LDL-C was calculated using Friedewald's equation.²⁷ The levels of apolipoproteins were measured by kinetic immunonephelometry. The coefficients of variation for interassay and intra-assay corresponding to the methods used to measure were the followings: TC (1.06% and 0.68%), HDL-C (3.51% and 0.96%), ApoB (4.3% and 2.93%), and ApoA-1 (4.5% and 2.5%).

Blood pressure (BP) measurements were taken twice with the patient in sitting position. Elevated systolic or diastolic pressure (SBP and DBP, respectively) was defined as a value above the 95th percentile for age and gender.²⁸

Modified National Cholesterol Education Program (NCEP) criteria² for diagnosis of MS were defined as the presence of three or more of the following: age-adjusted BMI >95th percentile, systolic or diastolic BP >90th percentile, TG >90th percentile, HDL cholesterol <5th percentile, and impaired fasting glucose >5.6 mM.

Statistical analyses

Statistical analyses were carried out using SPSS (version 24.0). Data are expressed as mean ± SD. Body mass index (BMI) values were converted into standard deviation scores (SDS), which were normalized for age and gender based on 2000 Center for Disease Control (CDC) growth charts. The natural logarithmic transformation of the variables was used in the correlation and regression analyses when they were found to be skewed. Differences between those with MS and non-MS groups were estimated using unpaired Student's t-tests. Chi-square analyses were used to compare prevalence of MS. Spearman's correlations were performed to examine the associations between ApoB/ApoA-1 and TC/HDL-C ratios as well as among SBP, hs-CRP, and HOMA-IR. Fisher Z transformation was used when comparing correlations. P < 0.05 was considered significant.

Results

Findings stratified by gender

Table 1 summarizes the clinical and biochemical characteristics of the entire participant cohort stratified according to gender. There were no differences in FM, fasting insulin, HbA_1c, hs-CRP, HOMA-IR, TG, TG:HDL-C, cholesterol, LDL-C, HDL-C, TC: HDL-C, ApoA-1, ApoB, and ApoB:ApoA-1 ratio between male and female subjects. However, male subjects had higher, BMI-SD, FFM, FFM:FM, TBW, and fasting glucose than female subjects (P < 0.01).

Table 1.

Clinical and Biochemical Characteristics of Participants Based on Gender

Parameters	All	Male	Female	P
N (%)	143	60 (41.9)	83 (58.1)	NA
Age (yrs)	14.9 ± 1.4	15.0 ± 1.4	14.8 ± 1.3	NS
Tanner Stage	4.3 ± 0.7	4.0 ± 0.7	4.5 ± 0.6	NS
Race/Ethnicity
Caucasians (%)	61 (42.7)	22 (36.7)	39 (47.0)	NS
Hispanics (%)	44 (30.7)	20 (33.3)	24 (28.9)	NS
African Americans (%)	38 (26.6)	18 (30.0)	20 (24.1)	NS
SBP (mmHg)	128.9 ± 10.2	128.6 ± 9.9	129.1 ± 10.6	NS
DBP (mmHg)	69.3 ± 8.8	68.1 ± 8.6	70.2 ± 8.6	NS
BMI SDS	2.4 ± 0.4	2.5 ± 0.3	2.3 ± 0.3	0.0001
Fat (%)	44.9 ± 7.6	43.6 ± 9.3	45.8 ± 5.8	NS
Fat Mass (kg)	49.1 ± 18.9	50.8 ± 21.7	48.1 ± 16.7	NS
Fat-free Mass (kg)	58.1 ± 12.8	62.6 ± 15.3	54.9 ± 9.4	0.0003
FFM:FM Ratio	1.3 ± 0.4	1.4 ± 0.5	1.2 ± 0.3	0.0034
TBW (kg)	42.4 ± 9.3	45.7 ± 11.2	40.1 ± 6.9	0.0003
Glucose (mM)	5.0 ± 0.5	5.1 ± 0.4	4.9 ± 0.5	0.0115
HbA_1c (%)	5.3 ± 0.5	5.4 ± 0.5	5.3 ± 0.4	NS
Insulin (pM)	219.9 ± 107.9	207.4 ± 98.4	229.1 ± 114.1	NS
HOMA-IR (mol μU/mL)	7.0 ± 3.5	6.8 ± 3.3	7.1 ± 3.6	NS
hs-CRP (mg/L)	3.6 ± 1.5	3.7 ± 1.6	3.5 ± 1.5	NS
Triglycerides (mM)	1.9 ± 1.0	1.9 ± 1.1	1.8 ± 0.9	NS
Cholesterol (mM)	4.7 ± 0.9	4.7 ± 1.0	4.6 ± 0.9	NS
HDL-C (mM)	1.1 ± 0.3	1.0 ± 0.2	1.0 ± 0.2	NS
LDL-C (mM)	2.8 ± 0.8	2.8 ± 0.8	2.8 ± 0.9	NS
Cholesterol:HDL-C Ratio	4.7 ± 1.5	4.8 ± 1.7	4.7 ± 1.4	NS
Triglycerides:HDL-C Ratio	4.6 ± 3.1	4.7 ± 3.7	4.5 ± 2.6	NS
Apolipoprotein A-1 (APOA-1) (g/L)	120.3 ± 24.3	117.8 ± 21	122.1 ± 26.5	NS
Apolipoprotein B APOB) (g/L)	96.1 ± 28.9	96.2 ± 33.9	96.1 ± 24.7	NS
APOB:APOA-1 Ratio	0.83 ± 0.33	0.85 ± 0.40	0.82 ± 0.25	NS
Prevalence of MS (%)	76 (53.1)	29 (48.3)	47 (56.6)	NS

