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Original Article
Associations Between Estimated Desaturase Activity and Insulin Resistance in Korean Boys
Young Sim Choia, Han Byul Janga, Ju Yeon Parka, Hye-Ja Leea, Jae-Heon Kangb, Kyung-Hee Parkc, Jong Ho Leed, Sang Ick Parka, Jihyun Songa
Osong Public Health and Research Perspectives 2014;5(5):251-257.
DOI: https://doi.org/10.1016/j.phrp.2014.08.008
Published online: September 4, 2014

aDivision of Metabolic Disease, Center for Biomedical Science, Korea National Institute of Health, Cheongju, Korea

bDepartment of Family Medicine, Obesity Research Institute, Seoul Paik Hospital, Inje University, Seoul, Korea

cDepartment of Family Medicine, Hallym University Sacred Heart Hospital, Hallym University, Anyang, Korea

dDepartment of Food and Nutrition, College of Human Ecology, Yonsei University, Seoul, Korea

∗Corresponding author. jhsong10@korea.kr
eBoth authors contributed equally to this article.
• Received: July 21, 2014   • Revised: August 23, 2014   • Accepted: August 25, 2014

© 2014 Published by Elsevier B.V. on behalf of Korea Centers for Disease Control and Prevention.

This is an Open Access article distributed under the terms of the CC-BY-NC License (http://creativecommons.org/licenses/by-nc/3.0).

