中华流行病学杂志  2023, Vol. 44 Issue (3): 511-515   PDF    
http://dx.doi.org/10.3760/cma.j.cn112338-20220507-00390
中华医学会主办。
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文章信息

刘博蕊, 胡嘉晋, 万宁钰, 于洋, 刘洋, 马亚楠, 闻德亮.
Liu Borui, Hu Jiajin, Wan Ningyu, Yu Yang, Liu Yang, Ma Yanan, Wen Deliang
基于基因与环境交互作用的儿童肥胖病因研究进展
Progress in research of etiology of childhood obesity based on interaction between genes and environment
中华流行病学杂志, 2023, 44(3): 511-515
Chinese Journal of Epidemiology, 2023, 44(3): 511-515
http://dx.doi.org/10.3760/cma.j.cn112338-20220507-00390

文章历史

收稿日期: 2022-05-07
基于基因与环境交互作用的儿童肥胖病因研究进展
刘博蕊1 , 胡嘉晋1 , 万宁钰1 , 于洋1 , 刘洋1 , 马亚楠2 , 闻德亮1     
1. 辽宁省肥胖与糖脂代谢性疾病重点实验室/中国医科大学健康科学研究院, 沈阳 110122;
2. 中国医科大学公共卫生学院, 沈阳 110122
摘要: 儿童肥胖是全球性的公共健康问题,不仅危害儿童自身健康,还是成年期慢性病发病的重要诱因。近年来,随着精准医学研究的深入开展,越来越多的研究证据指明环境、行为因素,如早期宫内环境、儿童饮食、体力活动等,与儿童自身基因风险对肥胖的发病具有显著的交互作用,可以促进或抑制儿童肥胖的发生发展。本文对该领域现有研究进行综述,总结基因风险和环境暴露因素对儿童肥胖发病的交互作用及潜在机制,为不同遗传背景儿童的肥胖精准防控提供参考依据。
关键词: 儿童肥胖    基因与环境交互作用    宫内暴露    膳食    体力活动    表观遗传    
Progress in research of etiology of childhood obesity based on interaction between genes and environment
Liu Borui1 , Hu Jiajin1 , Wan Ningyu1 , Yu Yang1 , Liu Yang1 , Ma Yanan2 , Wen Deliang1     
1. Key Laboratory of Obesity and Glucose, Lipid Associated Metabolic Diseases of Liaoning Province/Health Sciences Institute, China Medical University, Shenyang 110122, China;
2. School of Public Health, China Medical University, Shenyang 110122, China
Abstract: Childhood obesity is a global public health problem, which can not only endangers children's health, but also might be an important cause of chronic diseases in adulthood. In recent years, with the in-depth development of precision medicine research, more and more research evidences have shown that there are interactions between environmental factors, such as early intrauterine environment, children's diet, physical activity and children's gene factor on the incidence of childhood obesity, which can result in or inhibit the incidence and development of childhood obesity. This paper summarizes the progress in research in this field to reveal the effects and potential mechanisms of genetic factors and environmental factors on the incidence of childhood obesity in order to provide reference for the precise prevention and control of childhood obesity under different genetic backgrounds.
Key words: Childhood obesity    Interaction between genes and environment    Intrauterine exposure    Diet    Physical activity    Epigenetic    

进入21世纪以来,儿童肥胖已经成为世界范围内的重大公共健康问题。近年来,我国儿童肥胖流行率快速上升。2019年,我国 < 6岁儿童的超重和肥胖率分别为6.8%和3.6%,6~17岁儿童青少年的超重和肥胖率分别达到11.1%和7.9%[1]。儿童肥胖不仅影响儿童身心健康,还可能导致成年期心血管疾病、糖尿病、癌症等慢性病的发生[2-4]。既往研究在儿童肥胖病因的遗传维度及包含儿童行为在内的环境暴露维度进行了探索[5-8]。然而,儿童肥胖的发生发展是遗传因素与环境暴露因素共同作用的结果[9]。近年来,随着精准医学的发展,国内外学者开始探究不同基因背景下环境暴露因素对儿童肥胖发病的特异性作用,例如饮食因素对携带不同基因如FTOPPARG2、瘦素(Leptin)的儿童肥胖发病特异性影响等[10-12]。这些研究对揭示基因与环境对儿童肥胖的交互作用做了先期探索,然而,目前该领域研究证据尚不充分,结论尚不一致。本文对现有相关研究证据进行综述,为不同遗传背景下儿童肥胖的精准防控提供参考依据。