FM, fat mass; FFM, fat-free mass; TBW, total body water; HOMA-IR, homeostatic model assessment estimates for insulin resistance; MS, metabolic syndrome; NA, not applicable; NS, not significant.

The AA subgroup displayed significantly higher BMI-SDS, FM, and HbA1c than H and C subgroups (data not shown, P < 0.01). There were no ethnic differences in fasting insulin concentrations, HOMA-IR values, hs-CRP levels, and lipoprotein profiles in our cohort (data not shown).

Findings stratified by presence and absence of MS

In our cohort, 54.5% of adolescents met diagnostic criteria for MS displaying higher SBP, BMI SDS, FM, glucose, HbA1c, insulin, HOMA-IR, hs-CRP, triglycerides, triglycerides:HDL-C ratio, cholesterol:HDL-C ratio, and ApoB/ApoA-1 ratio than non-MS group (Table 2). There were no differences in total cholesterol and ApoB levels in MS compared with non-MS group. However, subjects in MS group had lower serum HDL-C and ApoA-1 levels than non-MS group.

Table 2.

Clinical and Biochemical Characteristics of Participants With and Without Metabolic Syndrome

Parameters	All	MS	Non-MS	P
N (%)	143	78 (54.5)	65 (45.5)	NA
Age (yrs)	14.9 ± 1.4	14.9 ± 1.5	14.8 ± 1.3	NS
Gender (% Female)	143 (58.0)	47 (61.8)	36 (53.7)	NS
Tanner stage	4.3 ± 0.7	4.4 ± 0.7	4.2 ± 0.7	NS
Race/Ethnicity
Caucasians (%)	61 (42.7)	32 (52.5)	29 (47.5)	NS
Hispanics (%)	44 (30.7)	26 (59.1)	18 (40.9)	NS
African Americans (%)	38 (26.6)	20 (52.6)	18 (47.4)	NS
SBP (mmHg)	128.9 ± 10.2	134.8 ± 8.5	121.8 ± 7.1	<0.0001
DBP (mmHg)	69.3 ± 8.8	70.5 ± 7.6	67.8 ± 8.8	NS
BMI SDS	2.4 ± 0.4	2.5 ± 0.4	2.3 ± 0.3	0.0011
Fat (%)	44.9 ± 7.6	45.5 ± 7.4	44.3 ± 7.7	NS
Fat mass (kg)	49.2 ± 18.9	52.2 ± 19.7	45.8 ± 17.5	0.043
Fat-free mass (kg)	58.1 ± 12.8	60.3 ± 14.3	55.5 ± 10.2	0.0249
FFM:FM ratio	1.30 ± 0.4	1.27 ± 0.42	1.33 ± 0.45	NS
TBW (kg)	42.4 ± 9.3	44.0 ± 10.4	40.5 ± 7.5	NS
Glucose (mM)	5.0 ± 0.5	5.0 ± 0.5	4.9 ± 0.4	0.025
HbA_1c (%)	5.3 ± 0.5	5.4 ± 0.5	5.2 ± 0.4	0.010
Insulin (pM)	219.9 ± 107.9	235.6 ± 88.8	201.1 ± 125.2	<0.05
HOMA-IR (mol μU/mL)	7.0 ± 3.5	7.5 ± 2.8	6.3 ± 4.0	0.037
hs-CRP (mg/L)	3.6 ± 1.5	4.2 ± 1.3	2.9 ± 1.4	<0.0001
SUA (mg/dL)	6.0 ± 1.3	6.3 ± 1.3	5.7 ± 1.3	0.0068
Triglycerides (mM)	1.9 ± 1.0	2.3 ± 1.1	1.4 ± 0.6	<0.0001
Cholesterol (mM)	4.7 ± 0.9	4.7 ± 0.9	4.5 ± 0.9	NS
HDL-C (mM)	1.1 ± 0.3	0.9 ± 0.2	1.2 ± 0.3	<0.0001
LDL-C (mM)	2.8 ± 0.8	2.8 ± 0.8	2.7 ± 0.9	NS
Cholesterol:HDL-C ratio	4.7 ± 1.5	5.5 ± 1.6	3.9 ± 0.9	<0.0001
Triglycerides:HDL-C ratio	4.6 ± 3.1	6.1 ± 3.4	2.7 ± 1.2	<0.0001
Apolipoprotein A-1 (ApoA-1) (g/L)	120.3 ± 24.3	106.1 ± 17.1	136.1 ± 23.6	<0.0001
Apolipoprotein B (ApoB) (g/L)	96.1 ± 28.9	99.5 ± 32.3	92.7 ± 23.7	NS
ApoB:ApoA-1 ratio	0.8 ± 0.3	0.93 ± 0.43	0.7 ± 0.2	<0.0001