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  • Objectives
    Obesity in childhood increases the risk of obesity in adulthood, and is predictive of the development of metabolic disorders. The fatty acid compositions of various tissues, including blood, are associated with obesity and obesity-associated disorders. Thus, tracking plasma phospholipid (PL) features and metabolic parameters in young individuals may strengthen the utility of fatty acid composition as an early biomarker of future metabolic disorders.
  • Methods
    Anthropometric and blood biochemical data were obtained from 131 Korean males aged 10.5 ± 0.4 years, and followed up at 2 years. We analyzed the plasma PL fatty acids according to obesity. Obese children were defined as those with a body mass index (BMI) greater than the 85th percentile for age and gender, based on Korean child growth standards.
  • Results
    Activities of lipid desaturases, stearyl-CoAD (SCD-16,16:1n-7/16:0), delta-6D (D6D, 20:3n-6/18:2n-6), and delta-5D (D5D, 20:4n-6/20:3n-6), were estimated. Obese individuals had significantly higher proportions of palmitoleic acid (16:1n-7) and dihomo-gamma linolenic acid (DGLA, 20:3n-6) at both baseline and follow-up than did lean individuals. The activities of SCD-16 and D6D were higher in obese than lean boys. The baseline SCD-16 activity level was positively associated with the baseline waist circumference (WC) and the metabolic risk score. The baseline D6D level was positively associated with WC and also with the homeostasis model of assessment of insulin resistance (HOMA-IR), a surrogate marker of insulin resistance (IR), and metabolic risk score at both baseline and follow-up.
  • Conclusion
    In young Korean males, higher D6D activity predicts the future development of IR and associated metabolic disorders including dyslipidemia.
Obesity has become increasingly prevalent among children and adolescents in many countries. Childhood obesity increases the risk of developing health problems including insulin resistance (IR) and metabolic syndrome [1,2], and also adult obesity and cardiovascular disease [3,4]. Therefore, early detection of childhood obesity and metabolic disorders is required to efficiently prevent development of problems in adulthood. Studies on child populations may clarify the mechanisms underlying the development of obesity and metabolic disorders, because problems in children are not confounded by the consequences of advanced metabolic disorders.
The levels of specific serum fatty acids and fatty acid desaturases have been suggested to serve as useful biomarkers predicting the development of IR and metabolic disorders [5–11]. Higher levels of saturated fatty acids, palmitoleic acid, linoleic acid, and dihomo-gamma linolenic acid (DGLA), have been reported to be associated with obesity and metabolic syndrome. In addition, both animal and human studies have suggested that fatty acid desaturases play roles in various metabolic disturbances, including dyslipidemia and IR [12]. The data have been derived principally from cross-sectional studies, which cannot predict the future development of obesity and metabolic disorders. Longitudinal studies can yield integrated information on the development of metabolic disorders over time, and can identify the optimal points of intervention [13]. Therefore, in the present study, we explored the longitudinal relations of plasma phospholipid (PL) fatty acid composition and desaturase activities to IR and metabolic risk factors in Korean boys.
2.1 Study participants and anthropometric parameters
This study is part of the Korean Children and Adolescent Cohort Study, which follows a student cohort from the time of entry into elementary school (at 7 years of age) to graduation (at age 19 years) in Seoul and Kyunggi provinces, Korea. The overall objective of the cohort study is to identify early risk factors for obesity and associated metabolic disease. The study was approved by the Institutional Review Board of the Korea Center for Disease Control and Prevention and the Ethics Committee of Seoul-Paik Hospital, Inje University, Seoul, Korea. Informed parental consent was obtained for each individual prior to enrolment. Body weight and body fat percentage were measured using a body composition analyzer (BC418; Tanita, Tokyo, Japan) and height was measured using an automatic stadiometer (DS-102; Jenix, Seoul, Korea). Obese children were defined as those with a body mass index (BMI) greater than the 85th percentile for age and gender, based on Korean child growth standards [14]. A total of 131 boys aged 9–11 years in 2008–2009 were included. After 2 years, health data were obtained once more.
2.2 Biochemical analysis
Each blood sample was collected from an antecubital vein into a vacutainer tube between 9:00 am and 11:00 am after a 12-hour overnight fast. Within 30 minutes, plasma and serum were separated and stored at −80°C prior to further analysis. The levels of triglyceride (TG), total cholesterol, high-density lipoprotein-cholesterol (HDL-C), alanine aminotransferase (ALT), aspartate aminotransferase (AST), and glucose were measured using an autoanalyzer (model 7600II; Hitachi, Tokyo, Japan). The fasting serum insulin level was measured using a Roche E170 instrument (Roche Diagnostics, Mannheim, Germany). The IR index was calculated using the homeostasis model assessment of insulin resistance (HOMA-IR) [15]. A metabolic risk score was constructed by summing the z-score of five metabolic risk factors, which are BMI, systolic blood pressure (SBP), TG, HDL-C, and HOMA-IR [16].
2.3 Fatty acid analysis
Plasma lipids were extracted using a modification of the method of Folch et al [17]. The PL fraction was isolated by thin-layer chromatography and the fatty acids were converted into methyl esters using the method of Lepage and Roy [18]. The composition of the methylated fatty acid mix was determined by gas chromatography (HP 7890A; Hewlett-Packard, Palo Alto, CA, USA). Individual fatty acids were identified by comparing retention times to those of standards and quantified based on the peak area relative to the total methylated fatty acid peak area (set at 100%). Desaturase levels were estimated by calculating the product:precursor ratios of individual fatty acids (using the proportions calculated above) as follows: delta-6D (D6D) = [20:3n-6/18:2n-6]; delta-6D (D5D) = [20:4n-6/20:3n-6]; stearyl-CoAD-16 (SCD-16) = [16:1n-7/16:0]; and stearyl-CoAD-18 (SCD-18) = [18:1n-9/18:0] [18].
2.4 Statistical analysis
Statistical analyses were performed with the aid of SAS software (version 9.1; SAS Institute, Cary, NC, USA). All data are expressed as mean ± standard deviation (SD). The normality of data distribution was checked. Variables with skewed distributions were log-transformed prior to analysis. The significance of observed between-group differences was assessed using the unpaired Student t test and the significance of among-group differences was analyzed using one-way analysis of variance (ANOVA). If a statistically significant effect was noted, Duncan's post-hoc test was applied to identify a between-group difference with a significance level of p < 0.05. Pearson correlation coefficients were calculated to measure the extent of correlation between pairs of variables.
3.1 Participant characteristics
Anthropometric and biological characteristics of all individuals at baseline are shown in Table 1. At commencement of the study, 75 of 131 boys were obese, and all had a significantly greater body weight, BMI, BMI z-score, and waist circumference than did the others. HOMA-IR values and levels of serum ALT, TG, and insulin were significantly higher and HDL-C was significantly lower in obese individuals (Table 1). Two years later, the children were examined once more. Of the 56 individuals who were not obese at baseline, categorized as “lean”, 40 boys had BMI values below the 60th percentile at follow-up. Of the 75 initially obese boys, 57 remained obese at follow-up. At this time, 14 boys who were not obese at baseline and 20 boys who were obese at that time had BMI values in the 60–85% percentile, and were categorized as “intermediate” in terms of obesity.
