The aim of this study was to investigate the relationship between
In China, as of 2010, there were more than 110 million adults with diabetes mellitus and another more than 490 million with prediabetes [
Epoxyeicosatrienoic acids (EETs) are involved in regulation of renal blood flow and long-term arterial blood pressure. Moreover, renal and cardiovascular diseases are associated with decreased renal and vascular levels of EETs [
Although the relationship between rs751141 and risk of IgA nephropathy has been investigated [
This study was approved by the institutional ethics committee of the China-Japan Friendship Hospital, Beijing, China. Signed informed consent was obtained from all participants. A total of 870 Chinese T2D patients were recruited from the China-Japan Friendship Hospital, between February 2015 and June 2016.
T2D was defined by the World Health Organization (WHO) 1999 criteria. This was a clinic-based case-control study. Cases were persons with type 2 diabetes and DN, and controls were persons with type 2 diabetes who did not have DN. Inclusion criteria for cases were diagnosed with T2D, age between 35 and 85 years old, and 24 h urinary albumin > 500 mg/L or an albumin creatinine ratio (ACR) > 30 mg/g. Inclusion criteria for controls were T2D duration ≥ 7 years, age between 35 and 85 years old, and 24 h urinary albumin < 150 mg/L or an ACR < 30 mg/g. Exclusion criteria for both groups consisted of known proteinuria before the onset of diabetes, other primary or secondary renal diseases (e.g., IgA nephropathy, membranous nephropathy, lupus nephritis, obstructive renal disease, renal stone disease, and acute urinary tract infection), and malignancy.
Demographic information, smoking habit, history of hypertension, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), 24 h urinary albumin excretion and ACR, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), triglycerides (TG), and homocysteine (Hcy) of each participant were obtained. Body weight and height were measured using standard methods, and BMI was calculated as weight (kg) divided by height squared (m2). Resting blood pressure was measured twice according to standard protocol and the results were averaged. Serum concentrations of fasting TG, TC, LDL-C, HDL-C, and Hcy were measured using an automated biochemical analyzer (AU5800 Clinical Chemistry System, Beckman Coulter, Brea, CA, USA). A1C was measured using the D-10 Hemoglobin Testing System (Bio-Rad, Hercules, CA, USA).
DNA was extracted from peripheral blood using the QIAamp DNA Blood Mini Kit (Qiagen, Hilden, Germany) following the manufacturer’s recommendations and then stored at −20°C or amplified immediately. The concentration of DNA was determined using the NanoDrop 1000 spectrophotometer (Thermo Scientific, Waltham, MA, USA).
Genotyping was confirmed using TaqMan SNP Genotyping Assay (Applied Biosystems, Waltham, MA, USA). In all, 50 ng DNA was amplified in a 25
Amplification was performed using a real-time polymerase chain reaction (PCR) detector (LightCycler 480, Roche Diagnostics, Penzberg, Germany) with a PCR temperature profile consisting of denaturation at 95°C for 10 minutes following 40 cycles of denaturation at 95°C for 15 seconds, annealing and elongation at 65°C for 60 seconds.
To confirm the genotyping results, 50 samples were randomly selected for DNA sequencing. rs751141 was amplified for DNA sequencing using the following designed primers F:5
Quantitative clinical data (age, BMI, blood pressure, duration of diabetes, total cholesterol, HDL-C, LDL-C, TG, and Hcy) were non-Gaussian distribution and presented as median (interquartile range), and Wilcoxon’s test was used to compare the difference in clinical characteristics between DN and DM groups. Genotype distribution and allelic frequency were analyzed using the chi-square test. Deviations from Hardy-Weinberg were also tested using the chi-square test. Finally, multiple logistic regression analyses were carried out to examine the association between rs751141 and risk of DN adjusted for age, sex, duration of diabetes, history of hypertension, smoking status, cholesterol, TG, and Hcy levels in additive, recessive, or dominant models. To define these models, take SNP rs751141 as an example where A is the minor allele. For the dominant model, AA and GA were coded as 1 in the regression model and GG was coded 0. For the recessive model, AA was coded as 1 while GG and GA were coded as 0. For the additive model, AA, GA, and GG were coded as 2, 1, and 0, respectively.
