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Epigenomic profiling in visceral white adipose tissue of offspring of mice exposed to late gestational sleep fragmentation.

Cortese R, Khalyfa A, Bao R, Andrade J, Gozal D - Int J Obes (Lond) (2015)

Bottom Line: A large proportion of the DMR-associated genes have reported functions that are altered in obesity and metabolic syndrome, such as Cartpt, Akt2, Apoe, Insr1 and so on.Our findings show a major role for epigenomic regulation of pathways associated with the metabolic processes and inflammatory responses in VWAT.LG-SF-induced epigenetic alterations may underlie increases in the susceptibility to obesity and metabolic syndrome in the offspring.

View Article: PubMed Central - PubMed

Affiliation: Section of Pediatric Sleep Medicine, Department of Pediatrics, Pritzker School of Medicine, The University of Chicago, Chicago, IL, USA.

ABSTRACT

Background: Sleep fragmentation during late gestation (LG-SF) is one of the major perturbations associated with sleep apnea and other sleep disorders during pregnancy. We have previously shown that LG-SF induces metabolic dysfunction in offspring mice during adulthood.

Objectives: To investigate the effects of late LG-SF on metabolic homeostasis in offspring and to determine the effects of LG-SF on the epigenome of visceral white adipose tissue (VWAT) in the offspring.

Methods: Time-pregnant mice were exposed to LG-SF or sleep control during LG (LG-SC) conditions during the last 6 days of gestation. At 24 weeks of age, lipid profiles and metabolic parameters were assessed in the offspring. We performed large-scale DNA methylation analyses using methylated DNA immunoprecipitation (MeDIP) coupled with microarrays (MeDIP-chip) in VWAT of 24-week-old LG-SF and LG-SC offspring (n=8 mice per group). Univariate multiple-testing adjusted statistical analyses were applied to identify differentially methylated regions (DMRs) between the groups. DMRs were mapped to their corresponding genes, and tested for potential overlaps with biological pathways and gene networks.

Results: We detected significant increases in body weight (31.7 vs 28.8 g; P=0.001), visceral (642.1 vs 497.0 mg; P=0.002) and subcutaneous (293.1 vs 250.1 mg; P=0.001) fat mass, plasma cholesterol (110.6 vs 87.6 mg dl(-1); P=0.001), triglycerides (87.3 vs 84.1 mg dl(-1); P=0.003) and homeostatic model assessment-insulin resistance values (8.1 vs 6.1; P=0.007) in the LG-SF group. MeDIP analyses revealed that 2148 DMRs (LG-SF vs LG-SC; P<0.0001, model-based analysis of tilling-arrays algorithm). A large proportion of the DMR-associated genes have reported functions that are altered in obesity and metabolic syndrome, such as Cartpt, Akt2, Apoe, Insr1 and so on. Overrepresented pathways and gene networks were related to metabolic regulation and inflammatory response.

Conclusions: Our findings show a major role for epigenomic regulation of pathways associated with the metabolic processes and inflammatory responses in VWAT. LG-SF-induced epigenetic alterations may underlie increases in the susceptibility to obesity and metabolic syndrome in the offspring.

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Differentially methylated regions between LG-SF and LF-SC groupsA) Unsupervised clustering of samples in the LG-SF and LG-SC groups based on DMR values. Samples are accommodated in columns and DMRs in rows. Z-score depicting the DNA methylation differences between the groups (DMRs with increased DNA methylation in LG-SF and LG-SC groups had positive and negative values, respectively) are shown in a color gradient ranging from blue (negative Z-scores) to red (positive scores). B) The number of probes per DMR did not differ between DMRs with increasing DNA methylation in the LG-SF (red box) and LG-SC (blue box) groups (p-value = 0.075, Wilcoxon rank sum test). C) Density plot of DMR lengths. DMRs with higher methylation in the LG-SF group were significantly shorter than those with higher methylation in the LG-SC group (p=0.003, Wilcoxon rank sum test). D) Distance to TSS did not differ significantly between DMRs higher methylated in the LG-SF and LG-SC groups (p=0.601; Wilcoxon rank sum test). The distance from the beginning of each region to the closest TSS are shown in the X-axis. Red and blue lines represent the LG-SF and LG-SC groups, respectively.
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Figure 2: Differentially methylated regions between LG-SF and LF-SC groupsA) Unsupervised clustering of samples in the LG-SF and LG-SC groups based on DMR values. Samples are accommodated in columns and DMRs in rows. Z-score depicting the DNA methylation differences between the groups (DMRs with increased DNA methylation in LG-SF and LG-SC groups had positive and negative values, respectively) are shown in a color gradient ranging from blue (negative Z-scores) to red (positive scores). B) The number of probes per DMR did not differ between DMRs with increasing DNA methylation in the LG-SF (red box) and LG-SC (blue box) groups (p-value = 0.075, Wilcoxon rank sum test). C) Density plot of DMR lengths. DMRs with higher methylation in the LG-SF group were significantly shorter than those with higher methylation in the LG-SC group (p=0.003, Wilcoxon rank sum test). D) Distance to TSS did not differ significantly between DMRs higher methylated in the LG-SF and LG-SC groups (p=0.601; Wilcoxon rank sum test). The distance from the beginning of each region to the closest TSS are shown in the X-axis. Red and blue lines represent the LG-SF and LG-SC groups, respectively.