The baseline and follow-up data of lean and obese individuals were compared. Not surprisingly, the mean values of height, weight, BMI, and waist circumference of both groups increased significantly over the 2 years, as did blood glucose and insulin levels, and HOMA-IR values. The mean values of BMI z-score, AST, and ALT levels were lower in lean boys at follow-up than at baseline, but this was not true of obese individuals. The mean SBP, diastolic blood pressure (DBP), and lipid levels (total cholesterol, HDL-C, and TG) did not differ between baseline and follow-up in either group.
At follow-up, obese boys had a significantly greater BMI z-score, and waist circumference than lean or intermediate individuals. In addition, obese individuals had significantly higher concentrations of ALT, TG, and insulin and a higher mean HOMA-IR value than the other groups.
3.2 Plasma PL fatty acid composition and desaturase levels
Table 2 shows the relative proportions of 25 individual fatty acids of plasma PLs. At baseline, over 63% of total fatty acids were saturated (SFAs), and no significant difference in the level of total SFA, palmitate, or stearate was evident between obese and lean individuals. Monounsaturated fatty acids (MUFAs) constituted 11% of total fatty acids in either group. However, the palmitoleic acid (16:1n-7) level was higher in obese individuals. Although no difference in total n-6 polyunsaturated fatty acid (PUFA) or 20:4n-6 level was observed, the DGLA (20:3n-6) level was higher in obese individuals as were the SCD-16 and D6D indices.
Baseline and follow-up data on lean and obese individuals were separately compared. The levels of only four fatty acids (22:0, 20:1, 22:5n-3, and 20:4n-6) differed between baseline and follow-up. The mean 22:5n-3 level increased in both groups at follow-up and the mean 20:4 level fell in lean boys at follow-up. Obese individuals had a higher palmitoleic acid and DGLA level than lean boys at follow-up. Also, trends toward increases in the SCD-16 and D6D indices were evident in boys of heavier weight.
3.3 Correlation between fatty acid and desaturase levels and the risks of adiposity and IR
The baseline level of palmitoleic acid (as a percentage of all fatty acids) was closely associated with WC and metabolic risk score (r = 0.217, p < 0.05; r = 0.221, p < 0.05, respectively). DGLA level was also highly associated with WC, HDL-C, TG, and metabolic risk score (r = 0.205, p < 0.05; r = −0.176, p < 0.05; r = 0.371, p < 0.001; r = 0.260, p < 0.01, respectively). The SCD-16 level was closely associated with WC and metabolic risk score (r = 0.209, p < 0.05; r = 0.200, p < 0.05, respectively) but not with the HOMA-IR value (Table 3). The D6D level was highly associated with most of the metabolic risk factors such as WC, TG, and HDL-C. The D6D level was thus positively associated with the HOMA-IR value and the metabolic risk score (r = 0.267, p < 0.01; r = 0.394, p < 0.001). The baseline D6D level showed significant positive association with the follow-up WC, HOMA-IR, and metabolic risk score (r = 0.480, r = 0.364, and r = 0.436, respectively). The baseline D5D level exhibited a negative association with them (Table 3).
A stepwise multiple regression analysis with the baseline levels of age, BMI z-score, WC, TG, HDL-C, and four estimated desaturase indices was performed to investigate potential factors associated with the follow-up HOMA-IR. Significant associations with the follow-up HOMA-IR were found for baseline WC and D6D (Table 4). Similarly, strong associations with the follow-up metabolic risk score were found for baseline WC and D6D level. Based on the regression analysis, the baseline D6D level could be a major predictive marker for future metabolic risks.
We investigated the relationships between individual plasma PL fatty acids and desaturase activities and metabolic risk factors in Korean children. Furthermore, we explored the longitudinal relations of estimates of desaturase activity to body fatness, IR, and metabolic risk score. Obese boys had significantly higher proportions of palmitoleic acid and DGLA at baseline than did lean children, in agreement with data on Japanese children [9]. Increased DGLA levels are positively associated with the development of metabolic disorders in both adults and children [19–21]. A previous cross-sectional study found that obese children have higher proportions of DGLA in plasma lipids than do those of normal weight [21]. Our data are in agreement with these earlier reports. The present study, a longitudinal study, also shows that obese boys had persistently high proportions of DGLA and palmitoleic acid at follow-up. Assessment of plasma DGLA level and/or palmitoleic acid level would give useful information on obesity status in children. Additionally, the present study shows that the baseline plasma DGLA content was positively associated with both present and future adiposity index values and metabolic risk score in Korean children.
Plasma fatty acid composition could be regulated by many factors such as dietary, hormonal, and environmental factors [12,22]. To assess the effect of dietary fatty acids on the serum PL fatty acid composition of the study participant, a reliable database for fatty acid composition of Korean food is needed, but was not available at this time. Linoleic acid (18:2n-6) is directly converted into 18:3n-6 by D6D and rapidly elongated to 20:3n-6 (DGLA) [22]. DGLA is converted into arachidonic acid by D5D [22]. The DGLA level, regulated by D6D activity, is increased by insulin [12]. Hyperinsulinemia induced by obesity might change the expression level of D6D. We observed D6D had a positive association with HOMA-IR, a surrogate marker of IR for epidemiology study. The observed increases in DGLA concentration and D6D activity, accompanied by a fall in D5D expression, in obese individuals suggest that impaired fatty acid metabolism, possibly caused by the development of IR, may trigger the accumulation of DGLA. Although DGLA plays multiple roles in protecting against inflammation and cell proliferation [22], increases in DGLA and D6D levels in association with IR could nonetheless aggravate metabolic disorders. A recent cross-sectional study with Korean adults suggested D6D as a major factor for determining plasma level of C-reactive protein, a surrogate marker for inflammation [23].
Not only was the baseline D6D activity significantly higher in obese than in lean children at baseline, but it was also positively associated with adiposity indices at follow-up. Baseline D6D activity also exhibited positive associations with the follow-up values of surrogate markers of IR and metabolic disorders, including the TG level, HOMA-IR value, and metabolic risk score. Accumulating evidence suggests that D6D plays a crucial role in the development of obesity and metabolic syndrome. High levels of D6D activity have been estimated in adults with obesity, diabetes, and metabolic syndrome [18,24,25]. Warensjo et al [25] found that a higher estimated D6D activity increased the risk of metabolic syndrome over 20 years in middle-aged men. To the best of our knowledge, only one prior study [26] explored the associations between longitudinal changes in fatty acid composition and body fatness in children. In that study, increased D6D activity was significantly associated with an elevated waist-to-hip ratio in both boys and girls. The authors suggested that D6D activity was positively associated with an increased HOMA-IR value only in girls [26]. However, their small sample size may have limited the observations that could be made. In the present study, the D6D levels did not vary greatly over the 2 years, whereas the HOMA-IR level increased. Thus, no positive association between changes in D6D and changes in the HOMA-IR value were noted. However, baseline D6D activity was positively associated with both baseline and follow-up HOMA-IR values, and also follow-up metabolic risk score. Results from the present multiple regression analysis suggested that WC and D6D were the major determinants of HOMA-IR and metabolic risk score, a suggested tool for an early-life determination of metabolic risk. Thus early detection of elevated D6D activity in Korean boys may predict the future development of IR and associated metabolic disorders including dyslipidemia. Adequate regulation of D6D level at an early age may help prevent the development of metabolic disorders.
All authors declare no conflicts of interest.
Acknowledgements
We thank all the participating schools, children, and parents, as well as current and past investigators and staff. This work was supported by intramural grants from the Korea National Institute of Health, Korea Center for Disease Control (4845-302-210-13, 2012-NG64001-00).

