pii: sp- 00105 -16
http://dx.doi.org/10.5665/sleep.5612
COMMENTARY
Methylation Changes in DNA in Patients with Obstructive Sleep Apnea Commentary on Chen et al. Whole genome DNA methylation analysis of obstructive sleep apnea: IL1R2, NPR2, AR, SP140 methylation and clinical phenotype. SLEEP 2016;39(4):743–755. Allan I. Pack, MBChB, PhD, FRCP Division of Sleep Medicine/Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
In this issue of SLEEP, there is an interesting article about differences in methylation patterns in patients with obstructive sleep apnea in Taiwan.1 As the authors point out, there are differences between individuals in levels of methylation at different sites in the genome (DNA). These can be inherited or be the result of environmental influences during the lifespan of the individual. Alteration of DNA by methylation affects the access of transcription factors to promotor regions and hence leads to altered transcription of the relevant gene. Typically, increases in methylation leads to reduced transcription and hypomethylation to the converse, i.e., increased transcription. The patterns of methylation found in individual subjects are different in different cell types. There are technologies now readily available to assess methylation levels across the whole genome. As with any broad approach there are multiple comparisons involved and hence the possibility of false positives. This is the first study to examine methylation patterns in adults with obstructive sleep apnea (OSA). There is a previous study in pediatric patients.2 The study reported has some important strengths. The study design had an initial discovery sample followed by replication analyses of specific findings in an independent cohort. The sample size was, however, small. The initial discovery sample was 16 patients with obstructive sleep apnea (OSA) and 8 healthy individuals without habitual snoring. Investigators identified outliers and one OSA patient and two controls were removed leaving a final discovery sample of 15 patients and only 6 controls. The validation sample included 48 patients with OSA and 24 subjects with primary snoring. The apnea-hypopnea index in these two groups was very different: 53.8 ± 22.5 events/hour and 2.8 ± 2.0 events/hour, respectively (P < 0.001). Another strength is that the investigators studied only one cell type, i.e., peripheral blood mononuclear cells. This removes variability due to different patterns of methylation in different cell types, i.e., cellular heterogeneity. Finally, the investigators also measured protein levels using ELISA for the genes being studied since, as described above, differences in methylation should alter expression of the gene and hence protein levels. The authors found a number of differences in methylation levels in several genes between cases and controls in the discovery sample. They also found differences in the small sample of patients in the discovery phase with hypertension (n = 8) and those without hypertension (n = 7). They chose to examine methylation levels over the promoter region in six selected genes identified in the discovery phase in the validation cohort. No significant differences in these methylation levels between cases and controls in the SLEEP, Vol. 39, No. 4, 2016
validation phase were found. Thus, in this sense the study is negative. The differences found in the discovery phase could be false positives. The investigators then chose to do analyses on different subsets of patients. They appreciated that sleep apnea is not a homogeneous entity. There is a wide variation in severity. Moreover, as recently identified, there are different clinical subtypes with only some patients having excessive daytime sleepiness.3 Specifically, they compared methylation levels of the six selected genes in those patients with oxygen saturation index (ODI) > 30 events/hour to those ≤ 30, and in a second analysis in patients with an Epworth Sleepiness Score (ESS) > 10 to those with ≤ 10. Additional correlation analyses were conducted treating ODI and ESS as continuous variables. It is unclear if these additional analyses were specified in advance or are exploratory given the initial negative primary analysis. These additional analyses did identify some interesting findings. They need, however, to be considered hypothesis generating. They found decreased methylation at a specific site on the IL1R2 promoter