Introduction

In western countries, the metabolic syndrome not only affects nearly one in four adults (1) but also points to an ever-increasing major health problem in young populations (2).

It has been shown that an altered mitochondrial function plays a crucial role in the pathogenesis of the metabolic syndrome, as a defective oxidative metabolism seems to be involved in visceral fat gain and in the development of insulin resistance (IR) in fat and skeletal muscle (3).

Recent studies using magnetic resonance spectroscopy in skeletal muscle have shown that a reduction of the mitochondrial function in the insulin-resistant offspring of parents with type 2 diabetes can be mostly attributed to reductions in mitochondrial density (4).

Therefore, both qualitative and quantitative changes in mitochondrial DNA (mtDNA) have been involved in the pathogenesis of type 2 diabetes, while mtDNA content in peripheral leukocytes has been associated to insulin sensitivity (5,6) in adult population. The decreased mtDNA content in peripheral leukocytes that precedes the development of type 2 diabetes (7) is consistent with previous studies demonstrating lower mitochondrial density and decreased mtDNA content in patients with type 2 diabetes (4,7).

In spite of the suggestion that mtDNA status might be a hereditary factor that could serve as an indicator for IR (8), there is no evidence about the role of decreased mtDNA content as an early surrogate marker of IR either in children or in adolescents.

We found that mtDNA content decreases in newborns with abnormal weight in comparison with infants with appropriate weight for gestational age (9). Thus, we speculated that mtDNA depletion may be one of the putative links between abnormal fetal growth and metabolic and cardiovascular complications in later life.

As mtDNA has a limited coding capacity (10,11), maintenance of mtDNA requires the concerted activity of several nuclear-encoded factors that participate in controlling replication, transcription, and translation of mtDNA (12). Working in concert with the mitochondrial transcription factor A (Tfam)—a key regulator of mtDNA copy number—(13), the transcriptional coactivator peroxisome proliferator–activated receptor- coactivator-1 (PGC-1) is able to control mitochondrial biogenesis by interacting with nuclear respiratory factor 1 (ref. 14), peroxisome proliferator–activated receptor- (PPAR-) (15), and perhaps with other nuclear factors (16). Besides, PGC-1 operates as a direct transcriptional coactivator of PPAR- (17).

Given the previously mentioned evidence, this study was designed to test the hypothesis that mtDNA content is related to IR in a sample of adolescents with features of metabolic syndrome. We further investigated the link between common gene variants in the aforementioned three genes involved in the regulation of mitochondrial biogenesis and maintenance of mtDNA replication; namely, Tfam, PPAR- , and PGC-1. In addition, by amplifying a full-length product of mtDNA using long-extension PCR, we also decided to evaluate whether mtDNA content was related to the presence of significant deletions in mtDNA.

Methods and Procedures

Data and blood samples were collected from 175 adolescents out of a cross-sectional, population-based study of 934 high school students of self-reported European ancestry in whom we had previously addressed the prevalence of obesity and hypertension (18,19). As we failed to evaluate mtDNA content in 18 samples, only 157 adolescents were finally included in this study.

Briefly, under parental supervision, subjects responded to a questionnaire on medical history, medication, and personal habits. Anthropometrical assessments included measurement of height, weight, and waist and hip circumferences. Waist circumference was assessed in the standing position, midway between the highest point of the iliac crest and the lowest point of the costal margin in the midaxillary line. Body height and weight were recorded in light clothing, and BMI was computed as weight in kilograms divided by height in meters squared. Resting arterial blood pressure (ABP) was measured after subjects had been sitting for at least 30 min. A mercury sphygmomanometer was used to measure blood pressure three times at the right arm by two investigators using cuffs with the appropriate length and width for the upper arm. We normalized BMI according to age and gender as established by the National Health and Nutrition Examination Survey located at the US Centers for Disease Control and Prevention web site (www.cdc.gov/nchs/about/major/nhanes/growthcharts/datafiles.htm). Resting blood pressure was normalized as a Z-score according to gender and age using the US Task Force tables (1996).

All the investigations performed in this study were conducted in accordance with the Guidelines of The Declaration of Helsinki. Written consent from the participants and their parents was obtained, in accordance with the procedures approved by the Ethical Committee of our institution.

Biochemical measurements

Blood was drawn from fasting subjects who were in a supine resting position for at least 30 min. Plasma glucose, insulin, uric acid, total cholesterol, high-density lipoprotein and low-density lipoprotein cholesterol, and triglycerides were measured using standard clinical laboratory techniques. We used the homeostasis model assessment (HOMA) index (fasting insulin in micro units per milliliter multiplied by fasting glucose in millimoles per liter divided by 22.5) as an estimation of IR. As HOMA cutoff point to identify IR in children or adolescents is not well defined, we divided our population into two groups (noninsulin resistance (NIR) and IR) based on the median value of HOMA-IR of the whole sample (2.2) (ref. 20).