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Table 1
Anthropometric and biochemical characteristics of the study participants.a
Baseline
Follow-up
Lean (n = 56) Obese (n = 75) p0a Lean (n = 40) Intermediate (n = 34) Obese (n = 57) p1a
Age (y) 10.5 ± 0.6*** 10.4 ± 0.6††† 0.161 12.5 ± 0.7 12.2 ± 0.6 12.3 ± 0.7 0.274
Height (cm) 142.7 ± 5.3*** 144.6 ± 6.6††† 0.073 156.9 ± 7.3 156.5 ± 7.9 157.0 ± 8.1 0.923
Body weight (kg) 37.1 ± 3.5*** 50.0 ± 8.3††† <0.0001 46.5 ± 5.1 53.3 ± 6.8 65.1 ± 12.1 <0.0001
BMI (kg/m2) 18.2 ± 0.5*** 23.8 ± 2.3††† <0.0001 18.8 ± 0.8 21.7 ± 1.0 26.2 ± 3.0 <0.0001
BMI z-score −0.02 ± 0.14*** 1.49 ± 0.40††† <0.0001 −0.21 ± 0.26 0.68 ± 0.24 1.60 ± 0.46 <0.0001
Waist circumference (cm) 62.4 ± 3.7*** 77.6 ± 6.2††† <0.0001 66.4 ± 5.1 74.9 ± 5.8 85.5 ± 8.1 <0.0001
SBP (mmHg) 108.0 ± 8.6 111.5 ± 13.1 0.064 107.8 ± 10.5 109.7 ± 11.7 115.1 ± 10.4 0.001
DBP (mmHg) 71.1 ± 7.5 71.2 ± 8.8 0.930 68.2 ± 10.3 69.1 ± 9.0 70.9 ± 8.3 0.152
AST (U/L) 23.3 ± 2.8** 26.3 ± 9.1 0.008 21.7 ± 3.1 23.0 ± 4.0 28.3 ± 14.8 0.001
ALT (U/L)b 13.8 ± 3.9* 26.7 ± 23.2 <0.0001 12.1 ± 3.6 16.0 ± 8.6 34.5 ± 37.1 <0.0001
Total cholesterol (mg/dL) 167.1 ± 24.5 173.8 ± 27.9 0.159 161.0 ± 18.6 161.4 ± 33.4 173.3 ± 31.2 0.030
HDL-C (mg/dL) 60.1 ± 12.0 52.0 ± 10.8 <0.0001 61.0 ± 10.9 55.9 ± 12.3 49.4 ± 9.4 <0.0001
TG (mg/dL)ab 61.5 ± 34.1 104.5 ± 63.8 <0.0001 57.1 ± 28.0 89.8 ± 41.5 117.4 ± 60.5 <0.0001
Glucose (mg/dL) 86.3 ± 6.4** 85.8 ± 8.0†† 0.714 90.8 ± 8.0 90.8 ± 6.4 90.7 ± 9.1 0.951
Insulin (μIU/mL)ab 6.1 ± 4.2*** 12.0 ± 11.0††† <0.0001 8.8 ± 3.5 11.9 ± 8.2 21.6 ± 19.9 <0.0001
HOMA-IRab 1.3 ± 0.9*** 2.5 ± 2.4††† <0.0001 2.0 ± 0.8 2.72 ± 2.1 5.0 ± 4.9 <0.0001
Metabolic risk score −1.59 ± 1.25*** 1.19 ± 2.23††† <0.0001 −1.87 ± 1.37 −0.58 ± 1.57 1.64 ± 2.51 <0.0001
MetS (%) 17.3 2.9 22.8