一、儿童肥胖相关基因概况

依托大型队列研究和全基因组关联研究(genome-wide association study,GWAS),国内外研究学者对肥胖相关基因进行了探索。肥胖相关基因广泛参与人体能量摄入与消耗如Leptin基因、MCR基因、POMC基因、瘦素受体基因、神经肽Y基因、解偶联蛋白系列基因和β3-肾上腺素能受体基因等[13]。肥胖相关基因还通过参与机体脂肪的合成与代谢作用于肥胖的发病,如过氧化物酶体增殖物激活受体γ(PPARγ)基因主要参与脂肪细胞的分化;FTO基因主要参与脂肪前体细胞的增殖等。

目前,针对儿童群体的肥胖相关基因GWAS尚有限。国外一项GWAS发现了与儿童肥胖相关的19个单核苷酸多态性(SNP)位点(METTL15 rs10835310、SEC16B rs539515、BDNF rs17309874、TNNI3K rs10493544、ADCY3 rs4077678等)[14]。Costa-Urrutia等[15]针对墨西哥儿童的研究结果显示11个SNP位点(SEC16B rs543874、OLFM4 rs12429545、FTO rs9939609、MC4R rs6567160、GNPDA2 rs13130484等)与儿童的BMI显著相关;7个SNP位点(SEC16B rs543874、OLFM4 rs12429545、FTO rs9939609、MC4R rs6567160、GNPDA23 rs1330484等)与儿童肥胖相关。国内学者针对中国儿童相关易感性基因位点也进行了探索。Fang等[16]报道了11个SNP位点(ADCY3 rs11676272、FAIM2 rs7132908、ELP3 rs13253111、RAB27B rs8092503、TMEM18 rs4854349等)与儿童肥胖发病风险相关;Zhao等[17]报道了11个SNP位点(FTO rs9939609、MC4R rs17782313、GNPDA2 rs10938397、BDNF rs6265、FAIM2 rs7138803等)与儿童代谢综合征发病风险显著相关;Song等[18]报道了FAM3C基因rs7776725和rs7793554位点与血脂异常和脂质特征显著关联;Wang等[19]报道了HIF3A基因rs46801642和rs46801699位点与儿童肥胖或BMI相关。

二、宫内环境暴露与子代风险基因对儿童肥胖的交互作用

都哈理论指出,宫内不良环境暴露是子代肥胖发病的重要诱因。胎儿期是代谢器官和代谢功能发育的关键时期[20],也是表观遗传修饰活跃的时期,因此该时期代谢功能发育更容易受到环境因素的影响。探究宫内环境暴露因素对不同基因型子代肥胖发病的特异性作用,对于在生命早期阶段采取针对性的肥胖防控措施具有重要的意义。

1. 孕期增重与子代风险基因对儿童肥胖的交互作用:孕期增重反映了母亲孕期的营养状态,也反映了胎儿宫内的营养供给情况。孕期过度增重是儿童肥胖发病的独立危险因素[21]。母亲孕期过度增重可能导致胎儿DNA甲基化水平的改变,进而影响肥胖相关基因的表达水平。Shrestha等[22]在调整了母亲年龄、种族、儿童性别等因素后发现孕妇孕早期和孕中期体重增速每增加1 kg/周,子代MYT1L基因的甲基化水平分别增加24.32%和28.91%,MYT1L基因的高表达与肥胖发生有关[23]。然而在雅芳亲子纵向研究(ALSPAC)中,Sharp等[24]没有观察到孕期增重对子代肥胖相关基因甲基化的作用,该领域研究结论尚不一致。

2. 孕期血糖、血脂水平与子代风险基因对儿童肥胖的交互作用:母亲孕期血糖、血脂异常也是儿童肥胖发病的主要危险因素之一[25]。目前尚无直接研究证据证明母亲孕期血糖、血脂与子代肥胖基因对儿童肥胖的发病存在交互作用,但有研究提示母亲孕期血糖、血脂异常可以诱导子代表观遗传变化[26-27]。Côté等[28]在调整了胎龄、新生儿性别、出生体重、孕期吸烟情况、孕期增重等混杂因素后的模型中发现母体较高的血糖水平和胎盘PPARGC1α基因甲基化水平升高有关,胎盘PPARGC1α基因甲基化水平与胎儿脐血瘦素水平之间存在正相关关系。与非妊娠糖尿病母亲的子代相比,妊娠糖尿病母亲子代HNF4A基因内含子处CpG位点(cg08407434)的甲基化水平升高[29]HNF4A基因对调节儿童胰腺β细胞发育和分化具有重要作用,是2型糖尿病发病的致病基因。动物实验表明,孕期营养环境变化可以诱导子代HNF4A基因在胰岛细胞中表达水平的改变[30]。此外,对雌鼠孕期采用高脂饮食喂养后,可观察到胎盘中促炎基因和生长发育相关基因表达水平普遍发生了上调[31],提示孕期宫内高脂环境可能通过诱导子代代谢风险基因表达上调诱发儿童肥胖的发生。

