Genetically elevated circulating homocysteine concentrations increase the risk of diabetic kidney disease in Chinese diabetic patients

Abstract Diabetic kidney disease (DKD) is a devastating and frequent complication of diabetes mellitus. Here, we first adopted methylenetetrahytrofolate reductase (MTHFR) gene C677T polymorphism as an instrument to infer the possible causal relevance between circulating homocysteine and DKD risk in a Chinese population and next attempted to build a risk prediction model for DKD. This is a hospital‐based case‐control association study. Total 1107 study participants were diagnosed with type 2 diabetes mellitus, including 547 patients with newly diagnosed and histologically confirmed DKD. MTHFR gene C677T polymorphism was determined using the TaqMan method. Carriers of 677TT genotype (14.55 μmol/L) had significantly higher homocysteine concentrations than carriers of 677CT genotype (12.88 μmol/L) (P < 0.001). Carriers of 677TT genotype had a 1.57‐fold increased risk of DKD (odds ratio: 1.57, 95% CI: 1.21‐2.05, P = 0.001) relative to carriers of 677CT genotype after adjusting for confounders. Mendelian randomization analysis revealed that the odds ratio for DKD relative to diabetes mellitus per 5 μmol/L increment of circulating homocysteine concentrations was 3.86 (95% confidence interval: 1.21‐2.05, P < 0.001). In the Logistic regression analysis, hypertension, homocysteine and triglyceride were significantly associated with an increased risk of DKD and they constituted a risk prediction model with good test performance and discriminatory capacity. Taken together, our findings provide evidence that elevated circulating homocysteine concentrations were causally associated with an increased risk of DKD in Chinese diabetic patients.


| Study participants
This is a hospital-based case-control association study conducted at the China-Japan Friendship Hospital between August 2016 and February 2018. In total, 1107 participants who were diagnosed with type 2 diabetes mellitus were recruited and hospitalized.
Diabetic kidney disease was diagnosed according to the National Kidney Foundation Kidney Disease Outcomes Quality Initiative (NKF-K/DOQI) guidelines. Patients with type 2 diabetes mellitus who had newly diagnosed and histologically confirmed DKD were classified as the case group (n = 547). The rest 560 patients who had experienced type 2 diabetes mellitus for seven or more years and had no history of DKD and severe kidney diseases formed the control group.
The conduct of this study was approved by the institutional review boards of the China-Japan Friendship Hospital. All study participants signed informed consent prior to blood sampling for genetic analysis and all of the other procedures associated with this study.

| Eligibility criteria
Participants in the case group were included if they had a clinical diagnosis of type 2 diabetes mellitus and 24 hours urinary albumin >500 mg/L or an albumin creatinine ratio (ACR) >30 mg/g and participants were excluded if they had no previous history of kidney diseases or if they had primary or secondary kidney diseases that caused proteinuria, such as IgA nephropathy, membranous nephropathy, lupus nephritis, obstructive renal disease and acute urinary tract infection.
Participants in the control group were included if they had a clinical diagnosis of type 2 diabetes mellitus and ACR <30 mg/g. The exclusion criteria were same as the case group.

| Data collection
Each participant was invited to complete a self-designed structured questionnaire to obtain information on age, sex, bodyweight, body height and smoking habit, hypertension and duration of diabetes mellitus. Body mass index (BMI) was calculated as weight (kg) divided by height squared (m 2 ).

| Genomic DNA extraction and genotyping
Genomic DNA was extracted from whole blood according to the manufacturer's recommendations and quantified using the NanoDrop 1000 spectrophotometer (ThermoScientific). DNA samples were frozen at −20°C until the time of analysis. To verify the genotypes, 50 polymerase chain reaction (PCR) products were randomly selected for DNA sequencing using the ABI 3500 Genetic Analyzer (Applied Biosystems) and the results were 100% concordant.

| Statistical analysis
Continuous variables were expressed as mean (SD) and categorical variables as number (percentage). Two group comparisons were performed using the t test or Wilcoxon rank-sum test or Chi-squared test where appropriate. Pearson correlation analysis was conducted to examine the relevance between homocysteine and lipid biomarkers. Forward Logistic regression analysis was used to select potential contributing factors at a significance level of 5%.
The −2 Log likelihood ratio test was used to compare the fit of two models. The goodness of fit of the model was justified using the Hosmer-Lemeshow test. The receiver operating characteristic (ROC) curves were plotted for models with and without significant factors.
The Sobel-Goodman mediation test was performed to test whether a mediator carried the influence of homocysteine on DKD risk. The net benefits of adding significant factors to basic model were seen by using decision curve analysis. 14 Finally, a nomogram was plotted for significant factors using regression modelling strategies (rms) program in the r software version 3.5.0.
A two-sided P less than 0.05 was considered the threshold of statistical significance. Unless otherwise stated, statistical analysis was completed using the stata/se software version 14.0 (StataCorp., College Station, TX). Table 1 shows the baseline characteristics of the study participants. More males were found in the case group than in the control group (67.09% vs 61.03, P = 0.035), as well as for hypertension percentage (77.27% vs 52.85%, P < 0.001). Mean levels of BMI, triglyceride and homocysteine were significantly higher in the case group than in the control group. The genotype distributions of MTHFR gene C677T polymorphism differed significantly between the two groups (P < 0.001), with the 677TT genotype overrepresented in the case group.

