Dong Feng Gu
Academy of Medical Sciences, United Kingdom
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Featured researches published by Dong Feng Gu.
Journal of Human Hypertension | 2006
Wei Huang; W Yang; Y Wang; Q Zhao; Dong Feng Gu; R Chen
Association study of angiotensin-converting enzyme 2 gene (ACE2) polymorphisms and essential hypertension in northern Han Chinese
Journal of Human Hypertension | 2011
H. Mei; Treva Rice; Dong Feng Gu; J. E. Hixson; Qi Zhao; Jichun Chen; J. Cao; Jianxin Li; Tanika N. Kelly; D. C. Rao; Jiang He
We examined the genetic association between blood pressure (BP) responses to dietary sodium and potassium intervention and to cold pressor test (CPT) in a large family-based dietary feeding study. The dietary intervention and CPT were conducted among 1906 participants in rural China. The dietary intervention included three 7-day periods of low-sodium feeding (51.3u2009mmol per day), high-sodium feeding (307.8u2009mmol per day) and high-sodium feeding plus potassium supplementation (60u2009mmol per day). BP responses to high-sodium intervention had strong genetic correlations (ρG) with both BP responses to low sodium (ρG=−0.43 to −0.54, P-values=0.0005 to 0.03) and to potassium supplementation (ρG=−0.41 to −0.49, P-values=0.001 to 0.005) interventions. Most environmental correlations between BP responses to various dietary interventions were significant. The ρG between BP responses to CPT and to high-sodium intervention and potassium supplementation were statistically significant. For example, the ρG between maximum BP responses to CPT and BP responses to high-sodium intervention was 0.37 (P=0.006) for systolic BP (SBP) and 0.41 (P=0.002) for diastolic BP (DBP). The ρG between maximum BP responses to CPT and BP responses to potassium intervention was −0.42 (P=0.001) for SBP and −0.46 (P=0.001) for SBP. Our study suggests that there are common genetic determinants that influence BP responses to dietary sodium and potassium interventions and to CPT.
Journal of Human Hypertension | 2015
Fangchao Liu; Xueli Yang; Xingbo Mo; Jian Feng Huang; Jichun Chen; Tanika N. Kelly; James E. Hixson; D. C. Rao; Chi Gu; Lawrence C. Shimmin; Treva Rice; Jianxin Li; Karen Schwander; Jiang He; De Pei Liu; Dong Feng Gu
In order to investigate the associations of SCNN1A, SCNN1G and SCNN1B genes with blood pressure (BP) in the Han Chinese population, we included 2880 participants did not use antihypertensive medication in the month prior to the baseline survey in the current analysis. Forty-four tag-single-nucleotide polymorphisms (SNPs) in epithelial sodium channel (ENaC) genes were selected and genotyped, and nine BP measurements were obtained during the 3-day examination. In the single-marker analyses, we identified significant associations of SCNN1A marker rs13306613 with diastolic BP (DBP) and SCNN1B marker rs12447134 with systolic BP (SBP) under codominant model after Bonferroni’s correction (P=2.82 × 10−5 and 4.63 × 10−4, respectively). In addition, five SNPs in SCNN1G and four SNPs in SCNN1B achieved nominal significance for SBP, DBP or mean arterial pressure (MAP) under the additive model. For example, the minor C allele of rs5735 in SCNN1G gene was associated with decreased SBP, DBP and MAP (P=0.016, 5.41 × 10−3 and 4.36 × 10−3, respectively). Gene-based results showed significant associations of SCNN1G and SCNN1B with BP levels. This study suggested that ENaC genes have important roles in BP regulation in the Han Chinese population. Future studies are warranted to replicate these findings, and functional studies are needed to identify true causal variants in ENaC genes.
