孟璐,高文静,曹卫华,吕筠,余灿清,吴涛,王胜锋,逄增昌,俞敏,汪华,吴先萍,董忠,吴凡,江国虹,王晓节,陆林,李立明.利用结构方程模型计算成年双生子饮酒遗传度的研究[J].Chinese journal of Epidemiology,2020,41(6):819-823 |
利用结构方程模型计算成年双生子饮酒遗传度的研究 |
Heritability of alcohol intake among adult twins, calculate by the structural equation model |
Received:January 03, 2020 |
DOI:10.3760/cma.j.cn112338-20200103-00007 |
KeyWord: 双生子研究 遗传 环境 饮酒 |
English Key Word: Twin study Heredity Environment Drinking |
FundProject:公益性行业科研专项(201502006,201002007);国家自然科学基金(81573223,81973126) |
Author Name | Affiliation | E-mail | Meng Lu | Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China | | Gao Wenjing | Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China | pkuepigwj@126.com | Cao Weihua | Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China | | Lyu Jun | Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China | | Yu Canqing | Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China | | Wu Tao | Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China | | Wang Shengfeng | Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China | | Pang Zengchang | Qingdao Center for Disease Control and Prevention, Qingdao 266033, China | | Yu Min | Zhejiang Center for Disease Control and Prevention, Hangzhou 310051, China | | Wang Hua | Jiangsu Center for Disease Control and Prevention, Nanjing 210009, China | | Wu Xianping | Sichuan Center for Disease Control and Prevention, Chengdu 610041, China | | Dong Zhong | Beijing Center for Diseases Prevention and Control, Beijing 100013, China | | Wu Fan | Shanghai Municipal Center for Disease Control&Prevention, Shanghai 200336, China | | Jiang Guohong | Tianjin Centers for Diseases Control and Prevention, Tianjin 300011, China | | Wang Xiaojie | Qinghai Center for Disease Prevention and Control, Xining 810007, China | | Lu Lin | Yunnan Center for Disease Control and Prevention, Kunming 650034, China | | Li Liming | Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China | |
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Abstract: |
目的 分析遗传和环境因素对饮酒的影响。方法 对2015-2018年中国双生子登记系统募集的9 231对成年同性别双生子,利用结构方程模型对饮酒相关变量进行拟合,估计遗传因素和环境因素对其的影响。结果 共纳入9 231对双生子进行分析,其中同卵双生子6 085对。同卵双生子年龄(36.91±13.07)岁,男性占56.80%;异卵双生子年龄(35.22±12.48)岁,男性占55.91%。双生子高风险饮酒者共350人,占1.90%,中风险饮酒者共367人,占1.99%。中风险饮酒受加性遗传、双生子共享环境及各自环境的影响,遗传度为24.3%(95% CI:0~56.8%),共享环境可解释50.7%(95% CI:20.4%~79.0%),特殊环境可解释24.9%(95% CI:18.3%~36.5%)。而高风险饮酒则主要受双生子共享环境及各自特殊环境的影响,共享环境可解释75.6%(95% CI:69.6%~80.8%),特殊环境可解释24.4%(95% CI:19.2%~30.4%)。中高风险饮酒的遗传度具有一定的性别差异,男性中遗传度为30.8%(95% CI:9.8%~53.5%),在女性中则主要受到环境的影响。结论 中高风险饮酒行为主要受环境影响,有一定的性别差异,且随着饮酒量的增加,环境对于饮酒行为的影响作用更趋显著。 |
English Abstract: |
Objective To explore the genetic and environmental effects on alcohol intake. Methods Data on 9 231 pairs of adult twins of the same sex was collected from the Chinese National Twin Registry (CNTR), between 2015 and 2018 and used in this study. Structural equation model was used to estimate the effects of genetic and environmental factors on alcohol intake. Results A total of 9 231 pairs of twins were included in the analysis, of which 6 085 pairs were monozygotic (MZ). The average age of MZ was (36.91±13.07) years old, and males accounted for 56.80%. The average age of dizygotic twins (DZ) was (35.22±12.48) years old, and males accounted for 55.91%. There were 350 pairs of alcohol-drinking twins were with high-risk, accounting for 1.90% and another 367 pairs (1.99%) were with medium-risk. Alcohol-drinkers with medium-risk were affected by additive genetics, common and unique environmental factors, seen among the twins. The overall heritability appeared as 24.3% (95%CI: 0 to 56.8%). Furthermore, 50.7% of the variation (95%CI: 20.4%-79.0%) could be explained by the common environmental factors and 24.9% (95%CI: 18.3%-36.5%) by unique environmental factors. High-risk related drinking behavior was affected by both common and unique environmental factors. The common environmental component appeared as 75.6% (95%CI: 69.6%-80.8%) and unique environmental component as 24.4% (95%CI: 19.2%-30.4%), respectively. Gender difference was seen in the heritability of those with medium or high-risk drinking behaviors. The heritability of men was 30.8% (95%CI: 9.8%-53.5%), while in women it was mainly affected by the environment. Conclusion Both alcohol drinkers with medium and high-risk drinking behaviors were mainly affected by the environment factors and gender. With the increase of drinking volume, the effect of environment on drinking behaviors became more obvious. |
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