目的 探索多基因风险评分(PRS)与儿童肥胖干预效果可持续性的关联,为未来开展基于遗传背景、可持续、个性化的儿童肥胖干预提供科学依据。方法 从一项研究儿童干预效果的整群随机对照试验(2018年9月—2021年4月)中,选取北京地区148名基线时处于超重肥胖的儿童作为研究对象,采集唾液进行全基因组测序。构建4个PRS:加权和未加权PRS69,加权和未加权PRS67。分析PRS与干预组别对干预效果可持续性(干预结束到最后一次随访期间肥胖相关指标变化)的交互作用。结果 PRS与干预组别对干预结束后儿童校正体质量指数(BMI)的腰围、校正BMI的腰臀比和收缩压的反弹程度存在交互作用。与对照组相比,干预组儿童加权PRS69每增加一个单位(1个s),校正BMI的腰围(β=0.34,95%CI: 0.05～0.63,P=0.020)和校正BMI的腰臀比(β=0.29,95%CI: 0.03～0.56, P=0.031)在干预结束后反弹得越多;加权PRS67和未加权PRS67每增加一个单位(1个s),收缩压在干预结束后反弹得越多(β=3.58,95%CI: 0.50～6.66, P=0.023;β=3.75,95%CI: 0.78～6.71,P=0.014)。结论 超重肥胖儿童PRS越高(携带风险等位基因越多),其在干预结束后的校正BMI的腰围、校正BMI的腰臀比和收缩压越容易反弹。未来应在干预结束后重点关注这些高危儿童的饮食和运动行为,预防和控制发生肥胖反弹。
Abstract
Objective To explore the relationship between polygenic risk score (PRS) and the sustainability of childhood obesity intervention, in order to provide scientific basis for future sustainable and personalized childhood obesity intervention based on genetic background. Methods A total of 148 children with overweight/obesity at baseline were selected as study subjects from a cluster randomized controlled trial (September 2018 to April 2021) regarding the effect of a childhood obesity intervention in Beijing, China. Saliva was collected to detect the whole genome sequencing. Four PRSs were built: weighted and unweighted PRS69, weighted and unweighted PRS67. The interactions between PRS and study arms on the sustainability of intervention effect (the changes in obesity-related indicators between the end of the intervention and the last follow-up) were analyzed. Results There were interactions between PRS and study arms on the rebound degree of waist circumference adjusted for body mass index (BMI), waist-to-hip ratio adjusted for BMI, and systolic blood pressure after the intervention. Compared with the control group, children in the intervention group carried each additional unit (standard deviation) of weighted PRS69, the waist circumference adjusted for BMI rebounded more by 0.34 (95%CI: 0.05 - 0.63, P=0.020), and waist-to-hip ratio adjusted for BMI rebounded more by 0.29 (95%CI: 0.03 - 0.56, P=0.031) at the last follow-up survey. When children in the intervention group carried each additional unit (standard deviation) of weighted PRS67 and unweighted PRS67, systolic blood pressure at the last follow-up survey rebounded more by 3.58 (95%CI:0.50 - 6.66, P=0.023) and 3.75 (95%CI: 0.78 - 6.71, P=0.014), respectively. Conclusions The higher PRS (the more risk alleles) children with overweight/obesity carried, their waist circumference, waist-to-hip ratio and systolic blood pressure are more likely to rebound after the intervention. Findings from this study suggest that future studies should focus more on these high-risk children after the intervention to prevent and control obesity rebound.
关键词
儿童肥胖 /
多基因风险评分 /
干预效果 /
可持续性
Key words
childhood obesity /
polygenic risk score /
intervention effect /
sustainability
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参考文献
[1] Bendor CD, Bardugo A, Pinhas-Hamiel O, et al. Cardiovascular morbidity, diabetes and cancer risk among children and adolescents with severe obesity[J]. Cardiovasc Diabetol,2020,19(1):79.
[2] Tsiros MD, Tian EJ, Shultz SP, et al. Obesity, the new childhood disability? An umbrella review on the association between adiposity and physical function[J]. Obes Rev,2020,21(12):e13121.
[3] Blanco M, Solano S, Alcántara AI, et al. Psychological well-being and weight-related teasing in childhood obesity: A case-control study[J]. Eat Weight Disord,2020,25(3):751-759.
[4] Quek YH, Tam WWS, Zhang MWB,et al. Exploring the association between childhood and adolescent obesity and depression:A Meta-analysis[J]. Obes Rev,2017,18(7):742-754.
[5] Geng T, Smith CE, Li C,et al. Childhood BMI and adult type 2 diabetes, coronary artery diseases, chronic kidney disease, and cardiometabolic traits: A mendelian randomization analysis[J]. Diabetes Care,2018,41(5):1089-1096.