NA, not applicable; NS, not significant.

Findings in the entire cohort

Using receiver-operating characteristic analysis indicated that the area under the curve in MS subjects for ApoB/ApoA-1 and TC/HDL-C ratios were not statistically different (0.76 ± 0.47 vs. 0.85 ± 0.36; P = 0.18). Total cholesterol/HDL-C and ApoB/ApoA-1 ratios were strongly correlated (r = 0.81, P < 0.0001) (Table 3). In addition, LDL-C/HDL-C and ApoB/ApoA-1 ratios were also highly correlated (r = 0.79; P < 0.0001) (data not shown). Although the relationships between ApoB/ApoA-1 and TC/HDL-C ratios with FM were not statistically significant, ApoB/ApoA-1 and TC/HDL-C ratios were positively correlated with SBP (r = 0.29; P = 0.0004) and (r = 0.43; P < 0.0001), respectively. Also, ApoB/ApoA-1 and TC/HDL-C ratios were correlated with hs-CRP (r = 0.21; P = 0.014) and (r = 0.26; P = 0.0016), respectively. Furthermore, there was a strong positive relationship between serum TG and hs-CRP levels (r = 0.0001). There were positive correlations between HOM-IR and FM (r = 0.48; P < 0.0001), TG (r = 0.26; P = 0.0014), HbA_1c (r = 0.30; P = 0.0002), and hs-CRP (r = 0.29; P = 0.0004), respectively. However, the relationships between ApoB/ApoA-1 and TC/HDL-C ratios with HOMA-IR were not statistically significant.

Table 3.

Bivariate Correlations of Clinical and Biochemical Characteristics for Whole Cohort of Participants

	FM (kg)	SBP (mmHg)	TC/HDL-C	ApoB/ApoA-1	HDL-C (mM)	TG (mM)	HbA_1c (%)	HOMA-IR (mol μU/mL)
FM (kg)	1.0
SBP (mmHg)	0.30^a	1.0
TC/HDL-C	−0.02	0.43^a	1.0
APOB/ApoA-1	−0.03	0.29^a	0.81^a	1.0
HDL-C (mM)	−0.12	−0.52^a	−0.66^a	−0.46^a	1.0
TG (mM)	−0.05	0.14	0.54^a	0.52^a	−0.33^a	1.0
HbA_1c (%)	0.23^a	0.04	0.01	−0.08	−0.10	0.08	1.0
HOMA-IR (mol μU/mL)	0.48^a	0.29^a	0.08	−0.10	−0.11	0.26^a	0.30^a	1.0
hs-CRP (mg/mL)	0.38^a	0.25^a	0.26^a	0.21^b	−0.29^a	0.32^a	0.23^a	0.29^a

P < 0.01.

