Fu-Ying Tian1, Marie-France Hivert2, Xiaozhong Wen3, Chuanbo Xie4, Zhongzheng Niu5, Lijun Fan6, Matthew W Gillman7, Wei-Qing Chen8. 1. Department of Medical Statistics and Epidemiology, Guangzhou Key Laboratory of Environmental Pollution and Health Assessment, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China. Electronic address: tianfy@mail2.sysu.edu.cn. 2. Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, 401 Park Drive, Suite 401, Boston, MA, USA; Diabetes Center, Massachusetts General Hospital, 50 Staniford Street, Boston, MA, USA; Department of Medicine, Université de Sherbrooke, 3001 12th Avenue North, Sherbrooke, Québec, Canada; Centre de recherche du Centre Hospitalier Universitaire de Sherbrooke, 3001 12th Avenue North, Wing 9, Door 6, Sherbrooke, Québec, Canada. Electronic address: marie-france_hivert@harvardpilgrim.org. 3. Division of Behavioral Medicine, Department of Pediatrics, School of Medicine and Biomedical Sciences, State University of New York at Buffalo, Buffalo, NY, USA. Electronic address: xiaozhon@buffalo.edu. 4. Department of Cancer Prevention Research, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China. Electronic address: xiechb@sysucc.org.cn. 5. Department of Medical Statistics and Epidemiology, Guangzhou Key Laboratory of Environmental Pollution and Health Assessment, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China. Electronic address: zhongzhengniu@hotmail.com. 6. Department of Medical Statistics and Epidemiology, Guangzhou Key Laboratory of Environmental Pollution and Health Assessment, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China. Electronic address: China.keirafanlj@gmail.com. 7. Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, 401 Park Drive, Suite 401, Boston, MA, USA. Electronic address: matthew.gillman@nih.gov. 8. Department of Medical Statistics and Epidemiology, Guangzhou Key Laboratory of Environmental Pollution and Health Assessment, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China. Electronic address: chenwq@mail.sysu.edu.cn.
Abstract
INTRODUCTION: Very few study addressed the relationship between Aryl-hydrocarbon receptor repressor (AHRR) DNA methylation and low birth weight, especially in multiple tissues of mother-infant pairs. In this study, we aimed to investigate AHRR DNA methylation modification in cord blood, placenta and maternal blood between full term low birth weight (FT-LBW) and full term normal birth weight (FT-NBW) newborns. METHODS: We enrolled 90 FT-LBW and 90 FT-NBW mother-infant pairs, of which all placenta and cord blood samples were collected while 45 maternal blood samples of each group were collected. We measured AHRR DNA methylation (Chr5: 373013-373606) using Sequenom MassARRAY, and assessed associations between AHRR DNA methylation and FT-LBW using logistic regression adjusting for maternal age, education, family income, delivery mode, and passive smoking. RESULTS: FT-LBW babies had 3% lower methylation at Chr5: 373378 (CpG 13) in cord blood, and 4-9% higher methylation levels at Chr5: 373315, 373378, 373423, 373476 and 373490/373494 (CpG 10; 13; 15; 16; 17/18 respectively) in maternal blood, comparing with FT-NBW. The methylation of Chr5: 373378 (CpG 13) remained significant association with FT-LBW both in cord blood (OR = 0.90; 95% CI: 0.82, 0.98) and maternal blood (OR = 1.14; 95% CI: 1.04, 1.25) further adjusting for each other in the same model. We observed no significant difference at any CpG sites in placenta. DISCUSSION: AHRR DNA methylation of cord and maternal blood might be independently associated with FT-LBW in different ways.
INTRODUCTION: Very few study addressed the relationship between Aryl-hydrocarbon receptor repressor (AHRR) DNA methylation and low birth weight, especially in multiple tissues of mother-infant pairs. In this study, we aimed to investigate AHRR DNA methylation modification in cord blood, placenta and maternal blood between full term low birth weight (FT-LBW) and full term normal birth weight (FT-NBW) newborns. METHODS: We enrolled 90 FT-LBW and 90 FT-NBW mother-infant pairs, of which all placenta and cord blood samples were collected while 45 maternal blood samples of each group were collected. We measured AHRR DNA methylation (Chr5: 373013-373606) using Sequenom MassARRAY, and assessed associations between AHRR DNA methylation and FT-LBW using logistic regression adjusting for maternal age, education, family income, delivery mode, and passive smoking. RESULTS: FT-LBW babies had 3% lower methylation at Chr5: 373378 (CpG 13) in cord blood, and 4-9% higher methylation levels at Chr5: 373315, 373378, 373423, 373476 and 373490/373494 (CpG 10; 13; 15; 16; 17/18 respectively) in maternal blood, comparing with FT-NBW. The methylation of Chr5: 373378 (CpG 13) remained significant association with FT-LBW both in cord blood (OR = 0.90; 95% CI: 0.82, 0.98) and maternal blood (OR = 1.14; 95% CI: 1.04, 1.25) further adjusting for each other in the same model. We observed no significant difference at any CpG sites in placenta. DISCUSSION: AHRR DNA methylation of cord and maternal blood might be independently associated with FT-LBW in different ways.