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Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. SUPPLEMENTARY MATERIAL
  8. Acknowledgments
  9. Disclosure
  10. REFERENCES
  11. Supporting Information

To analyze in severely obese women the circadian expression of the clock genes hPer2, hBmal1, and hCry1 in explants from subcutaneous (SAT) and visceral (VAT) adipose tissue (AT), in order to elucidate whether this circadian clockwork can oscillate accurately and independently of the suprachiasmatic nucleus (SCN) and if glucocorticoid metabolism-related genes such as glucocorticoid receptor (hGr) and 11β-hydroxysteroid dehydrogenase 1 (h11βHsd1) and the transcription factor peroxisome proliferator activated receptor γ (hPPARγ) are part of the clock controlled genes. AT biopsies were obtained from morbid obese patients (BMI ≥40 kg/m2) (n = 7). Anthropometric variables were measured and fasting plasma lipids and lipoprotein concentrations were analyzed. In order to carry out rhythmic expression analysis, AT explants were cultured during 24 h and gene expression was performed at the following times (T): 0, 6, 12, and 18 h, with quantitative real-time PCR. Clock genes oscillated accurately and independently of the SCN in AT explants. Their intrinsic oscillatory mechanism regulated the timing of other genes such as hPPARγ and glucocorticoid-related genes. Circadian patterns differed between VAT and SAT. Correlation analyses between the genetic circadian oscillation and components of the metabolic syndrome (MetS) revealed that subjects with a higher sagittal diameter showed an increased circadian variability in hPer2 expression (r = 0.91; P = 0.031) and hBmal1 (r = 0.90; P = 0.040). Data demonstrate the presence of peripheral circadian oscillators in human AT independently of the central circadian control mechanism. This knowledge paves the way for a better understanding of the circadian contribution to medical conditions such as obesity and MetS.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. SUPPLEMENTARY MATERIAL
  8. Acknowledgments
  9. Disclosure
  10. REFERENCES
  11. Supporting Information

Circadian rhythms are ingrained in our lives; however, little attention has been paid to their metabolic consequences. It has been suggested that disruption of the circadian system may be related to expression of the metabolic syndrome (MetS) (1). Thus, shift work, sleep deprivation and exposure to bright light at night have been shown to be related to increased adiposity and prevalence of MetS (1,2).

Recent findings support the notion that rhythmic expression of circadian genes exists not only in the brain but in several other tissues (3,4). Along these lines, we have shown clock gene expression in human adipose tissue (AT) (5) and demonstrated that this expression was associated with different components of the MetS (5). An important question is whether this circadian clockwork can oscillate accurately and independently of the suprachiasmatic nucleus (SCN) in human AT and whether other genes are controlled by this process.

The objective of the present research was to analyze the circadian expression of the clock genes hPer2, hBmal1 and hCry1 in AT explants from morbid obese women from subcutaneous (SAT) and visceral (VAT) AT, in order to elucidate whether this circadian clockwork can oscillate accurately and independently of the SCN and if glucocorticoid metabolism-related genes such as that glucocorticoid receptor (hGr) and 11β-hydroxysteroid dehydrogenase 1 (h11βHsd1) and the master transcription factor peroxisome proliferator activated receptor γ (hPPARγ) are controlled by clock genes.

Methods and Procedures

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. SUPPLEMENTARY MATERIAL
  8. Acknowledgments
  9. Disclosure
  10. REFERENCES
  11. Supporting Information

Subjects

VAT and SAT abdominal AT biopsies were obtained from severely obese women (n = 7), age: 49 ± 10 years, and BMI: 43.6 ± 5.2 kg/m2, undergoing laparoscopic gastric bypass surgery due to obesity, from the General Surgery Service of “Virgen de la Arrixaca” Hospital. The day before the surgery all patients were synchronized having lunch at 1430 hours and having dinner at 2100 hours. The AT biopsies were taken as paired samples from the two AT depots: VAT (omental) and SAT (abdominal) at the beginning of the surgical procedure (estimated time of biopsies sampling from 1000 to 1400 hours).

