Na Wu, Xiangyu Zhai, X. Tan, P. Wiklund, Sulin Cheng
{"title":"PO-185生活方式干预改变有失眠症状的超重和肥胖男性脂肪组织DNA甲基化","authors":"Na Wu, Xiangyu Zhai, X. Tan, P. Wiklund, Sulin Cheng","doi":"10.14428/ebr.v1i4.12783","DOIUrl":null,"url":null,"abstract":"Objective To study whether diet and exercise intervention affect sleep and obesity-related genes’ DNA methylation in overweight and obese men with insomnia symptoms \nMethods The study participants were a subgroup of a large intervention and consisted of 10 overweight or obesity men aged 34-65 years with insomnia symptoms. They participated in a 6-month progressive aerobic exercise training and individualized dietary consoling program and were randomly selected from diet (n=4), exercise (n=3) and control (n=3) groups. Body composition included fat mass and lean mass in the whole body and abdominal android region were assessed by dual-energy X-ray densitometry. The fitness level (VO2max) was determined by 2-km walk test using a standard protocol. Blood samples from venous were taken at fasted state in the morning. Total cholesterol, high density lipid cholesterol, low density lipid cholesterol, triglycerides, glucose, insulin, non-esterified fatty acid, alanine aminotransferase, aspartate aminotransferase and γ-glutamyltransferase were assessed by conventional methods. Subcutaneous adipose tissue was taken from abdominal region before and after the intervention. DNA was extracted from subcutaneous adipose tissue using a QIAamp DNeasy Tissue Kit. Whole genome-wide DNA methylation was obtained using MethylRAD-Seq. MethylRAD library preparation started from DNA digestion by FspEI, then digested products were run on agarose gel to verify digestion and DNA ligase was added to the digestion solution. After ligation products amplication, PCR was conducted by MyCycler thermal cycler (Bio-Rad). The target fragment was excised from polyacrylamide gel and DNA was diffused from the gel in nuclease-free water. For relative quantification of MethylRAD data, DNA methylation levels were determined using the normalized read depth (reads per million, RPM) for each site. For each restriction site, its methylation level was estimated by dividing the log-transformed depth of each site by the log-transformed maximum depth (representing 100% methylation; i.e. M-index ¼ log(depth site)/ log(depth max)), where depth max was summarized from the top 2% of sites (approx. 500 for the standard library) with the highest sequencing coverage. Heat map images are generated with Matlab 7.0 software and pathways are analysed by WEB-based Gene SeT AnaLysis Toolket. A statistical significance for methylated CpGs and pathways were set to p=0.001 and p=0.05, respectively. \nResults No significant group differences by time were found in sleep-related variables, body composition, lifestyle factors nor with measured lipid and glucose biomarkers. However, whole genome-wide DNA methylation was decreased after dietary intervention, but was increased after exercise intervention, respectively. Correspondingly, 1253 and 708 differentially methylated loci were found in diet and exercise groups by contrast to the control group. Among them, the overlap genes between diet and exercise had multiple differentially methylated CpGs, including e.g. MYT1L (4 CpGs), CAMTA1 (3 CpGs), NRXN1 (3 CpGs), RPS6KA2 (3 CpGs), SEMA4D (3 CpGs). DNA methylation in PCDH8 was negatively correlated with wake after sleep onset after exercise intervention and MYRIP associated with sleep duration showed lower methylation after the dietary intervention. Further, 13 (DIO1, GCK, GYS1, \nLMNA, LY86, PNMT, PPARA, PPARD, SERPINE1, TH, TMEM18, TNFRSF1B and UBL5) and 2 (SDCCAG8 and TNF) obesity-related genes’ DNA methylation profile changed in response to diet