三、饮食因素与风险基因对儿童肥胖的交互作用

饮食是影响儿童营养状态和肥胖发生的关键行为因素。GWAS中发现的肥胖相关基因大多与摄食中枢调节有关[32]。明确基因与饮食对儿童肥胖的交互作用,对不同肥胖基因型儿童采取特异性的饮食干预措施,将为儿童肥胖的精准防控提供新方向。

1. 母乳喂养与风险基因对儿童肥胖的交互作用:WHO提倡母乳喂养至儿童2周岁,以降低儿童超重肥胖的发病风险[33]。ALSPAC报道了纯母乳喂养对不同FTO基因型儿童的BMI轨迹及BMI峰值年龄起调节作用。对儿童采取5个月以上的纯母乳喂养可以降低FTO基因高风险表型(A等位基因)对儿童肥胖发病的风险[10]。另一项多基因研究发现,超过5个月的纯母乳喂养可以降低高肥胖遗传风险评分儿童在18岁时的BMI[34],其中男生平均可降低1.14 kg/m2,女生平均可降低1.53 kg/m2,其健康效益可抵消39%和70%的肥胖遗传风险。Verier等[11]报道母乳喂养和PPARG2基因多态性对儿童肥胖的发生具有显著的交互作用。在调整了年龄、性别等人口学混杂因素后发现,在携带PPARG2基因高风险表型Pro12Ala的儿童中,采取母乳喂养的儿童相比于采取人工喂养的儿童具有更低的BMI、腰围和皮褶厚度;而在PPARG2基因非高风险表型的儿童中,母乳喂养组儿童和人工喂养组儿童的肥胖相关指标无显著差异,提示母乳喂养对儿童肥胖的防控效益可能仅在特定遗传背景的儿童中存在。此外,有研究关注了母乳喂养与子代肥胖相关基因甲基化水平的关联,Obermann-Borst等[35]报道母乳喂养时间与17月龄儿童的Leptin基因甲基化水平呈显著负相关;Sherwood等[12]报道较长的母乳喂养时间与儿童10岁时Leptin基因甲基化水平降低有关,较长时间的母乳喂养促进了Leptin基因的高表达和血浆瘦素浓度的升高。

2. 儿童期饮食与风险基因对肥胖的交互作用:除母乳喂养外,儿童自身饮食也是儿童肥胖发病的重要危险因素。目前对于儿童期饮食与肥胖基因风险交互作用的研究多集中在饮食行为因素与FTOMC4R基因的交互作用。Wang等[36]研究发现MC4R基因临近位点rs12970134多态性与9~15岁超重肥胖儿童的食欲及饮料摄入量有关。Lv等[37]报道中国儿童青少年的SEC16BMC4RKCTD15基因多态性与高盐饮食对儿童肥胖存在交互作用。潜在的原因可能为SEC16BKCTD15MC4R基因高风险个体对高盐食物具有特殊偏好,提高了机体渗透压和体内水分潴留,降低了脂肪的分解代谢,进而导致儿童代谢异常和肥胖的发生。一项随机对照试验表明,与FTO基因型为AA的儿童相比,TT基因型肥胖儿童对饮食联合运动干预更为敏感,可通过膳食和有氧运动干预显著降低TC和LDL-C水平等[38]。Young等[39]报道了饮食评分与FTO基因多态性对儿童肥胖存在显著的交互作用,FTO基因对BMI的影响在高盐饮食的儿童中更加显著。