All values are presented as mean ± standard deviation (SD).

* Baseline vs. follow-up in control; *p < 0.05; **p < 0.01; ***p < 0.001.

Baseline vs. follow-up in obese; p < 0.05; ††p < 0.01; †††p < 0.001.

ALT = alanine aminotransferase; AST = aspartate aminotransferase; BMI = body mass index; DBP = diastolic blood pressure; HDL-C = high-density lipoprotein-cholesterol; HOMA-IR = homeostasis model of assessment of insulin resistance; IU = international unit; SBP = systolic blood pressure; TG = triglyceride; U = unit.

aTested by unpaired Student t test (p0, *, †) or one-way analysis of variance (ANOVA; p1 = p value for linear trends).

bData are log transformed prior to analysis.

Table 2
Plasma PL fatty acid composition and estimated desaturase activity of the study participants.a,b
Baseline
Follow-up
Control (n = 56) Obese (n = 75) p0 Control (n = 33) Intermediate (n = 25) Obese (n = 46) p1
Total SFA 63.5 ± 5.8 63.4 ± 7.5†† 0.776 63.5 ± 9.7 60.6 ± 10.3 61.8 ± 9.2 0.515
c12:0 0.14 ± 0.08 0.13 ± 0.06 0.443 0.12 ± 0.06 0.14 ± 0.06 0.11 ± 0.05 0.666
c14:0 0.54 ± 0.14 0.51 ± 0.11 0.385 0.54 ± 0.22 0.52 ± 0.08 0.50 ± 0.14 0.435
c16:0 38.9 ± 3.7 38.1 ± 4.8 0.213 39.2 ± 6.4 36.9 ± 6.5 37.3 ± 6.2 0.217
c18:0 21.2 ± 2.3 21.7 ± 2.8 0.341 20.7 ± 3.3 20.2 ± 3.6 20.9 ± 2.9 0.620
c20:0 0.51 ± 0.16 0.53 ± 0.15 0.321 0.55 ± 0.10 0.52 ± 0.12 0.55 ± 0.11 0.941
c22:0 1.17 ± 0.49* 1.28 ± 0.45 0.163 1.26 ± 0.24 1.23 ± 0.23 1.33 ± 0.31 0.238
c24:0 1.05 ± 0.41 1.10 ± 0.38 0.371 1.12 ± 0.27 1.05 ± 0.24 1.07 ± 0.27 0.413
Total MUFA 11.0 ± 1.6 11.0 ± 1.6 0.889 11.3 ± 1.0 11.1 ± 1.2 11.1 ± 1.1 0.545
c16:1n-7 0.43 ± 0.18 0.51 ± 0.20 0.018 0.36 ± 0.15 0.44 ± 0.18 0.44 ± 0.15 0.027
c18:1n-9 6.89 ± 1.46 6.79 ± 1.55 0.589 6.23 ± 1.68 6.68 ± 2.06 6.62 ± 1.48 0.278
c18:1n-7 1.25 ± 0.23 1.16 ± 0.21 0.039 1.20 ± 0.28 1.12 ± 0.20 1.13 ± 0.26 0.283
c20:1n-9 0.32 ± 0.26* 0.32 ± 0.32 0.446 0.62 ± 0.62 0.50 ± 0.59 0.43 ± 0.45 0.197
c22:1n-9 0.71 ± 0.42 0.69 ± 0.49 0.306 1.31 ± 1.08 0.89 ± 0.99 0.92 ± 0.84 0.271
c24:1n-9 1.40 ± 0.57 1.50 ± 0.57 0.248 1.52 ± 0.46 1.47 ± 0.38 1.57 ± 0.43 0.522
Total n-6 FA 21.7 ± 4.3*** 21.8 ± 5.7††† 0.752 21.2 ± 8.0 24.1 ± 8.1 22.7 ± 7.5 0.428
c18:2n-6 14.2 ± 2.9 13.7 ± 3.2 0.285 14.0 ± 4.9 15.4 ± 4.8 14.4 ± 4.1 0.690
c18:3n-6 0.40 ± 0.13 0.39 ± 0.14 0.497 0.45 ± 0.18 0.37 ± 0.11 0.39 ± 0.11 0.153
c20:2n-6 0.29 ± 0.18 0.28 ± 0.12 0.993 0.29 ± 0.13 0.30 ± 0.14 0.29 ± 0.12 0.864
c20:3n-6 2.08 ± 0.48 2.38 ± 0.61 0.008 2.00 ± 0.53 2.28 ± 0.71 2.39 ± 0.55 0.007
c20:4n-6 4.44 ± 1.74* 4.74 ± 2.30 0.891 3.96 ± 3.11 5.22 ± 3.21 4.84 ± 3.24 0.255
c22:4n-6 0.18 ± 0.09 0.21 ± 0.09 0.108 0.24 ± 0.27 0.24 ± 0.11 0.21 ± 0.12 0.894



Total n-3 FA 3.72 ± 1.27 3.82 ± 1.19††† 0.632 3.72 ± 1.30 3.80 ± 1.15 3.80 ± 1.23 0.367
c18:3n-3 0.11 ± 0.07 0.13 ± 0.07 0.109 0.13 ± 0.09 0.14 ± 0.08 0.14 ± 0.11 0.955
c20:3n-3 1.15 ± 0.70 0.96 ± 0.63 0.319 1.26 ± 0.66 0.92 ± 0.64 1.17 ± 0.70 0.569
c20:5n-3 0.37 ± 0.33 0.42 ± 0.30 0.340 0.42 ± 0.45 0.53 ± 0.37 0.45 ± 0.35 0.663
c22:5n-3 0.58 ± 0.34* 0.59 ± 0.30††† 0.709 0.76 ± 0.37 0.72 ± 0.28 0.77 ± 0.29 0.532
c22:6n-3 1.51 ± 1.03 1.71 ± 1.14 0.453 1.54 ± 1.46 1.95 ± 1.42 1.89 ± 1.70 0.591
Desaturase activity
D6D 0.15 ± 0.04 0.18 ± 0.04 <0.0001 0.15 ± 0.04 0.16 ± 0.04 0.18 ± 0.05 0.029
D5D 2.15 ± 0.78 1.95 ± 0.80 0.075 1.85 ± 1.38 2.10 ± 1.13 1.94 ± 1.26 0.590
SCD-16 0.011 ± 0.005 0.013 ± 0.006 0.016 0.009 ± 0.004 0.012 ± 0.006 0.012 ± 0.004 0.031
SCD-18 0.334 ± 0.100 0.323 ± 0.099 0.462 0.319 ± 0.126 0.354 ± 0.154 0.328 ± 0.103 0.572

All values are presented as mean ± standard deviation (SD).

* Baseline vs. follow-up in control; *p < 0.05; **p < 0.01; ***p < 0.001.

Baseline vs. follow-up in obese; p < 0.05; ††p < 0.01; †††p < 0.001.

D5D = delta-5D; D6D = delta-6D; FA = fatty acid; MUFA = monounsaturated fatty acid; PL = phospholipid; SCD = stearyl-CoAD; SFA = saturated fatty acid.

aData are log transformed prior to analysis.

bTested by unpaired Student t test (p0, *, †) or one-way analysis of variance (ANOVA; p1 = p value for linear trends).