and exercise, respectively. Percentage changes of CpGs within KLHDC8A, ANKS1A, FGFRL1 and KDM3B were correlated with energy yield fat and carbohydrate, HOMA-IR and VO2max, respectively. \nConclusions We found that both exercise and dietary interventions have impacts on these genes related to sleep indicating by DNA methylation in PCDH8 and MYRIP, respectively. Further diet may be more effective than aerobic exercise intervention since greater number of modified obesity-related genes observed after dietary intervention. Our results indicate that reduce insomnia symptoms may need to more focus on control obesity.","PeriodicalId":12276,"journal":{"name":"Exercise Biochemistry Review","volume":"61 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"PO-185 Lifestyle intervention modify DNA methylation of adipose tissue in overweight and obese men with insomnia symptoms\",\"authors\":\"Na Wu, Xiangyu Zhai, X. Tan, P. Wiklund, Sulin Cheng\",\"doi\":\"10.14428/ebr.v1i4.12783\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Objective To study whether diet and exercise intervention affect sleep and obesity-related genes’ DNA methylation in overweight and obese men with insomnia symptoms \\nMethods The study participants were a subgroup of a large intervention and consisted of 10 overweight or obesity men aged 34-65 years with insomnia symptoms. They participated in a 6-month progressive aerobic exercise training and individualized dietary consoling program and were randomly selected from diet (n=4), exercise (n=3) and control (n=3) groups. Body composition included fat mass and lean mass in the whole body and abdominal android region were assessed by dual-energy X-ray densitometry. The fitness level (VO2max) was determined by 2-km walk test using a standard protocol. Blood samples from venous were taken at fasted state in the morning. Total cholesterol, high density lipid cholesterol, low density lipid cholesterol, triglycerides, glucose, insulin, non-esterified fatty acid, alanine aminotransferase, aspartate aminotransferase and γ-glutamyltransferase were assessed by conventional methods. Subcutaneous adipose tissue was taken from abdominal region before and after the intervention. DNA was extracted from subcutaneous adipose tissue using a QIAamp DNeasy Tissue Kit. Whole genome-wide DNA methylation was obtained using MethylRAD-Seq. MethylRAD library preparation started from DNA digestion by FspEI, then digested products were run on agarose gel to verify digestion and DNA ligase was added to the digestion solution. After ligation products amplication, PCR was conducted by MyCycler thermal cycler (Bio-Rad). The target fragment was excised from polyacrylamide gel and DNA was diffused from the gel in nuclease-free water. For relative quantification of MethylRAD data, DNA methylation levels were determined using the normalized read depth (reads per million, RPM) for each site. For each restriction site, its methylation level was estimated by dividing the log-transformed depth of each site by the log-transformed maximum depth (representing 100% methylation; i.e. M-index ¼ log(depth site)/ log(depth max)), where depth max was summarized from the top 2% of sites (approx. 