四、体力活动与风险基因对儿童肥胖的交互作用

体力活动缺乏是近年来儿童肥胖流行的重要诱因。体力活动除了可以直接消耗能量外,还可下调参与脂肪酸合成基因的表达水平并减少脂肪生成[40]。既往对基因与体力活动交互作用的研究主要关注了体育活动时间和久坐行为,研究结论尚不一致。部分研究报道体力活动与基因风险对儿童肥胖存在显著交互作用,如Song等[41]报道了在IRS1基因型为TC和CC的儿童中体育活动 < 1 h/d和久坐行为≥2 h/d显著升高儿童肥胖的发病风险(OR=3.41,95%CI:1.45~8.01,P=0.005),在IRS1基因型为TT的儿童中未观察到类似关联。运动可以上调IRS1基因表达,同时使磷脂酰肌醇-3激酶在骨骼肌中的表达增强,导致胰岛素介导的骨骼肌葡萄糖摄取增加,减少了葡萄糖向脂肪的转化。Song等[42]报道了身体活动和久坐行为与MC4R基因多态性交互作用于肥胖儿童的BMI,该研究根据儿童久坐行为和身体活动水平进行分层,在调整年龄和性别后发现儿童体力活动 < 1 h/d和久坐行为≥2 h/d仅在MC4R基因型为A(高风险表型)的儿童中引发BMI升高(BMI:β=1.27 kg/m2,95%CI:0.10~2.45,P=0.034),在低风险表型儿童中作用不显著。然而,Kilpeläinen等[43]对19 268名儿童和青少年的Meta分析报道,虽然FTO风险等位基因与儿童和青少年BMI显著相关,但这种相关性没有受到儿童身体活动水平的调节。这些研究对于体力活动的测量普遍通过儿童自我报告获得,后续研究应更多使用加速度计等客观测量手段对儿童的体力活动进行测量。

五、睡眠因素与风险基因对儿童肥胖的交互作用

睡眠与人体昼夜节律及内分泌功能息息相关,缺乏睡眠会引起下丘脑激素分泌改变,导致瘦素和胃饥饿素等急速地改变,进而降低饱腹感反应和引发肥胖[44]。目前关于儿童睡眠与基因交互作用的研究大多关注了儿童睡眠时间。在北京儿童青少年代谢综合征队列研究中,与瘦素水平相关的SNP位点(FTO rs1558902、MC4R rs2331841、MAP2K5 rs4776970、GNPDA2 rs16858082、PCSK1 rs261967和BDNF rs2030323)计算的基因风险评分(GPSleptin)与睡眠时间对儿童肥胖存在显著的交互作用[45]。调整儿童年龄、性别、饮食评分和体力活动等混杂因素后,儿童GPSleptin与睡眠时间的乘积项每增加一个单位,瘦素浓度水平降低0.031 ng/ml,BMI降低0.073 kg/m2。美国的一项双生子研究也发现,随着睡眠时间的增加,遗传因素对儿童BMI的影响逐渐减弱[46]。新西兰一项儿童队列研究报道,CLOCKPEMTGHRELIN基因多态性与睡眠时间交互作用于儿童的BMI Z。在CLOCK基因型为AA和PEMT基因型为GG的儿童中,增加睡眠时间有利于保持健康的体重状态[47]。Prats-Puig等[48]研究发现FTOTMEM18NRXN3基因的多态性与睡眠时间交互作用于儿童的肥胖相关指标如腰围、BMI等,在FTO基因型为TT、TMEM18基因型为TT或NRXN3基因型为GG的儿童中,睡眠时间减少2 h将导致BMI Z增加一个标准差,腰围增加8.0 cm,而在FTO基因型为AA、TMEM18基因型为GG或NRXN3基因型为AA的儿童中未观察到类似的关联。这些研究表明睡眠时间对不同遗传背景儿童肥胖发病的作用存在显著差异。

六、基因与环境因素对儿童肥胖发病的交互作用机制

表观遗传修饰如DNA甲基化、非编码RNA调控和组蛋白修饰是目前揭示基因与环境交互作用于儿童肥胖发病机制的主要研究领域,其中DNA甲基化研究是目前该领域的主流研究方向。大量证据显示,不良的环境、行为暴露可以广泛影响儿童肥胖和代谢相关风险基因的甲基化水平,导致基因表达水平的改变,进而与基因风险发生协同或拮抗效应[49]。例如,母亲孕期的膳食可以改变胎儿脐带血中WNT5B基因(cg23757341)CpG岛的DNA甲基化水平,影响该基因的表达水平,进而影响儿童脂肪生成和胰岛素分泌[50]。国际孕期与儿童表观遗传工作组近期通过整合多个出生队列项目的甲基化研究数据,开展了孕期环境暴露致儿童基因甲基化的国际联合研究,对揭示儿童肥胖的基因与环境交互作用机制进行了重要探索[51]