Quantification of mtDNA

Nucleic acids were extracted from white blood cells from a blood sample using a standard method as described previously (21). An assay based on real-time quantitative PCR was used for both nuclear DNA (nDNA) and mtDNA quantification using SYBR green as a fluorescent dye (Invitrogen, Buenos Aires, Argentina).

The primer sequences for mtDNA, mtF3212 (5'-CACCCAAGAACAGGGTTTGT-3') and mtR3319 (5'-TGGCCATGGGTATGTT-GTTAA-3') and those for nDNA for loading normalization, 18S rRNA gene 18S1546F (5'-TAGAGGGACAAGTGGCGTTC-3') and 18S1650R (5'-CGCTGAGCCAGTCA-GTGT3') were reported by Bai et al. previously (22).

The PCR profile was 1 cycle of 95 °C for 2 min, followed by 35 cycles (95 °C 15 s and 60 °C 1 min). Real-time quantitative PCR was carried out in a Bio-Rad iCycler (Bio-Rad Laboratories, Hercules, CA). The calculation of DNA copy number involved extrapolation from the fluorescence readings in the mode of background subtracted form the Bio-Rad iCycler (Bio-Rad Laboratories) according to Rutledge (23). Specificity of amplification and the absence of primer dimers was confirmed by melting curve analysis at the end of each run.

The two-target amplicon sequence (mtDNA and nDNA) was visualized in agarose 2% and purified using Qiagen Qiaex II, Gel extraction Kit (Tecnolab, Buenos Aires, Argentina) and dilutions of purified amplicons were used as the standard curve. The interassay variation coefficient was <20%.

To ensure the specificity of the method and to avoid variability in the results because of the presence of mtDNA sequences in nDNA, we decided to sequence 20 samples selected from our studied population using the previously mentioned primers. The PCR products of forward and reverse sequencing were detected on an ABI3730XL self-loading high-throughput capillary sequencer provided as a service (Macrogen, Seoul, Korea). Next, we aligned the sequences in FASTA format using JALVIEW version 2.3 (ref. 24), including the consensus mtDNA sequence (available at http://www.mitomap.org/mitoseq.html) and two other nuclear sequences that, although shorter, were found to present the highest homology (92%) with the mtDNA sequence (ref|NT_004836.17|Hs1_4993 and ref|NT_011630.14|HsX_11787, respectively) using Blast software available at the NCBI site (www.ncbi.nlm.nih.gov). We observed that our samples were unique to human mtDNA as they showed a complete homology with mtDNA consensus sequence. On the contrary, the nDNA sequences showed some mismatch compared with either the mtDNA consensus sequence or the amplicon corresponding to the mtDNA sequence in our studied population samples (data not shown).

Long-extension PCR

Long-extension PCR was used to evaluate the presence of deleted mtDNA. The isolated DNA from peripheral blood was amplified according to the methods described by Bender et al. (25). Briefly, we used two different primer pairs to amplify the entire mitochondrial genome. The first product length was 10,421 bp: forward primer nt5876–5896 (CACTCAGCCATTTTACCTCAC); reverse primer nt16296–16276 (GTGGGTAGGTTTGTTGGTATC). The second product length was 6,600 bp: forward primer nt16007–16026 (CTTTCATGGGGAAGCAGATT) and reverse primer: nt6114–6095 (CTCCGATTATGATGGGTATT). All primers are numbered according to the Cambridge Reference Sequence (www.mitomap.org/mitoseq.html). Long-extension PCR products were separated by electrophoresis on a 0.8% agarose gel stained with ethidium bromide.

Genotyping

The genetic analyses were done on genomic DNA extracted from white blood cells as mentioned earlier. Genotyping for PPAR- (pro12Ala), PGC-1 (Gly482Ser), and Tfam (rs1937 and rs12247015) polymorphisms was performed by hot-start PCR-based restriction fragment length polymorphism analysis using a Robocycler 96 thermal cycler (Stratagene, La Jolla, CA) and Molecular Biology grade reagents unless otherwise indicated. Primers to detect the Gly482Ser variant were 5'-CAA GTC CTC AGT CCT CAC-3' and 5'-GGG GTC TTT GAG AAA ATA AGG-3'; and genotyping employed digestion with MspI (New England Biolabs, Ipswich, MA) as described previously (26).

Primers to detect Pro12Ala variant were 5'-GCC AAT TCA AGC CCA GTC-3' and 5'-GAT ATG TTT GCA GAC AGT GTA TCA GTG AAG GAA TCG CTT TCC G-3'; the variant was genotyped employing digestion with BstUI (New England Biolabs, Ipswich, MA) as described elsewhere (27).