The protocols were approved by the Ethics Committee of the “Virgen de la Arrixaca” University Hospital, and the subjects signed a written informed consent before the biopsies were obtained.

Clinical characteristics

BMI, waist and hip circumference, and skinfolds (biceps, triceps, suprailiac, and subscapular) were measured with a Harpenden caliper (Holtain, Crymych, UK). Total body fat (%) was measured by bioimpedance with a TANITA Model TBF-300 (TANITA Corporation of America, Arlington Heights, IL). Sagittal diameter and coronal diameter were measured at the level of the iliac crest (L4–5) using a Holtain Kahn Abdominal Caliper. Fasting Plasma concentrations of triacylglycerols, total cholesterol, high-density lipoprotein, and low-density lipoprotein cholesterol were determined with commercial kits (Roche Diagnostics, Mannheim, Germany). Arterial pressure was also measured.

AT culture

Explants were placed at 37 °C for 24 h in a humidified atmosphere containing 7% CO2 in 100 mm diameter dishes. AT (800–1,000 mg) was placed in 5 ml of Dulbecco's modified Eagle's medium supplemented with 10% fetal bovine serum.

On the next day, the adipose explants were collected to perform gene expression analysis at the following times (T): 0, 6, 12, and 18 in which T0 was arbitrarily defined as 0800 hours, because this was the usual waking time for patients, T6 as 1400 hours, T12 as 2000 hours, and T18 as 0200 hours. All cultures were performed in duplicates.

Analysis of gene expression

Reverse transcription was performed using random hexamers as primers and Thermoscript reverse transcriptase (Invitrogen, Cergy-Pontoise, France) with 1 µg total RNA for each sample.

Quantitative real-time PCR was performed using an ABI PRISM 7900 HT Sequence Detection System as described by the provider (Applied Biosystems, Foster City, CA). PCR Master MIX (Perkin-Elmer, Norwalk, CT) containing Hot Start Taq DNA polymerase was used. Taqman probes for hPer2, hBmal1, hCry1 and 18S rRNA as internal control were also supplied by Applied Biosystems (Assay-by-Design). All samples were determined as duplicates, and for a negative control the same setup was used except for the addition of reverse transcriptase. No PCR product was detected under these latter conditions. In brief, clock genes mRNA and 18S RNA were amplified in separated wells at 95 °C for 10 min and thereafter repeating cycles comprised of 95 °C for 30 s and 60 °C for 60 s for annealing and extension steps. During the extension step increase in fluorescence was measured in real-time.

Data were obtained as Ct values according to the manufacturer's guidelines, and used to determine ΔCt values (ΔCt = Ct of the target gene—Ct of the housekeeping gene (18S)) of each sample. Fold changes of gene expression were calculated by the 2−ΔΔCt method (6).

Statistical analysis

Clinical and anthropometric data are presented as means ± s.d. The results for gene expression, expressed in arbitrary units, are presented as means ± s.e.m. Paired t-test was used for comparing data from the samples derived from the two adipose depots in each individual subject.

The single cosinor method was used to analyze for circadian rhythm individually and as a group (7). This inferential method involves fitting a curve of a predefined period by the least squares method. The rhythm characteristics and their 95% confidence intervals estimated by this method include the mesor (middle value of the fitted cosine representing a rhythm-adjusted mean), the amplitude (half the difference between the minimum and maximum of the fitted cosine function), and the temporal location of maximum value or acrophase (the time at which the peak of a rhythm occurs, expressed in hours). Differences in rhythmicity among the genes studied and between AT depots were analyzed comparing the amplitude and the % of variance by ANOVA and paired t-test. The significance of the rhythms was determined by rejection of the zero amplitude hypotheses with a threshold of 60%. All statistical analyses were carried out using SPSS for windows (release 15.0; SPSS, Chicago, IL). The level of significance for all statistical tests and hypotheses was set at P < 0.05.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. SUPPLEMENTARY MATERIAL
  8. Acknowledgments
  9. Disclosure
  10. REFERENCES
  11. Supporting Information

Characteristics of the population and basal gene expression

Table 1 contains general characteristics of the women studied. The average values for waist circumference, glucose, and systolic pressure exceeded the cutoff points proposed by the International Diabetes Federation (8) for the definition of MetS.