region in patients with ODI > 30 compared to those with ODI ≤ 30. Supporting this observation is the finding that subjects with ODI > 30 events/hour have a significantly higher level of the protein for IL1R2. This is a decoy receptor for IL1 that negatively regulates the activity of IL1. Differences in methylation in the 5-alpha reductase (AR) promoter in subjects with different severities of OSA were also found. However, changes in this protein level were unexpected and in the converse direction, i.e., higher in those with greater methylation. This gene—5 alpha-reductase—is involved in the synthesis of testosterone. With respect to sleepiness (ESS ≤ 10 compared to > 10) differences in methylation and expected differences in protein levels were found for two genes NPR2 and SP140. NPR2 is involved in the cyclic guanosine monophosphate pathway (cGMP), while SP140 is a protein that is induced by interferon. cGMP has been implicated in sleep/wake control in mice4 and indeed in other species5 This study, therefore, represents a beginning. It requires others to seek to validate the main findings with respect to differences in methylation patterns and protein levels in mononuclear cells in individuals with different severities of OSA and those who are sleepy and those who are not. In thinking about validation, it is important to remember that OSA occurs in Asian populations at lower levels of BMI than in Caucasians.6 In the study reported here the BMI of the groups was between 25.0 and 27.0 kg/m2. It is conceivable that obesity may exert a modifying effect. The association with methylation levels also does not tell us about direction. Are these differences in 723
Commentary—Pack
methylation inherited and hence play a role in pathogenesis of OSA and its consequences? Alternatively, are these differences the consequence of the presence of OSA, e.g., from cyclical intermittent hypoxia, such that it results in modification of the genome? As described in the whitepaper on biomarkers published in this issue of SLEEP,7 there are now a wide variety of “OMIC” techniques available to move this area of investigation forward. There are, moreover, multiple applications of new biomarker approaches to clinical issues in obstructive sleep apnea.7,8 There is a need for international efforts in this area with standardization of phenotyping and biomarker assessment. It is terrific to see our colleagues in Taiwan moving this area forward.
4. Langmesser S, Franken P, Feil S, Emmenegger Y, Albrecht U, Feil R. cGMP-dependent protein kinase type I is implicated in the regulation of the timing and quality of sleep and wakefulness. PLoS One 2009;4:e4238. 5. Zimmerman JE, Naidoo N, Raizen DM, Pack AI. Conservation of sleep: insights from non-mammalian model systems. Trends Neurosci 2008;31:371–6. 6. Lee RW, Vasudavan S, Hui DS, et al. Differences in craniofacial structures and obesity in Caucasian and Chinese patients with obstructive sleep apnea. Sleep 2010;33:1075–80. 7. Mullington JM, Abbott SM, Carroll JE, et al. Developing biomarker arrays predicting sleep and circadian-coupled risks to health. Sleep 2016;39:727–36. 8. Khalyfa A, Gileles-Hillel A, Gozal D. The challenges of precision medicine in obstructive sleep apnea. Sleep Med Clin 2016; in press.
SUBMISSION & CORRESPONDENCE INFORMATION
CITATION Pack AI. Methylation changes in DNA in patients with obstructive sleep apnea. SLEEP 2016;39(4):723–724.
Submitted for publication March, 2016 Accepted for publication March, 2016 Address correspondence to: Allan I. Pack, MBChB, PhD, FRCP, John Miclot Professor of Medicine, Director, Center for Sleep and Circadian Neurobiology, Chief, Division of Sleep Medicine/Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA; Tel: (215) 746-4806; Fax: (215) 746-4814; Email: pack@ mail.med.upenn.edu
REFERENCES 1. Chen YC, Chen TW, Su MC, et al. Whole genome DNA methylation analysis of obstructive sleep apnea: IL1R2, NPR2, AR, SP140 methylation and clinical phenotype. Sleep 2016;39:743–55. 2. Kim J, Bhattacharjee R, Khalyfa A, et al. DNA methylation in inflammatory genes among children with obstructive sleep apnea. Am J Respir Crit Care Med 2012;185:330–8. 3. Ye LC, Plan GW, Ratcliffe SJ, et al. The different clinical faces of obstructive sleep apnoea: a cluster analysis. Eur Respir J 2014;44:1600–7.
SLEEP, Vol. 39, No. 4, 2016
DISCLOSURE STATEMENT Dr. Pack has indicated no financial conflicts of interest.