Mentions: We investigated how LG-SF affects the VWAT epigenome in the offspring using MeDIP-chip in VWAT samples of 24 week old offspring of the LG-SF and LG-SC groups (n=8 mice per group). Microarray data underwent extensive quality control. Quantile normalization with correction for probe sequence resulted in homogenous distribution of the microarray signal (Figure S1), and enabled the unbiased detection of DNA methylation differences between the LG-SF and LG-SC groups. All microarrays (n=16) passed technical quality control, without the need to exclude any of the data from downstream analysis. Based on the full set of probes in the microarray (n=4,103,551 probes), samples from the same groups showed higher correlation coefficients (Figure 1A) and clustered together in Principal Component Analysis (PCA) (Figure 1B). We detected 45,756 probes differentially methylated probes between the groups (p-value < 0.01; two-way ANOVA), with 25,258 and 20,498 probes showing increased DNA methylation in the LG-SF and LG-SC groups, respectively (Figure 1C). Next, we defined differentially methylated regions (DMRs) between the groups by combining adjacent probes showing statistically significant differential DNA methylation using the MAT algorithm (34) and the criteria detailed in Materials and Methods. We identified 2,148 DMRs (Figure 2A and Table S2). Of these, 497 and 1,651 DMRs showed higher DNA methylation in the LG-SF or LG-SC groups, respectively.


Epigenomic profiling in visceral white adipose tissue of offspring of mice exposed to late gestational sleep fragmentation.

Cortese R, Khalyfa A, Bao R, Andrade J, Gozal D - Int J Obes (Lond) (2015)

Differentially methylated regions between LG-SF and LF-SC groupsA) Unsupervised clustering of samples in the LG-SF and LG-SC groups based on DMR values. Samples are accommodated in columns and DMRs in rows. Z-score depicting the DNA methylation differences between the groups (DMRs with increased DNA methylation in LG-SF and LG-SC groups had positive and negative values, respectively) are shown in a color gradient ranging from blue (negative Z-scores) to red (positive scores). B) The number of probes per DMR did not differ between DMRs with increasing DNA methylation in the LG-SF (red box) and LG-SC (blue box) groups (p-value = 0.075, Wilcoxon rank sum test). C) Density plot of DMR lengths. DMRs with higher methylation in the LG-SF group were significantly shorter than those with higher methylation in the LG-SC group (p=0.003, Wilcoxon rank sum test). D) Distance to TSS did not differ significantly between DMRs higher methylated in the LG-SF and LG-SC groups (p=0.601; Wilcoxon rank sum test). The distance from the beginning of each region to the closest TSS are shown in the X-axis. Red and blue lines represent the LG-SF and LG-SC groups, respectively.
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Figure 2: Differentially methylated regions between LG-SF and LF-SC groupsA) Unsupervised clustering of samples in the LG-SF and LG-SC groups based on DMR values. Samples are accommodated in columns and DMRs in rows. Z-score depicting the DNA methylation differences between the groups (DMRs with increased DNA methylation in LG-SF and LG-SC groups had positive and negative values, respectively) are shown in a color gradient ranging from blue (negative Z-scores) to red (positive scores). B) The number of probes per DMR did not differ between DMRs with increasing DNA methylation in the LG-SF (red box) and LG-SC (blue box) groups (p-value = 0.075, Wilcoxon rank sum test). C) Density plot of DMR lengths. DMRs with higher methylation in the LG-SF group were significantly shorter than those with higher methylation in the LG-SC group (p=0.003, Wilcoxon rank sum test). D) Distance to TSS did not differ significantly between DMRs higher methylated in the LG-SF and LG-SC groups (p=0.601; Wilcoxon rank sum test). The distance from the beginning of each region to the closest TSS are shown in the X-axis. Red and blue lines represent the LG-SF and LG-SC groups, respectively.
Mentions: We investigated how LG-SF affects the VWAT epigenome in the offspring using MeDIP-chip in VWAT samples of 24 week old offspring of the LG-SF and LG-SC groups (n=8 mice per group). Microarray data underwent extensive quality control. Quantile normalization with correction for probe sequence resulted in homogenous distribution of the microarray signal (Figure S1), and enabled the unbiased detection of DNA methylation differences between the LG-SF and LG-SC groups. All microarrays (n=16) passed technical quality control, without the need to exclude any of the data from downstream analysis. Based on the full set of probes in the microarray (n=4,103,551 probes), samples from the same groups showed higher correlation coefficients (Figure 1A) and clustered together in Principal Component Analysis (PCA) (Figure 1B). We detected 45,756 probes differentially methylated probes between the groups (p-value < 0.01; two-way ANOVA), with 25,258 and 20,498 probes showing increased DNA methylation in the LG-SF and LG-SC groups, respectively (Figure 1C). Next, we defined differentially methylated regions (DMRs) between the groups by combining adjacent probes showing statistically significant differential DNA methylation using the MAT algorithm (34) and the criteria detailed in Materials and Methods. We identified 2,148 DMRs (Figure 2A and Table S2). Of these, 497 and 1,651 DMRs showed higher DNA methylation in the LG-SF or LG-SC groups, respectively.