[6] Bleich SN, Vercammen KA, Zatz LY,et al. Interventions to prevent global childhood overweight and obesity:A systematic review[J]. Lancet Diabetes Endocrinol,2018,6(4):332-346.
[7] Feng L, Wei DM, Lin ST, et al. Systematic review and meta-analysis of school-based obesity interventions in mainland China[J]. PLoS One,2017,12(9):e0184704.
[8] Liu Z, Xu HM, Wen LM, et al. A systematic review and meta-analysis of the overall effects of school-based obesity prevention interventions and effect differences by intervention components[J]. Int J Behav Nutr Phys Act,2019,16(1):95.
[9] Weihrauch-Blüher S, Kromeyer-Hauschild K, Graf C, et al. Current guidelines for obesity prevention in childhood and adolescence[J].Obes Facts,2018,11(3):263-276.
[10] Hall KD, Kahan S. Maintenance of lost weight and long-term management of obesity[J]. Med Clin North Am,2018,102(1):183-197.
[11] Nordmo M, Danielsen YS, Nordmo M. The challenge of keeping it off, a descriptive systematic review of high-quality, follow-up studies of obesity treatments[J]. Obes Rev,2020,21(1):e12949.
[12] Severin R, Sabbahi A, Mahmoud AM, et al. Precision medicine in weight loss and healthy living[J]. Prog Cardiovasc Dis,2019,62(1):15-20.
[13] Xiao WC, Chen J, Liu Z. The role of genetic variants in childhood obesity interventions: A systematic review and Meta-analysis[EB/OL]. Prospero,2022,CRD42022312177 Available from:https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022312177.
[14] Liu Z, Gao P, Gao AY, et al. Effectiveness of a multifaceted intervention forprevention of obesity in primary school children in China: A cluster randomized clinical trial[J]. JAMA Pediatr,2022,176(1):e214375.
[15] 中华人民共和国国家卫生健康委员会.WS/T 586-2018, 学龄儿童青少年超重与肥胖筛查[S]. 北京: 2018.
[16] Marees AT, de Kluiver H, Stringer S, et al. A tutorial on conductinggenome-wide association studies: Quality control and statistical analysis[J]. Int J Methods Psychiatr Res,2018,27(2):e1608.
[17] Howie B, Marchini J, Stephens M. Genotype imputation with thousands ofgenomes[J]. G3 (Bethesda),2011,1(6):457-470.
[18] Pulit SL, Stoneman C, Morris AP, et al. Meta-analysis of genome-wideassociation studies for body fat distribution in 694 649 individuals of European ancestry[J]. Hum Mol Genet,2019,28(1):166-174.
[19] Locke AE, Kahali B, Berndt SI, et al. Genetic studies of body mass index yieldnew insights for obesity biology[J]. Nature,2015,518(7538):197-206.
[20] Reinehr T, Hebebrand J, Friedel S, et al. Lifestyle intervention in obese childrenwith variations in the melanocortin 4 receptor gene[J].Obesity (Silver Spring),2009,17(2):382-389.
[21] Reinehr T, Wolters B, Roth CL, et al. FTO gene: Association to weight regainafter lifestyle intervention in overweight children[J].Horm Res Paediatr,2014,81(6):391-396.
[22] Cecil JE, Tavendale R, Watt P,et al. An obesity-associated FTO gene variant andincreased energy intake in children[J]. N Engl J Med,2008,359(24):2558-2566.
[23] Brunkwall L, Ericson U, Hellstrand S, et al. Genetic variation in the fat mass andobesity-associated gene (FTO) in association with food preferences in healthy adults[J]. Food Nutr Res,2013,57.
[24] Melhorn SJ, Askren MK, Chung WK, et al. FTO genotype impacts food intake and corticolimbic activation[J]. Am J Clin Nutr,2018,107(2):145-154.
[25] Yeo GS, Heisler LK. Unraveling the brain regulation of appetite: Lessons from genetics[J].Nat Neurosci,2012,15(10):1343-1349.
[26] de Lauzon-Guillain B, Clifton EAD, Day FR, et al. Mediation and modification of genetic susceptibility to obesity by eating behaviors[J]. Am J Clin Nutr,2017,106(4):996-1004.
[27] Szalanczy AM, Key CC, Solberg Woods LC. Genetic variation in satiety signaling and hypothalamic inflammation: Merging fields for the study of obesity[J]. J Nutr Biochem,2022,101:108928.
基金
国家自然科学基金项目(82373694,81903343);北京市教育科学“十四五”规划课题(BECA23111)
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