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Commentary—Pack
http://dx.doi.org/10.5665/sleep.5612
COMMENTARY
Methylation Changes in DNA in Patients with Obstructive Sleep Apnea Commentary on Chen et al. Whole genome DNA methylation analysis of obstructive sleep apnea: IL1R2, NPR2, AR, SP140 methylation and clinical phenotype. SLEEP 2016;39(4):743–755. Allan I. Pack, MBChB, PhD, FRCP Division of Sleep Medicine/Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
In this issue of SLEEP, there is an interesting article about differences in methylation patterns in patients with obstructive sleep apnea in Taiwan.1 As the authors point out, there are differences between individuals in levels of methylation at different sites in the genome (DNA). These can be inherited or be the result of environmental influences during the lifespan of the individual. Alteration of DNA by methylation affects the access of transcription factors to promotor regions and hence leads to altered transcription of the relevant gene. Typically, increases in methylation leads to reduced transcription and hypomethylation to the converse, i.e., increased transcription. The patterns of methylation found in individual subjects are different in different cell types. There are technologies now readily available to assess methylation levels across the whole genome. As with any broad approach there are multiple comparisons involved and hence the possibility of false positives. This is the first study to examine methylation patterns in adults with obstructive sleep apnea (OSA). There is a previous study in pediatric patients.2 The study reported has some important strengths. The study design had an initial discovery sample followed by replication analyses of specific findings in an independent cohort. The sample size was, however, small. The initial discovery sample was 16 patients with obstructive sleep apnea (OSA) and 8 healthy individuals without habitual snoring. Investigators identified outliers and one OSA patient and two controls were removed leaving a final discovery sample of 15 patients and only 6 controls. The validation sample included 48 patients with OSA and 24 subjects with primary snoring. The apnea-hypopnea index in these two groups was very different: 53.8 ± 22.5 events/hour and 2.8 ± 2.0 events/hour, respectively (P < 0.001). Another strength is that the investigators studied only one cell type, i.e., peripheral blood mononuclear cells. This removes variability due to different patterns of methylation in different cell types, i.e., cellular heterogeneity. Finally, the investigators also measured protein levels using ELISA for the genes being studied since, as described above, differences in methylation should alter expression of the gene and hence protein levels. The authors found a number of differences in methylation levels in several genes between cases and controls in the discovery sample. They also found differences in the small sample of patients in the discovery phase with hypertension (n = 8) and those without hypertension (n = 7). They chose to examine methylation levels over the promoter region in six selected genes identified in the discovery phase in the validation cohort. No significant differences in these methylation levels between cases and controls in the SLEEP, Vol. 39, No. 4, 2016
validation phase were found. Thus, in this sense the study is negative. The differences found in the discovery phase could be false positives. The investigators then chose to do analyses on different subsets of patients. They appreciated that sleep apnea is not a homogeneous entity. There is a wide variation in severity. Moreover, as recently identified, there are different clinical subtypes with only some patients having excessive daytime sleepiness.3 Specifically, they compared methylation levels of the six selected genes in those patients with oxygen saturation index (ODI) > 30 events/hour to those ≤ 30, and in a second analysis in patients with an Epworth Sleepiness Score (ESS) > 10 to those with ≤ 10. Additional correlation analyses were conducted treating ODI and ESS as continuous variables. It is unclear if these additional analyses were specified in advance or are exploratory given the initial negative primary analysis. These additional analyses did identify some interesting findings. They need, however, to be considered hypothesis generating. They found decreased methylation at a specific site on the