Single-nucleotide polymorphisms at Tfam were located in the promoter region and a coding region to screen genetic polymorphisms in common variants with known frequencies at the time of the study. Primers to detect the rs1937 polymorphism (nonsynonymous coding G/C at exon 1) were 5'-TAGGAGGGGCAGAAAGTGA-3' and 5'-CGGGTTCCAGTTGTGATTG-3', and genotyping used digestion with DdeI (New England Biolabs, Ipswich, MA). For, the rs12247015 (A/G at the 5'-UTR region) primers were 5'-GTGTGTTATCATGCCCGCCACTA-3' and 5'-GGCGGCCGGGGACAGAGGT-3' and genotyping employed digestion with BstUI (New England Biolabs).

Statistical analysis

Quantitative data were expressed as mean s.d. unless otherwise indicated. Because for most of the variables we observed a significant variance difference between groups and, in most cases, the distribution was significantly skewed, we chose to be conservative and to assess differences between groups by the Mann–Whitney's U-test or ANOVA and Neuman–Keuls test. Genotypes frequencies were analyzed by ² test. Correlation between two variables was performed by Spearman rank correlation test. In addition, multiple regression was used to analyze the correlation between the HOMA index as a dependent variable and systolic ABP (SABP) Z-score, uric acid levels, BMI Z-score, and as independent variables; and mtDNA/nDNA ratio as a dependent variable and age, waist-to-hip ratio, SABP Z-score, HOMA index, BMI Z-score, and PPAR- , PGC-1, and Tfam genotypes.

We used the CSS/Statistica program package, StatSoft V 6.0 (Tulsa, OK) to perform these analyses. A P value <0.05 was considered to be statistically significant.

Results

Characteristics of the study population according to IR status are shown in Table 1. The IR group had significantly higher fasting plasma glucose, insulin, high-density lipoprotein cholesterol, triglycerides, uric acid, HOMA index, SABP and diastolic ABP Z-score, and BMI Z-score than the NIR group.

Table 1 - Clinical characteristics of the study population according to the absence or presence of insulin resistance.

Full table (62K)

The mtDNA/nDNA ratio was inversely correlated with HOMA (R: -0.18, P < 0.02), plasma glucose levels (R: -0.21, P < 0.008), and uric acid levels (R: -0.18, P < 0.03).

Multiple regression analysis showed that HOMA index was independently correlated with SABP Z-score ('s: 0.23 0.08, P < 0.005), uric acid levels ('s: 0.22 0.07, P < 0.004), BMI Z-score ('s: 0.19 0.08, P < 0.02), and mtDNA/nDNA ratio ('s: -0.14 0.06, P < 0.04). In addition, mtDNA/nDNA ratio was significantly lower in the IR group (median: 9.08, range: 68.94) in comparison with the NIR one (median: 12.24, range: 71.92) (P < 0.03, Figure 1).

Figure 1.

Peripheral blood mitochondrial DNA/nuclear DNA ratio (mtDNA/nDNA) in noninsulin resistance (0) and insulin resistance (1) groups. Results are shown as follows: empty squares for individual data, the central boxes represent the values from the lower to the upper quartile (25 and 75 percentile). The middle lines represent the median. A line extends from the minimum to the maximum values, excluding "outside" and "far-out" values, which are displayed as full squares. P < 0.03 by Mann–Whitney's U-test.

Full figure and legend (12K)

Variants of PPAR- (pro12Ala), PGC-1 (Gly482Ser), and Tfam (rs1937 and rs12247015) were evaluated in the whole sample, and genotype frequencies were in Hardy–Weinberg equilibrium and similar to those reported in other populations (data not shown). We studied the mtDNA content in relation with the aforementioned variants at the candidate genes, and we found no significant differences in the mtDNA/nDNA ratio among the genotypes neither in NIR nor in IR groups (see Table 2). Furthermore, using multiple regressions, we found that the effect of genotypes on mtDNA content remained insignificant after adjustment by age, waist-to-hip ratio, SBP Z-score, HOMA index, and BMI Z-score (data not shown).

Table 2 - Peripheral blood leukocyte mtDNA content (mtDNA/nDNA ratio, median, and range) according to PPAR- (pro12Ala), PGC-1 (Gly482Ser), and Tfam (rs1937 and rs12247015) genotypes in noninsulin resistance (NIR) and insulin resistance (IR) adolescents.

Full table (55K)

Overall, the results of the long-extension PCR using two different primer pairs designed to amplify the entire genome of mtDNA showed no presence of significant deletions either in IR subjects or in NIR ones.

