Gene‐environment interaction in chronic kidney disease among people with type 2 diabetes from The Malaysian Cohort project: a case‐control study

2020 ◽  
Vol 37 (11) ◽  
pp. 1890-1901 ◽  
Author(s):  
N. Ahmad ◽  
S. A. Shah ◽  
A. H. Abdul Gafor ◽  
N. A. Abdul Murad ◽  
M. A. Kamaruddin ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Case Control Study ◽  
Case Control ◽  
Environment Interaction ◽  
Gene Environment Interaction ◽  
Gene Environment ◽  
Control Study

Association Between Tfeb Gene Polymorphism, Gene–environment Interaction, and Fatty Liver Disease: a Case–control Study in China

2021 ◽  
Author(s):  
Chunbao Mo ◽  
Tingyu Mai ◽  
Jiansheng Cai ◽  
Haoyu He ◽  
Huaxiang Lu ◽  
...  
Keyword(s):  
Liver Disease ◽  
Fatty Liver ◽  
Fatty Liver Disease ◽  
Case Control Study ◽  
Case Control ◽  
Environment Interaction ◽  
Additive Interaction ◽  
Gene Environment Interaction ◽  
Gene Environment ◽  
Control Study

Abstract Background: Fatty liver disease (FLD) is a serious public health problem that is rapidly increasing. Evidences indicated that the transcription factor EB (TFEB) gene may be involved in the pathophysiology of FLD; however, whether TEFB polymorphism is association with FLD remains unclear.Objectives: To explore the association among TFEB polymorphism, gene–environment interaction, and FLD and provide epidemiological evidence for clarifying the genetic factors of FLD.Methods: This study is a case–control study. Sequenom MassARRAY was applied in genotyping. Logical regression was used to analyze the association between TFEB polymorphism and FLD, and the gene–environment interaction in FLD was evaluated by multiplication and additive interaction models.Results: (1) The alleles and genotypes of each single nucleotide polymorphism of TFEB in the case and control groups were evenly distributed; no statistically substantial difference was observed. (2) Logistic regression analysis indicated that TFEB polymorphism is not remarkably associated with FLD. (3) In the multiplicative interaction model, rs1015149, rs1062966, and rs11754668 had remarkable interaction with smoking amount. Rs1062966 and rs11754668 also had a considerable interaction with body mass index and alcohol intake, respectively. However, no remarkable additive interaction was observed.Conclusion: TFEB polymorphism is not directly associated with FLD susceptibility, but the risk can be changed through gene–environment interaction.

Gene environment interaction in urinary bladder cancer with special reference to organochlorine pesticide: A case control study

2013 ◽  
Vol 13 (4) ◽  
pp. 243-251 ◽  
Author(s):  
Tusha Sharma ◽  
Smita Jain ◽  
Ankur Verma ◽  
Nivedita Sharma ◽  
Sanjay Gupta ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Urinary Bladder ◽  
Special Reference ◽  
Case Control Study ◽  
Urinary Bladder Cancer ◽  
Case Control ◽  
Environment Interaction ◽  
Gene Environment Interaction ◽  
Gene Environment ◽  
Control Study

scholarly journals Association between TFEB gene polymorphism, gene–environment interaction, and fatty liver disease: A case–control study in China

2021 ◽  
Vol 104 (3) ◽  
pp. 003685042110437
Author(s):  
Chunbao Mo ◽  
Tingyu Mai ◽  
Jiansheng Cai ◽  
Haoyu He ◽  
Huaxiang Lu ◽  
...  
Keyword(s):  
Liver Disease ◽  
Fatty Liver ◽  
Fatty Liver Disease ◽  
Case Control Study ◽  
Case Control ◽  
Environment Interaction ◽  
Additive Interaction ◽  
Gene Environment Interaction ◽  
Gene Environment ◽  
Control Study

Background: Fatty liver disease (FLD) is a serious public health problem that is rapidly increasing. Evidence indicates that the transcription factor EB ( TFEB) gene may be involved in the pathophysiology of FLD; however, whether TEFB polymorphism has an association with FLD remains unclear. Objectives: To explore the association among TFEB polymorphism, gene–environment interaction, and FLD and provide epidemiological evidence for clarifying the genetic factors of FLD. Methods: This study is a case–control study. Sequenom MassARRAY was applied in genotyping. Logical regression was used to analyze the association between TFEB polymorphism and FLD, and the gene–environment interaction in FLD was evaluated by multiplication and additive interaction models. Results: (1) The alleles and genotypes of each single nucleotide polymorphism and haplotypes of TFEB in the case and control groups were evenly distributed; no statistically substantial difference was observed. (2) Logistic regression analysis indicated that TFEB polymorphism is not remarkably associated with FLD. (3) In the multiplicative interaction model, rs1015149, rs1062966, rs11754668 and rs2273068 had remarkable interaction with the amount of cigarette smoking. Rs1062966 and rs11754668 also had a considerable interaction body mass index and alcohol intake, respectively. However, no remarkable additive interaction was observed. Conclusion: TFEB polymorphism is not directly associated with FLD susceptibility, but the risk can be changed through gene–environment interaction.

scholarly journals Risk of chronic kidney disease in type 2 diabetes determined by polymorphisms in NOS3, APOB, KCNJ11, TCF7L2 genes as compound effect of risk genotypes combination

2014 ◽  
Vol 17 (3) ◽  
pp. 23-30 ◽  
Author(s):  
Anna Viktorovna Zheleznyakova ◽  
Nadezhda Olegovna Lebedeva ◽  
Olga Konstantinovna Vikulova ◽  
Valery Vyacheslavovich Nosikov ◽  
Minara Shamkhalovna Shamkhalova ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Renal Damage ◽  
Case Control Study ◽  
Chronic Complications ◽  
Polymorphic Variants ◽  
Compound Effect ◽  
Control Study

Genetic susceptibility plays an important role in the risk of developing chronic complications in patients with type 2 diabetes mellitus (T2DM). Aims. In this study, we evaluated the possible association of the polymorphic variants that encode key renal damage mediators (endothelial dysfunction, lipid metabolism and insulin secretion/sensitivity) with the risk of chronic kidney disease (CKD) in patients with T2DM. Materials and Methods. We enrolled 435 patients with T2DM using case-control study design. In 253 patients, we used non-overlapping criteria to form groups with/without CKD (defined as GFR=10 years) (n=75 and 178, respectively) and analysed the following 4 polymorphic markers: I/D in ACE, ecNOS4a/4b in NOS3, I/D in APOB and e2/e3/e4 in APOE genes. We then divided 182 patients in groups with/without CKD (n=38 and 144, respectively) regardless of the duration of diabetes and studied pro12ala in PPARG2, rs5219 in KCNJ11, rs12255372 in TCF7L2 and rs13266634 in SLC30A8 genes. 2 test, and data were expressed as odds ratios (ORs) with 95% confidence intervals (CIs). Values of p

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