MicroRNA(miRNA)作为一种非编码RNA分子,也可通过转录后抑制信使RNA(mRNA)翻译或引起mRNA降解来调节基因表达[52]。研究表明,miRNA可受外部环境因素的调节,并对环境因素做出响应[53]。例如母乳喂养可以通过miRNA-29b/miRNA-21信号通路促进FTO基因内含子1的CpG去甲基化,导致FTO基因表达水平提高[11]。国内针对男性肥胖青少年的一项研究发现,在进行6周的运动结合饮食干预后,miRNA-126水平显著增加[54]。动物实验也发现宫内危险因素如孕期过度增重可通过调控miRNA-126来影响后代的代谢信号通路,miRNA-126的程序性过表达导致儿童胰岛素抵抗,从而增加后代患肥胖和2型糖尿病的风险[55]

此外,组蛋白修饰也是基因与环境产生交互作用的潜在机制。同一组蛋白可能涉及多个化学基团的修饰,例如甲基化和乙酰化,从而激活或抑制基因表达。尽管目前尚无研究报道组蛋白修饰在肥胖儿童中的表观遗传修饰中的作用,动物实验提供了进一步研究的线索。例如在对小鼠进行高脂饮食喂养后,小鼠的基因启动子中H3K9 me2或H3K9 me3的水平降低[56],组蛋白修饰激活的一系列基因如MAP3K5METVEGFA也发生上调,KEGG富集分析结果涉及脂肪生成、能量代谢和炎症的相关通路。

目前,尽管大量流行病学研究证据提示肥胖相关基因与致肥环境对儿童肥胖的发生存在交互作用,但相关机制研究尚不深入,作用机制有待进一步明确。后续研究应以流行病学研究证据为线索,结合多组学技术和基础实验研究,深入探讨相关机制。

七、展望

综上所述,现有的研究证据提示肥胖的遗传易感性与致肥环境对儿童肥胖发病存在广泛的交互作用。不同遗传背景的儿童可能对不同的致肥危险因素敏感性不同。针对不同肥胖基因背景的儿童,通过采取特异性的精准干预措施,可以有效提高儿童肥胖干预的效益。然而目前该研究领域现有的流行病学研究和机制研究证据尚不充分,相关研究结论一致性仍有待进一步验证。此外,既有研究对肥胖基因位点的纳入不尽相同,这些基因大多是基于成年人GWAS中发现的BMI相关基因,未在儿童人群中进行相关验证。后续研究应基于儿童肥胖相关基因,通过大规模的队列研究全面探索不同环境暴露因素与儿童肥胖风险基因的交互作用,以进一步明确不同肥胖易感性儿童的特异性肥胖防控措施。