Table 1.  Clinical characteristics of the population studied
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Basal gene expression for the genes under investigation, was similar for both SAT and VAT depots. Analysis of the relations among genes within each of the groups (Clock genes and other functional genes) showed significant and positive correlations in the SAT (P < 0.05). However, these significant correlations were absent within the VAT. Furthermore, when we analyzed the relation between the expression of clock genes and MetS features, we found that hPer2 expression in SAT correlated negatively with BMI (r = −0.86; P = 0.048) and with thigh circumference (r = −0.93; P = 0.024) whereas hBmal1 showed significant correlation with body fat variables (r = −0.92; P = 0.011), total cholesterol (r = −0.99; P = 0.002), low-density lipoprotein Cholesterol (r = −0.97; P = 0.006), and glucose concentrations (r = −0.89; P = 0.041).

Circadian gene expression

Figure 1 shows mean circadian rhythms for the three clock genes (Figure 1a) as well as for the other AT functional genes studied (hPPARγ, hGr, and h11βHsd1) (Figure 1b). We have observed circadian expression patterns for all the genes (data recently published for glucocorticoid metabolism-related and PPARγ genes (9)) investigated in these subjects except for the housekeeping gene 18S. Parameters imputed from each subject obtained by cosinor analysis (7) defining the circadian rhythms as mesor, amplitude, acrophase and percentage of variance are shown in Supplementary Table S1 online. These data indicate that among the clock genes examined, hPer2 was the one showing the highest circadian oscillation (P = 0.001), followed by hCry1 and hBmal1. hBmal1 oscillated with approximately the same phase as hPer2. In addition, VAT showed a higher cadence than SAT for all the genes examined.

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Figure 1. Circadian rhythms of all genes studied in total population. Rhythmic expression of clock genes (hPer2, hBmal1, and hCry1) (a) and other functional genes in human adipose tissue (hPPARγ, h11βHsd1, and hGr) (b) in both subcutaneous and visceral tissues. Adipose depots were isolated at 6-h intervals over the course of the day from adipose tissue cultures (time at 0, 6, 12, and 18 hours). Results are presented relative to the lowest basal relative expression for each gene. Data of relative expression are represented as Arbitrary Units (AU). Data are reported as means ± s.e.m. (s.e.m. of ΔCt are represented in parenthesis).

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Correlation analyses between the genetic circadian oscillation (amplitude) and components of the MetS revealed that those subjects with a higher sagittal diameter showed an increased circadian variability in hPer2 SAT expression (r = 0.91; P = 0.031) and hBmal1 (r = 0.90; P = 0.040).

Phase map of the genes studied

Figure 2 shows phase map of gene expression for clock genes and other functional genes. Average acrophases (the time at which the peak of a rhythm occurs, expressed in hours) imputed from cosinor analysis of hPer2, hBmal1, hCry1, hPPARγ, h11βHsd1 and hGr were plotted against 24 h-time scale. An interesting finding was that clock genes anticipated in their expression to the other genes implicated both, SAT (P = 0.003) and VAT AT (P = 0.01) metabolism. The response of hPPARγ, h11βHsd1, and hGr to the action of clock genes seemed to be faster in VAT than in SAT (11.3 h vs. 16.3 h, respectively).

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Figure 2. Phase map of genes studied in both subcutaneous and visceral tissues. Acrophases imputed from cosinor analyses of all genes studied in subcutaneous (a) and visceral (b) depots for total population. Values are shown as mean ± s.d. for clock genes (squares) and other functional genes (diamonds).