P < 0.05.

Discussion

In the present study, TC/HDL-C and ApoB/ApoA-1 ratios were strongly correlated, and TC/HDL-C and ApoB/ApoA-1 ratios showed similar association with MS. Also, ApoB/ApoA-1 and TC/HDL-C ratios were positively correlated with SBP. Finally, ApoB/ApoA-1 and TC/HDL-C ratios displayed similar correlations with hs-CRP in the entire cohort. However, the relationships between ApoB/ApoA-1 and TC/HDL ratios with HOMA-IR were not significant.

While the alterations in cholesterol, triglycerides, LDL-C, and HDL-c metabolism have already been identified as risk factors for CVD, other lipoproteins have been implicated to establish more dependable biochemical factors which can predict CVD. Juonala et al. reported that ApoB/ApoA-1 ratio, measured in a cohort of nonobese and obese adolescents, was a stronger predictor of adulthood carotid intima media (CIMT) and brachial flow-mediated dilation (FMD), as markers of subclinical atherosclerosis, than LDL-C/HDL-C ratios.¹⁵ However, ApoB/ApoA-1 and LDL-C/HDL-C ratios in adolescents were similarly correlated with adulthood SBP. Also, it has been suggested that there are advantages in measuring ApoB and ApoA-1 levels, since their concentrations influence the number of particles of their corresponding lipoprotein classes with resultant opposite risk level.²⁹ Therefore, a high ApoB/ApoA-1 ratio corresponds to the number of atherogenic lipoprotein particles, which are expected to be deposited in the arterial wall. However, Raitakari et al. have previously reported that conventional risk factors such as LDL-C, SBP, and obesity during adolescence are associated with increased adulthood CIMT.³⁰ While we did not assess any vascular markers of atherosclerosis, both ApoB/ApoA-1 and TC/HDL-C ratios were correlated with SBP in our obese adolescent cohort. Indeed, TC/HDL-C ratio appeared to have a stronger correlation with SBP than ApoB/ApoA-1 ratio.

In addition, ApoB/ApoA-1 ratio has been reported to be strongly associated with the presence of MS and insulin resistance in obese adults and children.^16,31 In our cohort, ApoB/ApoA-1 and TC/HDL-C ratios were significantly higher in obese adolescents with MS than those without MS. Indeed, there was no difference between ApoB/ApoA-1 and TC/HDL-C ratios and its relationship to MS. On the contrary, we did not observe any correlation between ApoB/ApoA-1 and TC/HL-C ratios and index of insulin resistance (HOMA-IR).

Some studies have reported a strong association of systemic inflammation with the serum ApoA-1 and ApoB/ApoA-1 ratio in adults and children.^16
–18 However, the advantage of ApoB/ApoA-1 ratio versus TC/HDL-C ratio in evaluating CVD risk factor and inflammatory state has not been confirmed in other studies.^19
–21 Recently, Agirbasli et al. reported that TC/HDL-C ratio correlates with hsCRP levels in a group of children and adolescents.¹¹ Furthermore, we observed that ApoB/ApoA-1 and TC/HDL-c had similar correlation with hs-CRP, a biomarker of low-grade inflammation.

In this cohort, male subjects had higher BMI SDS and higher fasting glucose levels than female subjects especially among AA and H subgroups. However, higher BMI SDS in AA and H male subjects was not associated with higher rate of dyslipidemia. It is likely that higher BMI SDS among males was due to their higher FFM and FFM:FM ratio than female subjects.³² Therefore, male subjects were less likely to have dyslipidemia due to lower relative body fat. While male subjects had higher fasting glucose levels than female subjects overall, their HbA1c levels were not significantly different from HbA1c levels among females. Finally, we observed a tendency for higher prevalence of the MS among females despite having a lower BMI SDS than males. Since 58.1% of our cohort were females with lower FFM:FM ratios compared with males, it is likely that this lower FFM:FM ratios is what may have influenced the development of insulin resistance in the females.³³

Limitations to this study include the retrospective design of the study and lack of oral glucose tolerance data to assess glucose homeostasis and β-cell function in relationship to the ApoB/ApoA-1 and TC/HDL-C ratios, particularly since HbA_1c values were higher in AA group compared with C and H groups. The possible presence of impaired glucose tolerance among some of the participant cohort may have influenced our results.³⁴ Another limitation to the study is that there were no age- and sex-matched normal weight controls for each racial/ethnic group. Also, the accuracy of bioelectrical impedance (BIA) for assessment of body composition has been questioned because of larger errors in individual estimates of body fat compared with DXA method.²⁴ However, BIA has been deemed accurate for assessing body composition in large groups of normal weight or obese pediatric subjects compared with DXA.³⁵