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参考文献
[1]
Pan XF, Wang LM, Pan A. Epidemiology and determinants of obesity in China[J]. Lancet Diabetes Endocrinol, 2021, 9(6): 373-392. DOI:10.1016/S2213-8587(21)00045-0
[2]
Zhang X, Shu XO, Gao YT, et al. Anthropometric predictors of coronary heart disease in Chinese women[J]. Int J Obes, 2004, 28(6): 734-740. DOI:10.1038/sj.ijo.0802634
[3]
Mi BB, Wu CL, Gao XY, et al. Long-term BMI change trajectories in Chinese adults and its association with the hazard of type 2 diabetes: evidence from a 20-year China Health and Nutrition Survey[J]. BMJ Open Diabetes Res Care, 2020, 8(1): e000879. DOI:10.1136/bmjdrc-2019-000879
[4]
Pang YJ, Kartsonaki C, Guo Y, et al. Adiposity and risks of colorectal and small intestine cancer in Chinese adults: a prospective study of 0.5 million people[J]. Br J Cancer, 2018, 119(2): 248-250. DOI:10.1038/s41416-018-0124-8
[5]
Serra-Juhé C, Martos-Moreno GÁ, de Pieri FB, et al. Heterozygous rare genetic variants in non-syndromic early-onset obesity[J]. Int J Obes (Lond), 2020, 44(4): 830-841. DOI:10.1038/s41366-019-0357-5
[6]
Saeed S, Arslan M, Manzoor J, et al. Genetic causes of severe childhood obesity: a remarkably high prevalence in an inbred population of Pakistan[J]. Diabetes, 2020, 69(7): 1424-1438. DOI:10.2337/db19-1238
[7]
Zhen SH, Ma YN, Zhao ZY, et al. Dietary pattern is associated with obesity in Chinese children and adolescents: data from China Health and Nutrition Survey (CHNS)[J]. Nutr J, 2018, 17(1): 68. DOI:10.1186/s12937-018-0372-8
[8]
Gaillard R, Durmuş B, Hofman A, et al. Risk factors and outcomes of maternal obesity and excessive weight gain during pregnancy[J]. Obesity (Silver Spring), 2013, 21(5): 1046-1055. DOI:10.1002/oby.20088
[9]
Reddon H, Guéant JL, Meyre D. The importance of gene-environment interactions in human obesity[J]. Clin Sci (Lond), 2016, 130(18): 1571-1597. DOI:10.1042/CS20160221
[10]
Wu YY, Lye S, Briollais L. The role of early life growth development, the FTO gene and exclusive breastfeeding on child BMI trajectories[J]. Int J Epidemiol, 2017, 46(5): 1512-1522. DOI:10.1093/ije/dyx081
[11]
Verier C, Meirhaeghe A, Bokor S, et al. Breast-feeding modulates the influence of the peroxisome proliferator-activated receptor-γ (PPARG2) Pro12Ala polymorphism on adiposity in adolescents: The Healthy Lifestyle in Europe by Nutrition in Adolescence (HELENA) cross-sectional study[J]. Diabetes Care, 2010, 33(1): 190-196. DOI:10.2337/dc09-1459
[12]
Sherwood WB, Bion V, Lockett GA, et al. Duration of breastfeeding is associated with leptin (LEP) DNA methylation profiles and BMI in 10-year-old children[J]. Clin Epigenet, 2019, 11(1): 128. DOI:10.1186/s13148-019-0727-9
[13]
Walley AJ, Asher JE, Froguel P. The genetic contribution to non-syndromic human obesity[J]. Nat Rev Genet, 2009, 10(7): 431-442. DOI:10.1038/nrg2594
[14]
Bradfield JP, Vogelezang S, Felix JF, et al. A trans-ancestral meta-analysis of genome-wide association studies reveals loci associated with childhood obesity[J]. Hum Mol Genet, 2019, 28(19): 3327-3338. DOI:10.1093/hmg/ddz1
[15]
Costa-Urrutia P, Abud C, Franco-Trecu V, et al. Effect of 15 BMI-associated polymorphisms, reported for Europeans, across ethnicities and degrees of Amerindian ancestry in Mexican children[J]. Int J Mol Sci, 2020, 21(2): 374. DOI:10.3390/ijms21020374
[16]
Fang J, Gong C, Wan YH, et al. Polygenic risk, adherence to a healthy lifestyle, and childhood obesity[J]. Pediatr Obes, 2019, 14(4): e12489. DOI:10.1111/ijpo.12489
[17]
Zhao XY, Xi B, Shen Y, et al. An obesity genetic risk score is associated with metabolic syndrome in Chinese children[J]. Gene, 2014, 535(2): 299-302. DOI:10.1016/j.gene.2013.11.006
[18]
Song QY, Song JY, Li CX, et al. Genetic variants in the FAM3C gene are associated with lipid traits in Chinese children[J]. Pediatr Res, 2021, 89(3): 673-678. DOI:10.1038/s41390-020-0897-3
[19]
Wang S, Song JY, Yang YD, et al. HIF3A DNA methylation is associated with childhood obesity and ALT[J]. PLoS One, 2015, 10(12): e0145944. DOI:10.1371/journal.pone.0145944
[20]