Bottom Line: A large proportion of the DMR-associated genes have reported functions that are altered in obesity and metabolic syndrome, such as Cartpt, Akt2, Apoe, Insr1 and so on.Our findings show a major role for epigenomic regulation of pathways associated with the metabolic processes and inflammatory responses in VWAT.LG-SF-induced epigenetic alterations may underlie increases in the susceptibility to obesity and metabolic syndrome in the offspring.

View Article: PubMed Central - PubMed

Affiliation: Section of Pediatric Sleep Medicine, Department of Pediatrics, Pritzker School of Medicine, The University of Chicago, Chicago, IL, USA.

ABSTRACT

Background: Sleep fragmentation during late gestation (LG-SF) is one of the major perturbations associated with sleep apnea and other sleep disorders during pregnancy. We have previously shown that LG-SF induces metabolic dysfunction in offspring mice during adulthood.

Objectives: To investigate the effects of late LG-SF on metabolic homeostasis in offspring and to determine the effects of LG-SF on the epigenome of visceral white adipose tissue (VWAT) in the offspring.

Methods: Time-pregnant mice were exposed to LG-SF or sleep control during LG (LG-SC) conditions during the last 6 days of gestation. At 24 weeks of age, lipid profiles and metabolic parameters were assessed in the offspring. We performed large-scale DNA methylation analyses using methylated DNA immunoprecipitation (MeDIP) coupled with microarrays (MeDIP-chip) in VWAT of 24-week-old LG-SF and LG-SC offspring (n=8 mice per group). Univariate multiple-testing adjusted statistical analyses were applied to identify differentially methylated regions (DMRs) between the groups. DMRs were mapped to their corresponding genes, and tested for potential overlaps with biological pathways and gene networks.

Results: We detected significant increases in body weight (31.7 vs 28.8 g; P=0.001), visceral (642.1 vs 497.0 mg; P=0.002) and subcutaneous (293.1 vs 250.1 mg; P=0.001) fat mass, plasma cholesterol (110.6 vs 87.6 mg dl(-1); P=0.001), triglycerides (87.3 vs 84.1 mg dl(-1); P=0.003) and homeostatic model assessment-insulin resistance values (8.1 vs 6.1; P=0.007) in the LG-SF group. MeDIP analyses revealed that 2148 DMRs (LG-SF vs LG-SC; P<0.0001, model-based analysis of tilling-arrays algorithm). A large proportion of the DMR-associated genes have reported functions that are altered in obesity and metabolic syndrome, such as Cartpt, Akt2, Apoe, Insr1 and so on. Overrepresented pathways and gene networks were related to metabolic regulation and inflammatory response.

Conclusions: Our findings show a major role for epigenomic regulation of pathways associated with the metabolic processes and inflammatory responses in VWAT. LG-SF-induced epigenetic alterations may underlie increases in the susceptibility to obesity and metabolic syndrome in the offspring.

Show MeSH
Related in: MedlinePlus