Power calculation was performed by Quanto software (version 1.2.4, University of Southern California, Los Angeles, CA, USA). Data were analyzed with the SPSS software (version 17.0, IBM, Armonk, NY, USA).
A total of 870 participants were included in this study. Cases included 406 DM patients with DN patients (258 males and 148 females), and controls included 464 DM patients without DN (271 males and 191 females) (Table
Characteristics of DM patients with DN (cases) and without DN (controls).
DM patients with DN ( |
DM patients without DN ( |
|
|
---|---|---|---|
Age (years) | 63 (54, 71) | 61 (54, 68) | 0.001 |
Sex, male (%) | 63.55 (258/406) | 58.41 (271/464) | 0.121 |
BMI (kg/m2) | 25.80 (23.89, 28.36) | 25.36 (23.20, 27.68) | 0.006 |
Duration of diabetes (years) | 15 (9, 21) | 13 (10, 18) | 0.097 |
History of hypertension (%) | 78.82 (320/406) | 49.35 (229/464) | <0.001 |
Smoking (%) | 34.73 (141/406) | 28.23 (131/464) | 0.039 |
SBP (mmHg) | 138 (125, 150) | 127 (120, 140) | <0.001 |
DBP (mmHg) | 80 (74, 84) | 80 (70, 80) | 0.048 |
A1C (%) | 7.6 (6.5, 9.3) | 7.9 (6.7,9.3) | 0.148 |
Hcy (umol/L) | 13.63 (11.03, 17.12) | 11.48 (9.51, 13.42) | <0.001 |
TC (mmol/L) | 4.25 (3.44, 5.06) | 4.14 (3.53, 4.86) | 0.36 |
HDL-C (mmol/L) | 0.96 (0.78, 1.18) | 1.02 (0.85, 1.24) | 0.004 |
LDL-C (mmol/L) | 2.39 (1.85, 2.98) | 2.38 (1.94, 2.97) | 0.535 |
TG (mmol/L) | 1.71 (1.20, 2.56) | 1.42 (0.99, 2.18) | <0.001 |
BMI: body mass index; DBP: diastolic blood pressure; Hcy: homocysteine; HDL-C: high-density lipoprotein cholesterol; LDL-C: low-density lipoprotein cholesterol SBP: systolic blood pressure; TC: triglyceride. aData are shown as median (interquantile range) or %.
Distribution of allele frequencies of rs751141 was in accordance with the Hardy-Weinberg equilibrium in both DM with DN and without DN participants (
Genotype distribution and allele frequency of rs751141 in DM patients with DN and without DN participants.
Genotype | Genotype frequencies |
|
|
---|---|---|---|
DM patients with DN | DM patients without DN | ||
GG | 250 | 251 | 0.001 |
GA | 142 | 168 | |
AA | 14 | 45 | |
A allele | 20.94% | 27.8% | 0.001 |
G allele | 79.06% | 72.2% |
DM: diabetes mellitus; DN: diabetic nephropathy.
To confirm the association between the genotyping of rs751141 and the possibility of DN, further multiple logistic regression analysis was performed. Three statistical models were used as unadjusted, adjusted for age and sex, and adjusted for age, sex, Hcy, BMI, duration of diabetes, hypertension, smoking, total cholesterol, and TG levels. Results indicated the risk of DN with rs751141 in these models (Table
Odds ratios and 95% confidence interval for DN under three genetic models.