500 for the standard library) with the highest sequencing coverage. Heat map images are generated with Matlab 7.0 software and pathways are analysed by WEB-based Gene SeT AnaLysis Toolket. A statistical significance for methylated CpGs and pathways were set to p=0.001 and p=0.05, respectively. \\nResults No significant group differences by time were found in sleep-related variables, body composition, lifestyle factors nor with measured lipid and glucose biomarkers. However, whole genome-wide DNA methylation was decreased after dietary intervention, but was increased after exercise intervention, respectively. Correspondingly, 1253 and 708 differentially methylated loci were found in diet and exercise groups by contrast to the control group. Among them, the overlap genes between diet and exercise had multiple differentially methylated CpGs, including e.g. MYT1L (4 CpGs), CAMTA1 (3 CpGs), NRXN1 (3 CpGs), RPS6KA2 (3 CpGs), SEMA4D (3 CpGs). DNA methylation in PCDH8 was negatively correlated with wake after sleep onset after exercise intervention and MYRIP associated with sleep duration showed lower methylation after the dietary intervention. Further, 13 (DIO1, GCK, GYS1, \\nLMNA, LY86, PNMT, PPARA, PPARD, SERPINE1, TH, TMEM18, TNFRSF1B and UBL5) and 2 (SDCCAG8 and TNF) obesity-related genes’ DNA methylation profile changed in response to diet and exercise, respectively. Percentage changes of CpGs within KLHDC8A, ANKS1A, FGFRL1 and KDM3B were correlated with energy yield fat and carbohydrate, HOMA-IR and VO2max, respectively. \\nConclusions We found that both exercise and dietary interventions have impacts on these genes related to sleep indicating by DNA methylation in PCDH8 and MYRIP, respectively. Further diet may be more effective than aerobic exercise intervention since greater number of modified obesity-related genes observed after dietary intervention. Our results indicate that reduce insomnia symptoms may need to more focus on control obesity.\",\"PeriodicalId\":12276,\"journal\":{\"name\":\"Exercise Biochemistry Review\",\"volume\":\"61 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Exercise Biochemistry Review\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.14428/ebr.v1i4.12783\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Exercise Biochemistry Review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14428/ebr.v1i4.12783","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
目的研究饮食和运动干预是否影响有失眠症状的超重和肥胖男性的睡眠和肥胖相关基因的DNA甲基化。方法研究参与者是一个大型干预的亚组,由10名34-65岁有失眠症状的超重或肥胖男性组成。他们参加了为期6个月的渐进式有氧运动训练和个性化饮食安慰计划,并从饮食组(n=4)、运动组(n=3)和对照组(n=3)中随机选择。采用双能x线密度仪测定全身及腹部脂肪、瘦肉质量。健康水平(VO2max)通过2公里步行测试确定,采用标准方案。早晨空腹取静脉血样。采用常规方法测定总胆固醇、高密度脂质胆固醇、低密度脂质胆固醇、甘油三酯、葡萄糖、胰岛素、非酯化脂肪酸、丙氨酸转氨酶、天冬氨酸转氨酶和γ-谷氨酰转移酶。干预前后分别取腹部皮下脂肪组织。使用QIAamp脱氧核糖核酸组织试剂盒从皮下脂肪组织中提取DNA。使用MethylRAD-Seq获得全基因组DNA甲基化。甲基rad文库的制备从FspEI酶切DNA开始,酶切产物在琼脂糖凝胶上进行酶切验证,酶切液中加入DNA连接酶。结扎产物扩增后,用MyCycler热循环仪(Bio-Rad)进行PCR。从聚丙烯酰胺凝胶中切除目标片段,将DNA从凝胶中扩散到无核酸酶的水中。对于MethylRAD数据的相对量化,使用每个位点的标准化读取深度(reads per million, RPM)来确定DNA甲基化水平。对于每个酶切位点,其甲基化水平通过将每个位点的对数转换深度除以对数转换最大深度(代表100%甲基化;即M-index¼log(深度站点)/ log(深度最大值)),其中深度最大值汇总自前2%的站点(约。500(标准文库),测序覆盖率最高。热图图像由Matlab 7.0软件生成,通路通过基于web的Gene SeT AnaLysis Toolket分析。甲基化CpGs和通路的统计学意义分别为p=0.001和p=0.05。结果在睡眠相关变量、身体成分、生活方式因素以及测量的脂质和葡萄糖生物标志物方面,各组间没有明显的时间差异。然而,饮食干预后全基因组DNA甲基化降低,运动干预后全基因组DNA甲基化增加。相应地,与对照组相比,饮食组和运动组分别发现了1253和708个不同的甲基化位点。其中,饮食与运动重叠基因存在多个差异甲基化CpGs,如MYT1L(4个CpGs)、CAMTA1(3个CpGs)、NRXN1(3个CpGs)、RPS6KA2(3个CpGs)、SEMA4D(3个CpGs)。运动干预后,PCDH8 DNA甲基化与睡眠后醒来呈负相关,而饮食干预后,与睡眠持续时间相关的MYRIP甲基化水平较低。此外,13个(DIO1、GCK、GYS1、LMNA、LY86、PNMT、PPARA、PPARD、SERPINE1、TH、TMEM18、TNFRSF1B和UBL5)和2个(SDCCAG8和TNF)肥胖相关基因的DNA甲基化特征分别随饮食和运动而改变。KLHDC8A、ANKS1A、FGFRL1和KDM3B中CpGs的百分比变化分别与能量产量、脂肪和碳水化合物、HOMA-IR和VO2max相关。我们发现运动和饮食干预都对这些与睡眠相关的基因有影响,这分别通过PCDH8和MYRIP的DNA甲基化来表明。进一步的饮食可能比有氧运动干预更有效,因为在饮食干预后观察到更多的肥胖相关基因。我们的研究结果表明,减少失眠症状可能需要更多地关注控制肥胖。
PO-185 Lifestyle intervention modify DNA methylation of adipose tissue in overweight and obese men with insomnia symptoms
Objective To study whether diet and exercise intervention affect sleep and obesity-related genes’ DNA methylation in overweight and obese men with insomnia symptoms