| Genotype-disease association
Carriers of the 677TT genotype had 1.57-fold increased risk of DKD (odds ratio: 1.57, 95% CI: 1.21-2.05, P = 0.001) relative to carriers of 677CT genotype after adjusting for confounding factors (age, sex, BMI, smoking, hypertension, duration of diabetes mellitus, triglyceride, TC and HDLC), whereas no significance was found for the comparison of the 677TT genotype vs 677CC genotype. Figure 1 presents the correlation plot of homocysteine and four blood lipids. The correlation coefficient of circulating homocysteine with lipids ranged from 0.006 to 0.027, with no detectable significance. In addition, the Sobel-Goodman mediation test failed to reveal any significant contribution of BMI and four blood lipids to the relevance between circulating homocysteine concentrations and DKD risk (Table S1).

| Mendelian randomization estimate
Based on the risk estimates of genotype-phenotype and genotypedisease associations and under the rationales of Mendelian randomization approach, the odds ratio for DKD relative to diabetes mellitus per 5 μmol/L increment of circulating homocysteine concentrations was 3.86 (95% confidence interval: 1.21-2.05, P < 0.001) implying a potential causal role of homocysteine in the pathogenesis of DKD.

| Selection of significant factors
Significant factors in association with DKD risk were selected based on the Forward Logistic regression analysis (

| Prediction performance assessment
Prediction models with (full model) and without (basic model) three significant factors differed significantly and both models showed goodness of fit (Table 3).

| Decision curve analysis and nomogram
The benefits gained by adding three significant factors to the basic model were higher than the benefits of the basic model ( Figure 2).
Based on three significant factors, a nomogram is plotted in Figure 3 to predict the risk of DKD relative to diabetes mellitus. The C-index of this nomogram to assess prediction accuracy was 0.71 (P < 0.01) indicating good prediction performance. Hyperhomocysteinaemia is an independent risk factor for glomeruloslerosis and renal insufficiency and the association of circulating homocysteine with DKD was widely evaluated in the medical literature, yet the results are not often reproducible. [7][8][9][18][19][20][21][22] Actually, current evidence linking homocysteine to DKD is mainly based on observational data, in which the degree of possible confounding and reverse causation may cloud the true relationship. 23,24 In this context, Mendelian randomization has proven to be a valuable method to overcome confounding and reverse causality 25,26 and this method enables estimation of causal relationship in observational studies using genetic alterations as instruments. 27 Following the principles of Mendelian randomization, we found that per 5 μmol/L increment in circulating homocysteine concentrations increased approximately four-fold the odds of having DKD. This finding was relatively convincing, as the instrumental polymorphism (C677T) selected in this study was simultaneously and significantly associated with circulating homocysteine changes and DKD risk by many studies 11,[28][29][30][31] and further the association between homocysteine and DKD risk was not mediated by obesity and blood lipids. For practical reasons, there is potential clinical utility in the consideration of homocysteine concentrations among diabetic patients.

| D ISCUSS I ON
In support of our findings, peroxisome proliferator-activated receptor gamma (PPAR-γ) agonist ciglitazone can protect DKD in part by activating PPAR-γ and clearing glomerular tissue homocysteine. 32 Pending prospective reproducible investigations circulating homocysteine concentrations can help identify diabetic patients with a high risk of DKD who could benefit from closer monitoring. The underlying mechanisms for the contribution of increased cir- Despite these limitations, our findings provide evidence that elevated circulating homocysteine concentrations were causally associated with an increased risk of DKD in Chinese diabetic patients.
Moreover, we have built a powerful risk prediction model, including homocysteine, hypertension and triglyceride, which can allow early detection and targeted treatment in the control of DKD. For practical reasons, we hope this study will not remain just another endpoint of research instead of a start to establish fundamental data to further explore the molecular mechanisms of circulating homocysteine and DKD.

CO N FLI C T O F I NTE R E S T
The authors declare that they have no competing interests.