Genetic models | Unadjusted | Adjusteda | Adjustedb | |||
---|---|---|---|---|---|---|
OR (95% CI) |
|
OR (95% CI) |
|
OR (95% CI) |
|
|
Additive | 0.69 (0.55–0.86) | <0.001 | 0.66 (0.52–0.83) | <0.001 | 0.68 (0.52–0.88) | 0.004 |
Recessive | 0.33 (0.18–0.62) | <0.001 | 0.33 (0.17–0.65) | 0.001 | 0.28 (0.14–0.60) | 0.001 |
Dominant | 0.72 (0.55–0.95) | 0.018 | 0.67 (0.50–0.90) | 0.008 | 0.73 (0.53–1.01) | 0.059 |
GA versus GG | 0.83 (0.63–1.10) | 0.201 | 0.77 (0.57–1.05) | 0.097 | 0.87 (0.62–1.23) | 0.43 |
AA versus GG | 0.31 (0.17–0.58) | <0.001 | 0.30 (0.15–0.60) | <0.001 | 0.27 (0.13–0.58) | <0.001 |
Allele (A versus G) | 0.69 (0.55–0.86) | <0.001 |
CI: confidence interval; DN: diabetic nephropathy; OR: odds ratio. aAdjusted for age and sex. bAdjusted for age, sex, Hcy, BMI, duration of diabetes, hypertension, smoking, total cholesterol, and TG levels.
Participants were randomly divided into three equal groups based on Hcy levels (low level: 4.29–10.78 umol/L; medium level: 10.79–13.93 umol/L; high level: 13.94–55.99 umol/L). The three genetic models of additive, recessive, and dominant showed significant association with DN in the high level of Hcy groups in unadjusted ( Association of R287Q with risk of DN in different Hcy-level groups. DN: diabetic nephropathy; Hcy: homocysteine. aAdjusted for age, sex, BMI, duration of diabetes, hypertension, smoking, total cholesterol, and TG levels.Hcy level (umol/L) Unadjusted Adjusteda Genotype OR (95% CI) OR (95% CI) Low: 4.29–10.78 Additive 0.67 (0.44–1.02) 0.063 0.67 (0.41–1.10) 0.113 Recessive 0.42 (0.14–1.27) 0.12 0.18 (0.03–0.98) 0.05 Dominant 0.65 (0.38–1.11) 0.12 0.74 (0.40–1.38) 0.35 Medium:10.79–13.93 Additive 0.74 (0.49–1.11) 0.14 0.81 (0.51–1.30) 0.38 Recessive 0.22 (0.05–0.98) 0.047 0.27 (0.06–1.28) 0.10 Dominant 0.82 (0.51–1.32) 0.41 0.93 (0.53–1.65) 0.81 High:13.94–55.99 Additive 0.57 (0.38–0.84) 0.005 0.52 (0.33–0.81) 0.004 Recessive 0.32 (0.13–0.82) 0.02 0.27 (0.09–0.78) 0.015 Dominant 0.56 (0.34–0.92) 0.02 0.51 (0.29–0.90) 0.019
To our knowledge, this study is the first to describe the association between the polymorphism rs751141 of
Studies have demonstrated that the A allele of rs751141 exhibits markedly lower sEH metabolic activity and decreased EET hydrolysis in vitro [
Interactions between genetic and environmental factors play a substantial role in disease risk [
The present study was performed with 406 patients with DN and 464 control participants with DM, which would have good statistical power to detect associations. However, there are still some limitations. First, the sample size of this study was limited when stratified according to Hcy level. Second, this study was conducted in Chinese and whether the results can be generalized to other ethnic groups need further investigation. Thus, a more extensive examination across various ethnic groups may help clarify the role of
In conclusion, our findings revealed that the exonic genetic variant in
The authors declare no conflicts of interest.
This study was supported by the National Natural Science Foundation of China (Grant nos. 81703892, 8162010803, and 81473526) and the China-Japan Friendship Hospital Youth Science and Technology Excellence Project (Grant no. 2015-QNYC-B-09). The authors thank Nissi S. Wang, MSc, for developmental editing of the manuscript.