Discussion

There is substantial data showing a direct relation between mitochondrial function and IR in adult population. In this study, we tested whether peripheral leukocytes mtDNA content normalized by nDNA may be associated with IR in adolescents with features of the metabolic syndrome. We found that the mtDNA/nDNA ratio was inversely correlated with plasma glucose, HOMA index, and uric acid levels. Besides, HOMA index was inversely correlated with mtDNA/nDNA independently of SABP and BMI Z-score and uric acid. Therefore, the mtDNA/nDNA ratio was lower in IR adolescents than in NIR ones.

These results are consistent with those previously reported not only in experimental models but also in human disease. For example, the depletion of mtDNA in an insulin-sensitive cell line expressing an extracellular myc epitope–tagged glucose transporter 4 (L6 GLUT4myc) was directly correlated with a drastic reduction in basal glucose utilization and resistance to insulin stimulation (28). Other studies have shown a decrease of mtDNA content in tissues of individuals with impaired glucose tolerance (28,29) and also in peripheral blood mtDNA of offspring of patients with type 2 diabetes (8). It was also observed that mtDNA content may precede the development of type 2 diabetes as, even before the development of the disease (7), mtDNA copy number in subjects who became diabetic in 2 years was lower than in controls.

About the observed inverse relation between mtDNA content and uric acid levels, it is worth noting that uric acid and HOMA index were similarly related to mtDNA content. Although uric acid is not part of any definition of the metabolic syndrome, several studies have shown robust associations between uric acid levels and the metabolic syndrome, mainly in adults (30). Thus, our finding is in agreement with a recent report showing a positive association between concentrations of serum uric acid and the prevalence of the metabolic syndrome in adolescents (31).

We further aimed to determine whether the diminished peripheral blood mtDNA content observed in our adolescents with IR bore some relation to gene variants of master mitochondrial biogenesis regulators. Then, we studied the Gly482Ser single-nucleotide polymorphism in PGC-1 gene, which changes lysine to serine in codon 482 and the Pro12Ala in PPAR- gene variant, a common missense mutation in the functional domain, both variants associated with either type 2 diabetes pathogenesis or IR in several populations (27,32,33). Besides, we included two gene variants of Tfam, one in the promoter region and the other in the first exon of the gene, as no functional single-nucleotide polymorphism has yet been detected in Tfam. We did not observe any significant association between leukocyte mtDNA content and the aforementioned gene variants even after adjustment for potential confounders such as age, SABP and BMI Z-scores, waist-to-hip ratio, and HOMA index. Although we were unable to find a significant association between PGC-1, PPAR- , and TFAM polymorphisms and mtDNA content, we do not exclude the possibility that a novel or untyped variant in linkage equilibrium with the selected single-nucleotide polymorphisms in the previously mentioned genes may be involved in the regulation of mtDNA content. Besides, even though mtDNA content is supposed to be related to several factors, for example genetic control, the mechanisms regarding regulation of mtDNA content are not entirely clear.

To evaluate whether mtDNA content was related to the presence of deleted mtDNA, we performed long-range PCR of the mtDNA to amplify the entire mitochondrial genome (25). Comparison of the size of the amplicons between individuals with and without IR did not show any mtDNA deletion to justify the main finding mentioned previously. We might speculate that the decrease of mtDNA content in peripheral leukocytes in insulin-resistant subjects of our population is due to a decrease in mtDNA copy number (owing to either a decreased mitochondrial number or a decrease in the mtDNA genome copy number per mitochondria) rather than to higher levels of single or multiple deletions in mitochondrial genome. These findings should be cautiously considered in the light of the level of the amount of deleted mtDNA detected using this qualitative method even though long-range PCR is a sensitive and very helpful technique for determining single or multiple deletions (34).

In summary, our results indicate that reduced mtDNA content in peripheral leukocyte is associated with IR and elevated uric acid levels in adolescents.

Although more studies performed on larger population samples are necessary to confirm our findings, this study provides further support for future research to clarify both the pathogenic and the predictive role of mtDNA content in adolescents with metabolic syndrome as an early biomarker of the disease.

Disclosure

The authors declared no conflict of interest.

References

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Acknowledgments

This study was supported partially by grants B119 (Universidad de Buenos Aires), PICT 05-08719, and PICT 25920 (Agencia Nacional de Promoción Científica y Tecnológica) and funds provided by Fundación Alfredo Lanari and Fundación Diabetes. S.S., C.G., S.I.G., and C.J.P. belong to Consejo Nacional de Investigaciones Científicas y Técnicas and T.F.G. is a recipient of a Health Ministry Fellowship (Beca Ramón Carrillo-Arturo Oñativia Ministerio de Salud y Ambiente de la Nación, Convocatoria 2007).