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Blood cells as a source of transcriptional biomarkers of childhood obesity and its related metabolic alterations: results of the IDEFICS Study

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Abstract
Background: IDEFICS (Identification and Prevention of Dietary-and Lifestyle-Induced Health Effects in Children and Infants Project) is a European multicenter study on childhood obesity. One of its goals is to define early biomarkers of risk associated with obesity and its comorbid conditions. Objective: We considered blood cells as a new potential source of transcriptional biomarkers for these metabolic disorders and examined whether blood cell mRNA levels of some selected genes (LEPR, INSR, CPT1A, SLC27A2, UCP2, FASN, and PPAR alpha) were altered in overweight children and whether their expression levels could be defined as markers of the insulin-resistant or dyslipidemic state associated with overweight. Design: Blood samples were obtained from 306 normal-weight and overweight children, aged 2-9 yr, from eight different European countries. Whole-blood mRNA levels were assessed by quantitative RT-PCR. Results: LEPR, INSR, and CPT1A mRNA levels were higher in overweight compared with normal-weight children (the two latter only in males), whereas SLC27A2 mRNA levels were lower in overweight children. Significant associations were also found between expression levels of LEPR, INSR, CPT1A, SLC27A2, FASN, PPAR alpha, and different parameters, including body mass index, homeostasis model assessment index, and plasma triglycerides and cholesterol levels. These associations showed that high expression levels of CPT1A, SLC27A2, INSR, FASN, or PPAR alpha may be indicative of a lower risk for the insulin-resistant or dyslipidemic state associated with obesity, whereas low LEPR mRNA levels appear as a marker of high low-density lipoprotein cholesterol, independently of body mass index. Conclusions: These findings point toward the possibility of using the expression levels of these genes in blood cells as markers of metabolic status and can potentially provide an early warning of a future disorder.
Keywords
EXPRESSION, GENES, MULTICENTER, OVERWEIGHT, DISORDERS, LEPTIN INTAKE, FEEDING CONDITIONS, MONONUCLEAR-CELLS, HIGH-FAT DIET, MODEL

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Chicago
Sanchez, Juana, Teresa Priego, Catalina Pico, Wolfgang Ahrens, Stefaan De Henauw, Arno Fraterman, Staffan Marild, et al. 2012. “Blood Cells as a Source of Transcriptional Biomarkers of Childhood Obesity and Its Related Metabolic Alterations: Results of the IDEFICS Study.” Journal of Clinical Endocrinology & Metabolism 97 (4): E648–E652.
APA
Sanchez, Juana, Priego, T., Pico, C., Ahrens, W., De Henauw, S., Fraterman, A., Marild, S., et al. (2012). Blood cells as a source of transcriptional biomarkers of childhood obesity and its related metabolic alterations: results of the IDEFICS Study. JOURNAL OF CLINICAL ENDOCRINOLOGY & METABOLISM, 97(4), E648–E652.
Vancouver
1.
Sanchez J, Priego T, Pico C, Ahrens W, De Henauw S, Fraterman A, et al. Blood cells as a source of transcriptional biomarkers of childhood obesity and its related metabolic alterations: results of the IDEFICS Study. JOURNAL OF CLINICAL ENDOCRINOLOGY & METABOLISM. 2012;97(4):E648–E652.
MLA
Sanchez, Juana, Teresa Priego, Catalina Pico, et al. “Blood Cells as a Source of Transcriptional Biomarkers of Childhood Obesity and Its Related Metabolic Alterations: Results of the IDEFICS Study.” JOURNAL OF CLINICAL ENDOCRINOLOGY & METABOLISM 97.4 (2012): E648–E652. Print.
@article{2975696,
  abstract     = {Background: IDEFICS (Identification and Prevention of Dietary-and Lifestyle-Induced Health Effects in Children and Infants Project) is a European multicenter study on childhood obesity. One of its goals is to define early biomarkers of risk associated with obesity and its comorbid conditions. 
Objective: We considered blood cells as a new potential source of transcriptional biomarkers for these metabolic disorders and examined whether blood cell mRNA levels of some selected genes (LEPR, INSR, CPT1A, SLC27A2, UCP2, FASN, and PPAR alpha) were altered in overweight children and whether their expression levels could be defined as markers of the insulin-resistant or dyslipidemic state associated with overweight. 
Design: Blood samples were obtained from 306 normal-weight and overweight children, aged 2-9 yr, from eight different European countries. Whole-blood mRNA levels were assessed by quantitative RT-PCR. 
Results: LEPR, INSR, and CPT1A mRNA levels were higher in overweight compared with normal-weight children (the two latter only in males), whereas SLC27A2 mRNA levels were lower in overweight children. Significant associations were also found between expression levels of LEPR, INSR, CPT1A, SLC27A2, FASN, PPAR alpha, and different parameters, including body mass index, homeostasis model assessment index, and plasma triglycerides and cholesterol levels. These associations showed that high expression levels of CPT1A, SLC27A2, INSR, FASN, or PPAR alpha may be indicative of a lower risk for the insulin-resistant or dyslipidemic state associated with obesity, whereas low LEPR mRNA levels appear as a marker of high low-density lipoprotein cholesterol, independently of body mass index. 
Conclusions: These findings point toward the possibility of using the expression levels of these genes in blood cells as markers of metabolic status and can potentially provide an early warning of a future disorder.},
  author       = {Sanchez, Juana and Priego, Teresa and Pico, Catalina and Ahrens, Wolfgang and De Henauw, Stefaan and Fraterman, Arno and Marild, Staffan and Molnar, Denes and Moreno, Luisa A and Peplies, Jenny and Russo, Paolo and Siani, Alfonso and Tornaritis, Michael and Veidebaum, Toomas and Palou, Andreu},
  issn         = {0021-972X},
  journal      = {JOURNAL OF CLINICAL ENDOCRINOLOGY \& METABOLISM},
  language     = {eng},
  number       = {4},
  pages        = {E648--E652},
  title        = {Blood cells as a source of transcriptional biomarkers of childhood obesity and its related metabolic alterations: results of the IDEFICS Study},
  url          = {http://dx.doi.org/10.1210/jc.2011-2209},
  volume       = {97},
  year         = {2012},
}

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