Journal of Hypertension | 2017
Shufeng Chen; F. Liu; Yang X; Jian Feng Huang; Xiangfeng Lu; Jichun Chen; Jie Cao; Jianxin Li; Hongfan Li; L. Wang; De-Pei Liu; Dong Feng Gu
Objective: Insulin resistance (IR) is the crucial mechanism for metabolic syndrome, and a risk factor of cardiovascular disease (CVD). Salt restriction is recommended to decrease the risk of CVD. Nevertheless, recent studies have suggested that low sodium intake increases IR. We aimed to examine the association between IR and salt sensitivity of blood pressure (BP) in the GenSalt study. Design and method: We conducted a 7-day low-sodium intervention (51.3u200ammol of sodium per day) followed by a 7-day high-sodium intervention (307.8u200ammol of sodium per day) in population from the northern rural China. BP measurements were obtained at baseline and each dietary intervention using a random-zero sphygmomanometer. The serum insulin levels were analyzed using an automated two-site radioimmunoassay (Cisbio Bioassays, France). The index of IR was estimated as HOMA-IRu200a=u200a(fasting glucose (mg/dL) X fasting insulin (&mgr;U/mL))/405. Correlations between IR and BP were derived adjusting for age and gender. The associations between insulin response to sodium intervention and BP response to sodium intervention were tested using linear mixed-effect regression model. Results: A total of 1822 participants were included in the final analysis. Fasting serum glucose, insulin and HOMA-IR were higher during low-sodium intervention and lower during high-sodium intervention. The mean glucose, insulin and HOMA-IR were 86.4u200amg/dl, 6.1u200auIU/ml and 1.3 at baseline, 89.9u200amg/dl, 6.4u200auIU/ml and 1.4 at the end of low-sodium intervention, 85.3u200amg/dl, 5.4u200auIU/ml and 1.2 at the end of high-sodium intervention. After adjustment for age and gender, insulin was correlated with BP (SBP: ru200a=u200a0.15, Pu200a<u200a0.0001; DBP: ru200a=u200a0.09, Pu200a<u200a0.0001; MAP: ru200a=u200a0.13, Pu200a<u200a0.0001) at baseline; change in insulin was correlated with BP response (SBP: ru200a=u200a−0.04, Pu200a=u200a0.11; DBP: ru200a=u200a0.05, Pu200a=u200a0.04; MAP: ru200a=u200a−0.05, Pu200a=u200a0.04) to low-sodium intervention. In linear mixed-effect regression model, the increase in insulin was associated with decrease in SBP (&bgr;u200a=u200a−0.07, pu200a=u200a0.002), DBP (&bgr;u200a=u200a−0.06, pu200a=u200a0.03) and MAP (&bgr;u200a=u200a−0.09, pu200a=u200a0.003) during low-sodium intervention. Conclusions: We concluded that change in inzsulin was significantly associated with BP change during low-sodium intervention. The specific mechanism is not fully understood and further functional studies are warranted to clarify their relationship.
Circulation-cardiovascular Genetics | 2014
Xueli Yang; Dong Feng Gu; Jiang He; James E. Hixson; D. C. Rao; Fanghong Lu; Jianjun Mu; Jichun Chen; Huang J; Lawrence C. Shimmin; Treva Rice; Xigui Wu; De Pei Liu; Tanika N. Kelly
Background—Blood pressure (BP) response to cold pressor test (CPT) is associated with increased risk of cardiovascular disease. We performed a genome-wide linkage scan and regional association analysis to identify genetic determinants of BP response to CPT. Methods and Results—A total of 1961 Chinese participants completed the CPT. Multipoint quantitative trait linkage analysis was performed, followed by single-marker and gene-based analyses of variants in promising linkage regions (logarithm of odds ≥2). A suggestive linkage signal was identified for systolic BP response to CPT at 20p13 to 20p12.3, with a maximum multipoint logarithm of odds score of 2.37. On the basis of regional association analysis with 1351 single nucleotide polymorphisms in the linkage region, we found that marker rs2326373 at 20p13 was significantly associated with mean arterial pressure responses to CPT (P=8.8×10−6) after false discovery rate adjustment for multiple comparisons. A similar trend was also observed for systolic BP response (P=0.03) and diastolic BP response (P=4.6×10−5). Results of gene-based analyses showed that variants in genes MCM8 and SLC23A2 were associated with systolic BP response to CPT (P=4.0×10−5 and 2.7×10−4, respectively), and variants in genes MCM8 and STK35 were associated with mean arterial pressure response to CPT (P=1.5×10−5 and 5.0×10−5, respectively). Conclusions—Within a suggestive linkage region on chromosome 20, we identified a novel variant associated with BP responses to CPT. We also found gene-based associations of MCM8, SLC23A2, and STK35 in this region. Additional work is warranted to confirm these findings. Clinical Trial Registration—URL: http://www.clinicaltrials.gov; Unique identifier: NCT00721721.
Chinese Medical Journal | 2006
Qi Zhao; Shao Yong Su; Shu Feng Chen; Biao Li; Dong Feng Gu
Chinese Medical Journal | 2007
Shulian Chen; Lu Xf; Yan Wl; Jian Feng Huang; Dong Feng Gu
Chinese journal of preventive medicine | 2003
Dong Feng Gu; H. Jiang; Xi gui Wu; Kristi Reynolds; Wen qi Gan; Dong hai Liu; Shao yong Su; Xiufang Duan; Guang yong Huang; Paul K. Whelton
Biomedical and Environmental Sciences | 2006
Yan Wl; Shu Feng Chen; Jian Feng Huang; Shen Y; Qiang Bq; Liu Dh; Dong Feng Gu
Chinese Medical Journal | 2008
Lu Xf; Yu Hj; Zhou Xy; Wang Ly; Jian Feng Huang; Dong Feng Gu