Methods The study participants were a subgroup of a large intervention and consisted of 10 overweight or obesity men aged 34-65 years with insomnia symptoms. They participated in a 6-month progressive aerobic exercise training and individualized dietary consoling program and were randomly selected from diet (n=4), exercise (n=3) and control (n=3) groups. Body composition included fat mass and lean mass in the whole body and abdominal android region were assessed by dual-energy X-ray densitometry. The fitness level (VO2max) was determined by 2-km walk test using a standard protocol. Blood samples from venous were taken at fasted state in the morning. Total cholesterol, high density lipid cholesterol, low density lipid cholesterol, triglycerides, glucose, insulin, non-esterified fatty acid, alanine aminotransferase, aspartate aminotransferase and γ-glutamyltransferase were assessed by conventional methods. Subcutaneous adipose tissue was taken from abdominal region before and after the intervention. DNA was extracted from subcutaneous adipose tissue using a QIAamp DNeasy Tissue Kit. Whole genome-wide DNA methylation was obtained using MethylRAD-Seq. MethylRAD library preparation started from DNA digestion by FspEI, then digested products were run on agarose gel to verify digestion and DNA ligase was added to the digestion solution. After ligation products amplication, PCR was conducted by MyCycler thermal cycler (Bio-Rad). The target fragment was excised from polyacrylamide gel and DNA was diffused from the gel in nuclease-free water. For relative quantification of MethylRAD data, DNA methylation levels were determined using the normalized read depth (reads per million, RPM) for each site. For each restriction site, its methylation level was estimated by dividing the log-transformed depth of each site by the log-transformed maximum depth (representing 100% methylation; i.e. M-index ¼ log(depth site)/ log(depth max)), where depth max was summarized from the top 2% of sites (approx. 500 for the standard library) with the highest sequencing coverage. Heat map images are generated with Matlab 7.0 software and pathways are analysed by WEB-based Gene SeT AnaLysis Toolket. A statistical significance for methylated CpGs and pathways were set to p=0.001 and p=0.05, respectively.
Results No significant group differences by time were found in sleep-related variables, body composition, lifestyle factors nor with measured lipid and glucose biomarkers. However, whole genome-wide DNA methylation was decreased after dietary intervention, but was increased after exercise intervention, respectively. Correspondingly, 1253 and 708 differentially methylated loci were found in diet and exercise groups by contrast to the control group. Among them, the overlap genes between diet and exercise had multiple differentially methylated CpGs, including e.g. MYT1L (4 CpGs), CAMTA1 (3 CpGs), NRXN1 (3 CpGs), RPS6KA2 (3 CpGs), SEMA4D (3 CpGs). DNA methylation in PCDH8 was negatively correlated with wake after sleep onset after exercise intervention and MYRIP associated with sleep duration showed lower methylation after the dietary intervention. Further, 13 (DIO1, GCK, GYS1,
LMNA, LY86, PNMT, PPARA, PPARD, SERPINE1, TH, TMEM18, TNFRSF1B and UBL5) and 2 (SDCCAG8 and TNF) obesity-related genes’ DNA methylation profile changed in response to diet and exercise, respectively. Percentage changes of CpGs within KLHDC8A, ANKS1A, FGFRL1 and KDM3B were correlated with energy yield fat and carbohydrate, HOMA-IR and VO2max, respectively.
Conclusions We found that both exercise and dietary interventions have impacts on these genes related to sleep indicating by DNA methylation in PCDH8 and MYRIP, respectively. Further diet may be more effective than aerobic exercise intervention since greater number of modified obesity-related genes observed after dietary intervention. Our results indicate that reduce insomnia symptoms may need to more focus on control obesity.