Table 3
Correlation coefficient between estimated desaturase activity and risks for metabolic syndrome.a
D6D D5D SCD-16 SCD-18
Baseline
BMI (kg/m2) 0.414*** −0.203* 0.193* −0.093
BMI z-score 0.410*** −0.209* 0.199* −0.097
Waist circumference (cm) 0.414*** −0.254** 0.209* −0.137
SBP (mmHg) 0.151 −0.137 0.153 0.068
DBP (mmHg) 0.181* −0.160 −0.031 −0.039
AST 0.279** −0.124 0.153 −0.013
ALT 0.370*** −0.164 0.155 −0.070
Total cholesterol (mg/dL) 0.214* −0.030 0.073 0.110
HDL-C (mg/dL) −0.292*** 0.082 −0.090 0.055
TG (mg/dL) 0.482*** −0.144 0.166 0.015
Glucose (mg/dL) −0.138 0.219* 0.119 0.126
Insulin (μIU/mL) 0.290** −0.195* 0.036 −0.072
HOMA-IR 0.267** −0.161 0.050 −0.054
Metabolic risk score 0.394*** −0.258** 0.200* −0.006
Follow-up
BMI (kg/m2) 0.445*** −0.279** 0.155 −0.100
BMI z-score 0.456*** −0.297*** 0.156 −0.103
Waist circumference (cm) 0.480*** −0.300*** 0.153 −0.087
SBP (mmHg) 0.340*** −0.305*** −0.017 −0.181*
DBP (mmHg) 0.203* −0.155 −0.092 −0.061
AST 0.131 −0.145 0.012 −0.092
ALT 0.306*** −0.258** 0.089 −0.116
Total cholesterol (mg/dL) 0.197* −0.092 0.091 0.123
HDL-C (mg/dL) −0.289*** 0.147 0.000 0.135
TG (mg/dL) 0.356*** −0.233** 0.090 −0.105
Glucose (mg/dL) 0.004 −0.219* −0.228** −0.208*
Insulin (μIU/mL) 0.377*** −0.261** 0.046 −0.066
HOMA-IR 0.364*** −0.278** 0.014 −0.089
Metabolic risk score 0.436*** −0.340*** 0.112 −0.107

*p < 0.05; **p < 0.01; ***p < 0.001.

ALT = alanine aminotransferase; AST = aspartate aminotransferase; BMI = body mass index; D5D = delta-5D; D6D = delta-6D; DBP = diastolic blood pressure; HDL-C = high-density lipoprotein-cholesterol; HOMA-IR = homeostasis model of assessment of insulin resistance; IU = international unit; SBP = systolic blood pressure; SCD = stearyl-CoAD; TG = triglyceride.

aTested by age-adjusted partial correlation analysis; data are log transformed prior to analysis.

Table 4
Stepwise multiple regression analysis for predicting follow-up HOMA-IR levels and metabolic risk score.a,b
Variable Adjusted
p r2
β Coefficient
Follow up HOMA-IRc
Waist circumference 0.026 < 0.0001 0.206
D6D 0.619 0.007 0.250
Follow up metabolic risk scored
Waist circumference 0.135 <0.0001 0.356
D6D 2.338 0.002 0.402

BMI = body mass index; HDL-C = high-density lipoprotein-cholesterol; HOMA-IR = homeostasis model of assessment of insulin resistance; TG = triglyceride.

aData are log transformed prior to analysis.

bFor multiple stepwise regression analysis, only the two independent variables incorporated into the model are listed, and the r2 values displayed are cumulative.

cIndependent variables include: baseline age, BMI z-score, waist circumference, TG, HDL-C, and desaturase.

dIndependent variables include: baseline age, waist circumference, and desaturase.