Kwon EJ, Kim YJ. What is fetal programming?: a lifetime health is under the control of in utero health[J]. Obstet Gynecol Sci, 2017, 60(6): 506-519. DOI:10.5468/ogs.2017.60.6.506
[21]
Bider-Canfield Z, Martinez MP, Wang X, et al. Maternal obesity, gestational diabetes, breastfeeding and childhood overweight at age 2 years[J]. Pediatr Obes, 2017, 12(2): 171-178. DOI:10.1111/ijpo.12125
[22]
Shrestha D, Ouidir M, Workalemahu T, et al. Placental DNA methylation changes associated with maternal prepregnancy BMI and gestational weight gain[J]. Int J Obes (Lond), 2020, 44(6): 1406-1416. DOI:10.1038/s41366-020-0546-2
[23]
Blanchet P, Bebin M, Bruet S, et al. MYT1L mutations cause intellectual disability and variable obesity by dysregulating gene expression and development of the neuroendocrine hypothalamus[J]. PLoS Genet, 2017, 13(8): e1006957. DOI:10.1371/journal.pgen.1006957
[24]
Sharp GC, Lawlor DA, Richmond RC, et al. Maternal pre-pregnancy BMI and gestational weight gain, offspring DNA methylation and later offspring adiposity: findings from the Avon Longitudinal Study of Parents and Children[J]. Int J Epidemiol, 2015, 44(4): 1288-1304. DOI:10.1093/ije/dyv042
[25]
Yang IV, Zhang W, Davidson EJ, et al. Epigenetic marks of in utero exposure to gestational diabetes and childhood adiposity outcomes: the EPOCH study[J]. Diabet Med, 2018, 35(5): 612-620. DOI:10.1111/dme.13604
[26]
Howe CG, Cox B, Fore R, et al. Maternal gestational diabetes mellitus and newborn DNA methylation: findings from the pregnancy and childhood epigenetics consortium[J]. Diabetes Care, 2020, 43(1): 98-105. DOI:10.2337/dc19-0524
[27]
Kazmi N, Sharp GC, Reese SE, et al. Hypertensive disorders of pregnancy and DNA methylation in newborns[J]. Hypertension, 2019, 74(2): 375-383. DOI:10.1161/HYPERTENSIO.NAHA.119.12634
[28]
Côté S, Gagné-Ouellet V, Guay SP, et al. PPARGC1α gene DNA methylation variations in human placenta mediate the link between maternal hyperglycemia and leptin levels in newborns[J]. Clin Epigenet, 2016, 8: 72. DOI:10.1186/s13148-016-0239-9
[29]
Kim E, Kwak SH, Chung HR, et al. DNA methylation profiles in sibling pairs discordant for intrauterine exposure to maternal gestational diabetes[J]. Epigenetics, 2017, 12(10): 825-832. DOI:10.1080/15592294.2017.1370172
[30]
Sandovici I, Smith NH, Nitert MD, et al. Maternal diet and aging alter the epigenetic control of a promoter-enhancer interaction at the Hnf4a gene in rat pancreatic islets[J]. Proc Natl Acad Sci USA, 2011, 108(13): 5449-5454. DOI:10.1073/pnas.1019007108
[31]
Nitert MD, Vaswani K, Hum M, et al. Maternal high-fat diet alters expression of pathways of growth, blood supply and arachidonic acid in rat placenta[J]. J Nutr Sci, 2013, 2: e41. DOI:10.1017/jns.2013.36
[32]
Day FR, Loos RJF. Developments in obesity genetics in the era of genome-wide association studies[J]. J Nutrigenet Nutrigenomics, 2011, 4(4): 222-238. DOI:10.1159/000332158
[33]
Robinson SM. Infant nutrition and lifelong health: current perspectives and future challenges[J]. J Dev Orig Health Dis, 2015, 6(5): 384-389. DOI:10.1017/S2040174415001257
[34]
Wu YY, Lye S, Dennis CL, et al. Exclusive breastfeeding can attenuate body-mass-index increase among genetically susceptible children: A longitudinal study from the ALSPAC cohort[J]. PLoS Genet, 2020, 16(6): e1008790. DOI:10.1371/journal.pgen.1008790
[35]
Obermann-Borst SA, Eilers PHC, Tobi EW, et al. Duration of breastfeeding and gender are associated with methylation of the LEPTIN gene in very young children[J]. Pediatr Res, 2013, 74(3): 344-349. DOI:10.1038/pr.2013.95
[36]
Wang S, Song J, Yang Y, et al. Rs12970134 near MC4R is associated with appetite and beverage intake in overweight and obese children: A family-based association study in Chinese population[J]. PLoS One, 2017, 12(5): e0177983. DOI:10.1371/journal.pone.0177983
[37]
Lv D, Zhang DD, Wang H, et al. Genetic variations in SEC16B, MC4R, MAP2K5 and KCTD15 were associated with childhood obesity and interacted with dietary behaviors in Chinese school-age population[J]. Gene, 2015, 560(2): 149-155. DOI:10.1016/j.gene.2015.01.054
[38]
Zou ZC, Mao LJ, Shi YY, et al. Effect of exercise combined with dietary intervention on obese children and adolescents associated with the FTO rs9939609 polymorphism[J]. Eur Rev Med Pharmacol Sci, 2015, 19(23): 4569-4575.