In conclusion, ApoB and ApoB/ApoA-1 ratio does not have significant advantage over conventional lipoprotein ratios in evaluating the presence of systemic inflammation, MS, and risk of atherosclerosis in obese adolescents. Since apolipoprotein and lipoprotein ratios share similar dietary and lifestyle factors and are highly correlated, either of these ratios may be an adequate index of dyslipidemia. Further studies are needed, however, to evaluate importance of ApoB/ApoA-1 ratio in predicting atherosclerosis in adolescents with MS.

Footnotes

Acknowledgment

This study was funded by the Diabetes Research Fund, Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI

Authors' Contributions

Ramin Alemzadeh collected and analyzed the data as well as wrote and edited the article; Jessica Kichler analyzed the data as well as wrote and edited the article.

Author Disclosure Statement

No competing financial interests exist.

References

Grundy

, Cleeman

, Daniels

, et al. Diagnosis and management of the metabolic syndrome: An American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation, 2005; 112:2735–2752.

Weiss

, Dziura

, Burgert

, et al. Obesity in the metabolic syndrome in children and adolescents. N Eng J Med, 2004; 350:2362–2374.

Freeman

, Norrie

, Caslake

, et al. C-reactive protein is an independent predictor of risk for development of diabetes in the West of Scotland coronary prevention study. Diabetes, 2002; 51:1596–1600.

Ridker

, Hennekens

, Buring

, et al. C-reactive protein and other markers of inflammation in the prediction of cardiovascular disease in women. N Eng J Med, 2000; 342:836–843.

Danesh

, Wheeler

, Hirschfield

, et al. C-reactive protein and other circulating markers of inflammation in the prediction of coronary heart disease. N Eng J Med, 2004; 350:1387–1397.

Ridker

, Stampfer

, Rifai

. Novel risk factors for systemic atherosclerosis: A comparison of c-reactive protein, fibrinogen, homocysteine, lipoprotein(a), and standard cholesterol screening as predictors of peripheral artery disease. JAMA, 2001; 285:2481–2485.

NCEP (2002). Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation, 2002; 106:3143–3421.

Castelli

. Epidemiology of coronary heart disease: The Framingham study. Am J Med, 1984; 76:4–12.

Abbott

, Wilson

, Kannel

, et al. High density lipoprotein cholesterol, total cholesterol screening, and myocardial infarction. The Framingham Study. Arteriosclerosis, 1988; 8:207–211.

10.

Jialal

, Devaraj

. Inflammation and atherosclerosis: The value of the high-sensitivity C-reactive protein assay as a risk marker. Am J Clin Pathol, 2001; 116 Suppl:S108–S5115.

11.

Agirbasli

, Tanrikulu

, Acar Sevim

, et al. Total cholesterol-to-high-density lipoprotein cholesterol ratio predicts high-sensitivity C-reactive protein levels in Turkish children. J Clin Lipidol, 2015; 9:195–200.

12.

Walldius

, Jungner

. Apolipoprotein A-I versus HDL cholesterol in the prediction of risk for myocardial infarction and stroke. Curr Opin Cardiol, 2007; 22:359–367.

13.

O'Donnell

, Xavier

, Liu

, et al. Risk factors for ischaemic and intracerebral haemorrhagic stroke in 22 countries (the INTERSTROKE study): A case-control study. Lancet, 2010; 376:112–123.

14.

Kastelein

, van der Steeg

, Holme

, et al. Lipids, apolipoproteins, and their ratios in relation to cardiovascular events with statin treatment. Circulation, 2008; 117:3002–3009.

15.

Juonala

, Viikari

, Kähönen

, et al. Childhood levels of serum apolipoproteins B and A-I predict carotid intima-media thickness and brachial endothelial function in adulthood: The cardiovascular risk in young Finns study. J Am Coll Cardiol, 2008:52:293–299.

16.

Sierra-Johnson

, Somers

, Kuniyoshi

, et al. Comparison of apolipoprotein-B/apolipoprotein-AI in subjects with versus without the metabolic syndrome. Am J Cardiol, 2006; 98:1369–1373.