IL1R2 promoter region in patients with ODI > 30 compared to those with ODI ≤ 30. Supporting this observation is the finding that subjects with ODI > 30 events/hour have a significantly higher level of the protein for IL1R2. This is a decoy receptor for IL1 that negatively regulates the activity of IL1. Differences in methylation in the 5-alpha reductase (AR) promoter in subjects with different severities of OSA were also found. However, changes in this protein level were unexpected and in the converse direction, i.e., higher in those with greater methylation. This gene—5 alpha-reductase—is involved in the synthesis of testosterone. With respect to sleepiness (ESS ≤ 10 compared to > 10) differences in methylation and expected differences in protein levels were found for two genes NPR2 and SP140. NPR2 is involved in the cyclic guanosine monophosphate pathway (cGMP), while SP140 is a protein that is induced by interferon. cGMP has been implicated in sleep/wake control in mice4 and indeed in other species5 This study, therefore, represents a beginning. It requires others to seek to validate the main findings with respect to differences in methylation patterns and protein levels in mononuclear cells in individuals with different severities of OSA and those who are sleepy and those who are not. In thinking about validation, it is important to remember that OSA occurs in Asian populations at lower levels of BMI than in Caucasians.6 In the study reported here the BMI of the groups was between 25.0 and 27.0 kg/m2. It is conceivable that obesity may exert a modifying effect. The association with methylation levels also does not tell us about direction. Are these differences in 723
Commentary—Pack
methylation inherited and hence play a role in pathogenesis of OSA and its consequences? Alternatively, are these differences the consequence of the presence of OSA, e.g., from cyclical intermittent hypoxia, such that it results in modification of the genome? As described in the whitepaper on biomarkers published in this issue of SLEEP,7 there are now a wide variety of “OMIC” techniques available to move this area of investigation forward. There are, moreover, multiple applications of new biomarker approaches to clinical issues in obstructive sleep apnea.7,8 There is a need for international efforts in this area with standardization of phenotyping and biomarker assessment. It is terrific to see our colleagues in Taiwan moving this area forward.
4. Langmesser S, Franken P, Feil S, Emmenegger Y, Albrecht U, Feil R. cGMP-dependent protein kinase type I is implicated in the regulation of the timing and quality of sleep and wakefulness. PLoS One 2009;4:e4238. 5. Zimmerman JE, Naidoo N, Raizen DM, Pack AI. Conservation of sleep: insights from non-mammalian model systems. Trends Neurosci 2008;31:371–6. 6. Lee RW, Vasudavan S, Hui DS, et al. Differences in craniofacial structures and obesity in Caucasian and Chinese patients with obstructive sleep apnea. Sleep 2010;33:1075–80. 7. Mullington JM, Abbott SM, Carroll JE, et al. Developing biomarker arrays predicting sleep and circadian-coupled risks to health. Sleep 2016;39:727–36. 8. Khalyfa A, Gileles-Hillel A, Gozal D. The challenges of precision medicine in obstructive sleep apnea. Sleep Med Clin 2016; in press.
SUBMISSION & CORRESPONDENCE INFORMATION
CITATION Pack AI. Methylation changes in DNA in patients with obstructive sleep apnea. SLEEP 2016;39(4):723–724.
Submitted for publication March, 2016 Accepted for publication March, 2016 Address correspondence to: Allan I. Pack, MBChB, PhD, FRCP, John Miclot Professor of Medicine, Director, Center for Sleep and Circadian Neurobiology, Chief, Division of Sleep Medicine/Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA; Tel: (215) 746-4806; Fax: (215) 746-4814; Email: pack@ mail.med.upenn.edu
REFERENCES 1. Chen YC, Chen TW, Su MC, et al. Whole genome DNA methylation analysis of obstructive sleep apnea: IL1R2, NPR2, AR, SP140 methylation and clinical phenotype. Sleep 2016;39:743–55. 2. Kim J, Bhattacharjee R, Khalyfa A, et al. DNA methylation in inflammatory genes among children with obstructive sleep apnea. Am J Respir Crit Care Med 2012;185:330–8. 3. Ye LC, Plan GW, Ratcliffe SJ, et al. The different clinical faces of obstructive sleep apnoea: a cluster analysis. Eur Respir J 2014;44:1600–7.
SLEEP, Vol. 39, No. 4, 2016
DISCLOSURE STATEMENT Dr. Pack has indicated no financial conflicts of interest.
724
Commentary—Pack