[39]
Young AI, Wauthier F, Donnelly P. Multiple novel gene-by-environment interactions modify the effect of FTO variants on body mass index[J]. Nat Commun, 2016, 7: 12724. DOI:10.1038/ncomms12724
[40]
Li X, Qi L. Gene-environment interactions on body fat distribution[J]. Int J Mol Sci, 2019, 20(15): 3690. DOI:10.3390/ijms20153690
[41]
Song QY, Song JY, Li CX, et al. Physical activity attenuates the association between the IRS1 genotype and childhood obesity in Chinese children[J]. Nutr Metab Cardiovasc Dis, 2019, 29(8): 793-801. DOI:10.1016/j.numecd.2019.05.058
[42]
Song JY, Song QY, Wang S, et al. Physical activity and sedentary behaviors modify the association between Melanocortin 4 receptor gene variant and obesity in Chinese children and adolescents[J]. PLoS One, 2017, 12(1): e0170062. DOI:10.1371/journal.pone.0170062
[43]
Kilpeläinen TO, Qi L, Brage S, et al. Physical activity attenuates the influence of FTO variants on obesity risk: a meta-analysis of 218, 166 adults and 19, 268 children[J]. PLoS Med, 2011, 8(11): e1001116. DOI:10.1371/journal.pmed.1001116
[44]
Hayes AL, Xu F, Babineau D, et al. Sleep duration and circulating adipokine levels[J]. Sleep, 2011, 34(2): 147-152. DOI:10.1093/sleep/34.2.147
[45]
Fu JL, Wang YH, Li G, et al. Childhood sleep duration modifies the polygenic risk for obesity in youth through leptin pathway: the Beijing Child and Adolescent Metabolic Syndrome cohort study[J]. Int J Obes (Lond), 2019, 43(8): 1556-1567. DOI:10.1038/s41366-019-0405-1
[46]
Watson NF, Harden KP, Buchwald D, et al. Sleep duration and body mass index in twins: a gene-environment interaction[J]. Sleep, 2012, 35(5): 597-603. DOI:10.5665/sleep.1810
[47]
Krishnan M, Shelling AN, Wall CR, et al. Gene-by- environment interactions of the CLOCK, PEMT, and GHRELIN loci with average sleep duration in relation to obesity traits using a cohort of 643 New Zealand European children[J]. Sleep Med, 2017, 37: 19-26. DOI:10.1016/j.sleep.2017.05.017
[48]
Prats-Puig A, Grau-Cabrera P, Riera-Pérez E, et al. Variations in the obesity genes FTO, TMEM18 and NRXN3 influence the vulnerability of children to weight gain induced by short sleep duration[J]. Int J Obes (Lond), 2013, 37(2): 182-187. DOI:10.1038/ijo.2012.27
[49]
Barbosa P, Landes RD, Graw S, et al. Effect of excess weight and insulin resistance on DNA methylation in prepubertal children[J]. Sci Rep, 2022, 12(1): 8430. DOI:10.1038/s41598-022-12325-y
[50]
Küpers LK, Fernández-Barrés S, Nounu A, et al. Maternal Mediterranean diet in pregnancy and newborn DNA methylation: a meta-analysis in the PACE Consortium[J]. Epigenetics, 2022, 2: 1-13. DOI:10.1080/15592294.2022.2038412
[51]
Felix JF, Joubert BR, Baccarelli AA, et al. Cohort profile: pregnancy and childhood epigenetics (PACE) consortium[J]. Int J Epidemiol, 2018, 47(1): 22-23u. DOI:10.1093/ije/dyx190
[52]
De Sousa MC, Gjorgjieva M, Dolicka D, et al. Deciphering miRNAs' Action through miRNA Editing[J]. Int J Mol Sci, 2019, 20(24): 6249. DOI:10.3390/ijms20246249
[53]
Fernandez-Twinn DS, Alfaradhi MZ, Martin-Gronert MS, et al. Downregulation of IRS-1 in adipose tissue of offspring of obese mice is programmed cell- autonomously through post-transcriptional mechanisms[J]. Mol Metab, 2014, 3(3): 325-333. DOI:10.1016/j.molmet.2014.01.007
[54]
Tang DH, Bai S, Li XL, et al. Improvement of microvascular endothelial dysfunction induced by exercise and diet is associated with microRNA-126 in obese adolescents[J]. Microvasc Res, 2019, 123: 86-91. DOI:10.1016/j.mvr.2018.10.009
[55]
De Almeida-Faria J, Duque-Guimarães DE, Ong TP, et al. Maternal obesity during pregnancy leads to adipose tissue ER stress in mice via miR-126-mediated reduction in Lunapark[J]. Diabetologia, 2021, 64(4): 890-902. DOI:10.1007/s00125-020-05357-4
[56]
Wang Z, Zhu M, Wang M, et al. Integrated multiomic analysis reveals the high-fat diet induced activation of the MAPK signaling and inflammation associated metabolic cascades via histone modification in adipose tissues[J]. Front Genet, 2021, 12: 650863. DOI:10.3389/fgene.2021.650863