17.

Tani

, Nagao

, Hirayama

. Association of systemic inflammation with the serum apolipoprotein A-1 level: A cross-sectional pilot study. J Cardiol, 2016; 68:168–177.

18.

Karabouta

, Papandreou

, Makedou

, et al. Associations of Apolipoprotein A, high-sensitivity c-reactive protein and fasting plasma insulin in obese children with and without family history of cardiovascular disease. J Clin Med Res, 2016; 8:431–436.

19.

Mora

, Otvos

, Rifai

, et al. Lipoprotein particle profiles by nuclear magnetic resonance compared with standard lipids and apolipoproteins in predicting incident cardiovascular disease in women. Circulation, 2009; 119:931–939.

20.

Arsenault

, Després

, Stroes

, et al. Lipid assessment, metabolic syndrome and coronary heart disease risk. Eur J Clin Invest, 2010; 40:1081–1093.

21.

Kappelle

, Gansevoort

, Hillege

, et al. Apolipoprotein B/A-I and total cholesterol/high-density lipoprotein cholesterol ratios both predict cardiovascular events in the general population independently of nonlipid risk factors, albuminuria and C-reactive protein. J Intern Med, 2011; 269:232–242.

22.

Cole

, Bellizzi

, Flegal

, et al. Establishing a standard definition for child overweight and obesity worldwide: International survey. BMJ, 2000; 320:1240–1243.

23.

Lommez

, Borys

, Ducimetiere

, et al. Reliability of bioimpedance analysis compared with other adiposity measurements in children: The FLVS II Study. Diabet Metab, 2005; 31:534–541.

24.

Lazzer

, Boirie

, Meyer

, et al. Which alternative method to dual-energy X-ray absorptiometry for assessing body composition in overweight and obese adolescents?. Arch Pediatr, 2005; 12:1094–1101.

25.

Brasil

, Norton

, Rossetti

, et al. C-reactive protein as an indicator of low intensity inflammation in children and adolescents with and without obesity. J Pediatr (Rio J), 2007; 83:477–480.

26.

Matthews

, Hosker

, Rudenski

, et al. Homeostasis model assessment: Insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia, 1985; 28:412–419.

27.

Friedewald

, Levy

, Fredrickson

. Estimation of the concentration of low density lipoprotein cholesterol without use of preparative ultracentrifuge. Clin Chem, 1972; 18:499–502.

28.

National High Blood Pressure Education Program Working Group on High Blood Pressure in Children and Adolescents. The Fourth Report on the Diagnosis, Evaluation, and Treatment of High Blood Pressure in Children and Adolescents. Pediatrics, 2004; 114:555–576.

29.

Walldius

, Jungner

. The ApoB/apoA-1 ratio: A strong, new risk factor for cardiovascular disease and a target for lipid lowering therapy-a review of the evidence. J Intern Med, 2006; 259:493–519.

30.

Raitakari

, Juonala

, Kähönen

, et al. Cardiovascular risk factors in childhood and carotid artery intima media thickness in adulthood-The Cardiovascular Risk in Young Finns Study. JAMA, 2003; 290:2277–2283.

31.

Savas Erdeve

, Simsek

, Dallar

, et al. Utility of ApoB/ApoA1 ratio in the prediction of cardiovascular risk in children with metabolic syndrome. Indian J Pediatr, 2010; 77:1261–1265.

32.

Lamb

, Ogden

, Carroll

, et al. Association of body fat percentage with lipid concentrations in children and adolescents: United States, 1999–2004. Am J Clin Nutr, 2011; 94:877–883.

33.

Burrows

, Correa-Burrows

, Reyes

, et al. Low muscle mass is associated with cardiometabolic risk regardless of nutritional status in adolescents: A cross-sectional study in a Chilean birth cohort. Pediatr Diabetes, 2017. Epub ahead of print]; DOI: 10.1111/pedi.12505.

34.

Arslanian

, Lewy

, Danadian

, et al. Glucose intolerance in obese adolescents with polycystic ovary syndrome: Roles of insulin resistance and beta-cell dysfunction and risk of cardiovascular disease. J Clin Endocrinol Metab, 2001; 86:66–71.

35.

Haroun

, Crocker

, Viner

, et al. Validation of BIA in obese children and adolescents and re-evaluation in a longitudinal study. Obesity, 2009; 12:2245–2250.