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Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. SUPPLEMENTARY MATERIAL
  8. Acknowledgments
  9. Disclosure
  10. REFERENCES
  11. Supporting Information

We have demonstrated in human AT the presence of active circadian clock mechanisms and confirmed their periodic nature. An important consideration is that this rhythm persists ex vivo for at least two circadian cycles after surgery. These results are consistent with previously reported findings for clock genes in cells extracted from other tissues (10,11,12,13). The persistency of gene expression oscillations in vitro strongly suggests the existence of an intracellular circadian clock system directly regulating local cell functions (14). Previously, we provided evidence of clock genes expression and demonstrated that it was associated with different components of MetS (5). However, it remained to be elucidated whether this circadian clockwork could oscillate accurately and independently of the SCN in human AT, and which other genes were controlled in this process.

An interesting observation obtained from the present work was that 24 h rhythmic expression patterns was observed for all the genes investigated, except for the housekeeping gene (18S), suggesting their potential role in the circadian machinery in human AT. Among the clock genes studied, hPer2 was the gene with the highest oscillation pattern. Similar results were obtained in AT from other diurnal and nocturnal mammals (15,16).

Our current data in women are consistent with our previous findings in men showing an inverse relationship between basal hPer2 expression and obesity parameters (5). The fact that circadian oscillations of hPer2 were positively related with sagittal diameter strongly supports a role for hPer2 in the physiological disturbances leading to the MetS (5).

The hBmal1 gene also showed significant correlations with components of the MetS, both in terms of its basal expression and in its rhythm. Bmal1 has been shown to play essential roles in the regulation of adipocyte differentiation and lipogenesis (17,18).

An important aspect of circadian regulation is that rhythms are expressed in a particular phase relationship to one another. With respect to hBmal1, our data show that this clock gene oscillated with approximately the same phase as hPer2, instead of being antiphasic as anticipated from data previously obtained in other peripheral tissues (19). This unusual phase relationship has also been previously described. Similar results have been obtained in human peripheral blood mononuclear cells (19) and in mouse bone marrow (20). It is essential to note that in addition to Per2 and Cry1, other genes are involved in the regulation of Bmal1 in the molecular circadian oscillator. Indeed, a secondary stabilizing loop is established by the negative, orphan nuclear hormone receptor that is encoded on the noncoding strand of the thyroid hormone receptor α-gene, and positive, retinoic acid–related orphan receptor-α effect on Bmal1 transcription through their activity on retinoic acid–related orphan receptor response elements. PPARα also induces Bmal1 and Rev-Erbα transcription through its action on PPRE located in their respective promoters. Most of these genes are highly regulated by fatty acids and are implicated in AT metabolism. Therefore, we could hypothesize that AT could present an especial circadian behavior influenced by its particular characteristics such as: fat cell size and number, fatty acid composition, etc. Further studies focusing on these genes expression in human AT will be necessary.

Our results are at odds with “ex vivo” analyses of circadian gene expression in synchronized cultures of human adipose-derived cells (21). One important difference between both studies is that we performed our study in severely obese women, whereas in Wu et al. study women were normal weight (21). As has been previously demonstrated chronodisruption could be present in these obese subjects, explaining discrepancies (22). Other interesting difference is that in the current study, primary AT cells were used, in contrast to the study of Wu et al. which was performed in secondary cultures of adipose-derived stem cells.

It has been established that VAT adiposity is more closely associated with the MetS than SAT adiposity. In the present work VAT behaves remarkably different from SAT. Expression of the genes examined showed significant correlation in SAT; however, no such correlation was apparent in VAT. These results resemble those previously reported for some clock genes (5). Moreover, our data show that the rhythm of the genes studied was more robust in VAT than in SAT fat depot, consistent with previous data in mice (14). Glucocorticoids are circadian key hormones strongly implicated in the MetS physiopathology (23). Recently, it has been demonstrated that glucocorticoids genes show circadian patterns (9). One of objective of the present study was to elucidate if glucocorticoids genes circadian expression could be in some way related to clock genes behavior in human AT. Our results indicate that hGr and h11βHsd together with hPPARγ, oscillated in antiphase in extra- and intra-abdominal depots (9), suggesting that the internal circadian regulation of each fat depot metabolism could act in a region dependent manner.