Figure & Data

References

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    Associations Between Estimated Desaturase Activity and Insulin Resistance in Korean Boys
    Associations Between Estimated Desaturase Activity and Insulin Resistance in Korean Boys
    Baseline
    Follow-up
    Lean (n = 56)Obese (n = 75)p0aLean (n = 40)Intermediate (n = 34)Obese (n = 57)p1a
    Age (y)10.5 ± 0.6***10.4 ± 0.6†††0.16112.5 ± 0.712.2 ± 0.612.3 ± 0.70.274
    Height (cm)142.7 ± 5.3***144.6 ± 6.6†††0.073156.9 ± 7.3156.5 ± 7.9157.0 ± 8.10.923
    Body weight (kg)37.1 ± 3.5***50.0 ± 8.3†††<0.000146.5 ± 5.153.3 ± 6.865.1 ± 12.1<0.0001
    BMI (kg/m2)18.2 ± 0.5***23.8 ± 2.3†††<0.000118.8 ± 0.821.7 ± 1.026.2 ± 3.0<0.0001
    BMI z-score−0.02 ± 0.14***1.49 ± 0.40†††<0.0001−0.21 ± 0.260.68 ± 0.241.60 ± 0.46<0.0001
    Waist circumference (cm)62.4 ± 3.7***77.6 ± 6.2†††<0.000166.4 ± 5.174.9 ± 5.885.5 ± 8.1<0.0001
    SBP (mmHg)108.0 ± 8.6111.5 ± 13.10.064107.8 ± 10.5109.7 ± 11.7115.1 ± 10.40.001
    DBP (mmHg)71.1 ± 7.571.2 ± 8.80.93068.2 ± 10.369.1 ± 9.070.9 ± 8.30.152
    AST (U/L)23.3 ± 2.8**26.3 ± 9.10.00821.7 ± 3.123.0 ± 4.028.3 ± 14.80.001
    ALT (U/L)b13.8 ± 3.9*26.7 ± 23.2<0.000112.1 ± 3.616.0 ± 8.634.5 ± 37.1<0.0001
    Total cholesterol (mg/dL)167.1 ± 24.5173.8 ± 27.90.159161.0 ± 18.6161.4 ± 33.4173.3 ± 31.20.030
    HDL-C (mg/dL)60.1 ± 12.052.0 ± 10.8<0.000161.0 ± 10.955.9 ± 12.349.4 ± 9.4<0.0001
    TG (mg/dL)ab61.5 ± 34.1104.5 ± 63.8<0.000157.1 ± 28.089.8 ± 41.5117.4 ± 60.5<0.0001
    Glucose (mg/dL)86.3 ± 6.4**85.8 ± 8.0††0.71490.8 ± 8.090.8 ± 6.490.7 ± 9.10.951
    Insulin (μIU/mL)ab6.1 ± 4.2***12.0 ± 11.0†††<0.00018.8 ± 3.511.9 ± 8.221.6 ± 19.9<0.0001
    HOMA-IRab1.3 ± 0.9***2.5 ± 2.4†††<0.00012.0 ± 0.82.72 ± 2.15.0 ± 4.9<0.0001
    Metabolic risk score−1.59 ± 1.25***1.19 ± 2.23†††<0.0001−1.87 ± 1.37−0.58 ± 1.571.64 ± 2.51<0.0001
    MetS (%)17.32.922.8
    Baseline
    Follow-up
    Control (n = 56)Obese (n = 75)p0Control (n = 33)Intermediate (n = 25)Obese (n = 46)p1
    Total SFA63.5 ± 5.863.4 ± 7.5††0.77663.5 ± 9.760.6 ± 10.361.8 ± 9.20.515
    c12:00.14 ± 0.080.13 ± 0.060.4430.12 ± 0.060.14 ± 0.060.11 ± 0.050.666
    c14:00.54 ± 0.140.51 ± 0.110.3850.54 ± 0.220.52 ± 0.080.50 ± 0.140.435
    c16:038.9 ± 3.738.1 ± 4.80.21339.2 ± 6.436.9 ± 6.537.3 ± 6.20.217
    c18:021.2 ± 2.321.7 ± 2.80.34120.7 ± 3.320.2 ± 3.620.9 ± 2.90.620
    c20:00.51 ± 0.160.53 ± 0.150.3210.55 ± 0.100.52 ± 0.120.55 ± 0.110.941
    c22:01.17 ± 0.49*1.28 ± 0.450.1631.26 ± 0.241.23 ± 0.231.33 ± 0.310.238
    c24:01.05 ± 0.411.10 ± 0.380.3711.12 ± 0.271.05 ± 0.241.07 ± 0.270.413
    Total MUFA11.0 ± 1.611.0 ± 1.60.88911.3 ± 1.011.1 ± 1.211.1 ± 1.10.545
    c16:1n-70.43 ± 0.180.51 ± 0.200.0180.36 ± 0.150.44 ± 0.180.44 ± 0.150.027
    c18:1n-96.89 ± 1.466.79 ± 1.550.5896.23 ± 1.686.68 ± 2.066.62 ± 1.480.278
    c18:1n-71.25 ± 0.231.16 ± 0.210.0391.20 ± 0.281.12 ± 0.201.13 ± 0.260.283
    c20:1n-90.32 ± 0.26*0.32 ± 0.320.4460.62 ± 0.620.50 ± 0.590.43 ± 0.450.197
    c22:1n-90.71 ± 0.420.69 ± 0.490.3061.31 ± 1.080.89 ± 0.990.92 ± 0.840.271
    c24:1n-91.40 ± 0.571.50 ± 0.570.2481.52 ± 0.461.47 ± 0.381.57 ± 0.430.522
    Total n-6 FA21.7 ± 4.3***21.8 ± 5.7†††0.75221.2 ± 8.024.1 ± 8.122.7 ± 7.50.428
    c18:2n-614.2 ± 2.913.7 ± 3.20.28514.0 ± 4.915.4 ± 4.814.4 ± 4.10.690
    c18:3n-60.40 ± 0.130.39 ± 0.140.4970.45 ± 0.180.37 ± 0.110.39 ± 0.110.153
    c20:2n-60.29 ± 0.180.28 ± 0.120.9930.29 ± 0.130.30 ± 0.140.29 ± 0.120.864
    c20:3n-62.08 ± 0.482.38 ± 0.610.0082.00 ± 0.532.28 ± 0.712.39 ± 0.550.007
    c20:4n-64.44 ± 1.74*4.74 ± 2.300.8913.96 ± 3.115.22 ± 3.214.84 ± 3.240.255
    c22:4n-60.18 ± 0.090.21 ± 0.090.1080.24 ± 0.270.24 ± 0.110.21 ± 0.120.894
    


    Total n-3 FA3.72 ± 1.273.82 ± 1.19†††0.6323.72 ± 1.303.80 ± 1.153.80 ± 1.230.367
    c18:3n-30.11 ± 0.070.13 ± 0.070.1090.13 ± 0.090.14 ± 0.080.14 ± 0.110.955
    c20:3n-31.15 ± 0.700.96 ± 0.630.3191.26 ± 0.660.92 ± 0.641.17 ± 0.700.569
    c20:5n-30.37 ± 0.330.42 ± 0.300.3400.42 ± 0.450.53 ± 0.370.45 ± 0.350.663
    c22:5n-30.58 ± 0.34*0.59 ± 0.30†††0.7090.76 ± 0.370.72 ± 0.280.77 ± 0.290.532
    c22:6n-31.51 ± 1.031.71 ± 1.140.4531.54 ± 1.461.95 ± 1.421.89 ± 1.700.591
    Desaturase activity
    D6D0.15 ± 0.040.18 ± 0.04<0.00010.15 ± 0.040.16 ± 0.040.18 ± 0.050.029
    D5D2.15 ± 0.781.95 ± 0.800.0751.85 ± 1.382.10 ± 1.131.94 ± 1.260.590
    SCD-160.011 ± 0.0050.013 ± 0.0060.0160.009 ± 0.0040.012 ± 0.0060.012 ± 0.0040.031
    SCD-180.334 ± 0.1000.323 ± 0.0990.4620.319 ± 0.1260.354 ± 0.1540.328 ± 0.1030.572
    D6DD5DSCD-16SCD-18
    Baseline
    BMI (kg/m2)0.414***−0.203*0.193*−0.093
    BMI z-score0.410***−0.209*0.199*−0.097
    Waist circumference (cm)0.414***−0.254**0.209*−0.137
    SBP (mmHg)0.151−0.1370.1530.068
    DBP (mmHg)0.181*−0.160−0.031−0.039
    AST0.279**−0.1240.153−0.013
    ALT0.370***−0.1640.155−0.070
    Total cholesterol (mg/dL)0.214*−0.0300.0730.110
    HDL-C (mg/dL)−0.292***0.082−0.0900.055
    TG (mg/dL)0.482***−0.1440.1660.015
    Glucose (mg/dL)−0.1380.219*0.1190.126
    Insulin (μIU/mL)0.290**−0.195*0.036−0.072
    HOMA-IR0.267**−0.1610.050−0.054
    Metabolic risk score0.394***−0.258**0.200*−0.006
    Follow-up
    BMI (kg/m2)0.445***−0.279**0.155−0.100
    BMI z-score0.456***−0.297***0.156−0.103
    Waist circumference (cm)0.480***−0.300***0.153−0.087
    SBP (mmHg)0.340***−0.305***−0.017−0.181*
    DBP (mmHg)0.203*−0.155−0.092−0.061
    AST0.131−0.1450.012−0.092
    ALT0.306***−0.258**0.089−0.116
    Total cholesterol (mg/dL)0.197*−0.0920.0910.123
    HDL-C (mg/dL)−0.289***0.1470.0000.135
    TG (mg/dL)0.356***−0.233**0.090−0.105
    Glucose (mg/dL)0.004−0.219*−0.228**−0.208*
    Insulin (μIU/mL)0.377***−0.261**0.046−0.066
    HOMA-IR0.364***−0.278**0.014−0.089
    Metabolic risk score0.436***−0.340***0.112−0.107
    VariableAdjusted
    pr2
    β Coefficient
    Follow up HOMA-IRc
    Waist circumference0.026< 0.00010.206
    D6D0.6190.0070.250
    Follow up metabolic risk scored
    Waist circumference0.135<0.00010.356
    D6D2.3380.0020.402
    Table 1 Anthropometric and biochemical characteristics of the study participants.a

    All values are presented as mean ± standard deviation (SD).

    * Baseline vs. follow-up in control; *p < 0.05; **p < 0.01; ***p < 0.001.

    Baseline vs. follow-up in obese; p < 0.05; ††p < 0.01; †††p < 0.001.

    ALT = alanine aminotransferase; AST = aspartate aminotransferase; BMI = body mass index; DBP = diastolic blood pressure; HDL-C = high-density lipoprotein-cholesterol; HOMA-IR = homeostasis model of assessment of insulin resistance; IU = international unit; SBP = systolic blood pressure; TG = triglyceride; U = unit.

    Tested by unpaired Student t test (p0, *, †) or one-way analysis of variance (ANOVA; p1 = p value for linear trends).

    Data are log transformed prior to analysis.

    Table 2 Plasma PL fatty acid composition and estimated desaturase activity of the study participants.a,b

    All values are presented as mean ± standard deviation (SD).

    * Baseline vs. follow-up in control; *p < 0.05; **p < 0.01; ***p < 0.001.

    Baseline vs. follow-up in obese; p < 0.05; ††p < 0.01; †††p < 0.001.

    D5D = delta-5D; D6D = delta-6D; FA = fatty acid; MUFA = monounsaturated fatty acid; PL = phospholipid; SCD = stearyl-CoAD; SFA = saturated fatty acid.

    Data are log transformed prior to analysis.

    Tested by unpaired Student t test (p0, *, †) or one-way analysis of variance (ANOVA; p1 = p value for linear trends).

    Table 3 Correlation coefficient between estimated desaturase activity and risks for metabolic syndrome.a

    *p < 0.05; **p < 0.01; ***p < 0.001.

    ALT = alanine aminotransferase; AST = aspartate aminotransferase; BMI = body mass index; D5D = delta-5D; D6D = delta-6D; DBP = diastolic blood pressure; HDL-C = high-density lipoprotein-cholesterol; HOMA-IR = homeostasis model of assessment of insulin resistance; IU = international unit; SBP = systolic blood pressure; SCD = stearyl-CoAD; TG = triglyceride.

    Tested by age-adjusted partial correlation analysis; data are log transformed prior to analysis.

    Table 4 Stepwise multiple regression analysis for predicting follow-up HOMA-IR levels and metabolic risk score.a,b

    BMI = body mass index; HDL-C = high-density lipoprotein-cholesterol; HOMA-IR = homeostasis model of assessment of insulin resistance; TG = triglyceride.

    Data are log transformed prior to analysis.

    For multiple stepwise regression analysis, only the two independent variables incorporated into the model are listed, and the r2 values displayed are cumulative.

    Independent variables include: baseline age, BMI z-score, waist circumference, TG, HDL-C, and desaturase.

    Independent variables include: baseline age, waist circumference, and desaturase.


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