Moreover, when acrophases, time at which the peak of a rhythm occurs, for the genes analyzed were plotted against 24-h time scale, we observed the presence of two markedly different groups: one for the clock genes and the other for hPPARγ, hGr and hHsd. From these results we could hypothesize that hPPARγ and glucocorticoids genes are associated to clock genes (24). It has been reported that hPPARγ can directly regulate the transcription of clock genes (25). Further studies focusing on the regulatory circadian mechanisms and transcriptional targets of hPPARγ, especially those related with energy balance and lipoprotein metabolism (26) may provide insights into the pathogenesis of MetS. Interesting, the response to the action of clock genes in VAT preceded that in SAT by 7 h, suggesting an AT site specific differential response to the clock genes output signals. The one weakness of this study is the limited number of patients included, which is due to the considerable difficulties in obtaining enough fat from VAT and SAT locations within the same patients to perform four different AT explants cultures. However, from a statistical point of view this is not a limitation because most of the statistical analyses were performed comparing different points in the same subject. Another important aspect is that the surgical procedure itself could be affecting the circadian pattern of clock genes. However, our main purpose was to demonstrate the presence of circadian rhythmicity in an ex vivo setting, independently of the rhythmicity pattern, and our results indicate that even under these conditions, clock genes demonstrate a circadian pattern unable to occur without the presence of a functional internal clock in AT itself.

In conclusion, circadian clockwork can oscillate accurately and independently of the SCN in AT explants and this intrinsic oscillatory mechanism may participate in regulating the timing of other genes such as hPPARγ and glucocorticoid metabolism-related genes. Moreover, we have demonstrated that this circadian regulation differs between VAT and SAT depots. The strength of this paper is the novelty and growing interest of this area of research and the relevance of showing in humans the existence of circadian rhythm in human AT and its relation to the MetS. We feel confident that our contribution will pave the way for a better understanding of the circadian contribution to various medical and endocrine conditions related with AT metabolism such as obesity, MetS and cardiovascular diseases.

In light of these results, further investigations should aim to (i) compare AT circadian behavior between obese and normal-weight patients; (ii) study how different zeitgebers such as glucocorticoids input, cell starvation, and changes of light exposure, could influence these circadian patters in human AT cultures, and (iii) analyze the circadian rhythmicity of MetS-related-cytokines and their plausible regulation by this newly identified intrinsic circadian clock.

Acknowledgments

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. SUPPLEMENTARY MATERIAL
  8. Acknowledgments
  9. Disclosure
  10. REFERENCES
  11. Supporting Information

This work was supported by the Seneca Foundation from the Government of Murcia (project 02934/PI/05 to MG) and by the Government of Education, Science and Research of Murcia (project BIO/FFA 07/01-0004) and by the Spanish Government of Science and Innovation (projects AGL2008-01655/ALI) by NIDDK grant DK075030, and by contracts 53-K06-5-10 and 58-1950-9-001 from the US Department of Agriculture Research Service. C.G.-S. contributed to AT culture development and manuscript preparation. P. G.-A. carried out gene expression and contributed to manuscript preparation. J.J.H-M contributed to gene expression. J.A.M interpreted the results. J.A.L. contributed to technical assistance in obtaining adipose tissue. J.M.O. contributed to manuscript preparation and interpreted the results. M.G. explained the hypothesis, contributed to manuscript preparation and coordinated this work.

REFERENCES

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. SUPPLEMENTARY MATERIAL
  8. Acknowledgments
  9. Disclosure
  10. REFERENCES
  11. Supporting Information

Supporting Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. SUPPLEMENTARY MATERIAL
  8. Acknowledgments
  9. Disclosure
  10. REFERENCES
  11. Supporting Information

supporting Information

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