The Association Between Leucine and Diabetic Nephropathy in Different Gender: A Cross-Sectional Study in Chinese Patients With Type 2 Diabetes

Association between the MCP-1 -2518 A > G (rs1024611) polymorphism and susceptibility to type 2 diabetes mellitus and diabetic nephropathy: a meta-analysis

BACKGROUND

Studies evaluating the association between monocyte chemoattractant protein-1 (MCP-1) -2518 A > G (rs1024611) polymorphism and type 2 diabetes mellitus (T2DM) and diabetic nephropathy (DN) are contradictory. The present study aims to provide a comprehensive assessment and more reliable estimation of the relationship between the MCP-1 rs1024611 polymorphism and T2DM and DN risk.

METHODS

Eligible articles were retrieved from the PubMed, Web of Science, EMBASE, Cochrane, and China National Knowledge Infrastructure databases. The effect summary odds ratios (ORs) and 95% confidence intervals (CIs) were obtained to calculate the summary effect size. Heterogeneity was analyzed by subgroup analysis and meta-regression. Publication bias was tested using funnel plots and Egger's test.

RESULTS

In total, sixteen studies were included. Thirteen studies involving 2,363 patients with T2DM and 4,650 healthy controls found no significant association between the MCP-1 rs1024611 polymorphism and T2DM in the overall population. Ethnicity stratification found an association between the GG + GA genotype and decreased T2DM risk in Caucasians (OR = 0.79, 95% CI: 0.66-0.93, P = 0.006; PQ = 0.372). No significant risks were found in the Asian population for any genetic models. Seven studies found an association between the GG + GA genotype and DN risk in the Asian population (OR = 1.37, 95% CI: 1.11-1.71, P = 0.004, PQ = 0.222). No significant risks were found in the Caucasian population with any genetic models. There were no statistically significant differences in genotype distribution between patients with T2DM and DN in Asians or Caucasians. Meta-regression revealed that genotyping method was a major driver of heterogeneity in five genetic models (GG + GA vs. AA: P = 0.032; GG vs. GA + AA: P = 0.028; GG vs. AA: P = 0.035; GG vs. GA: P = 0.041; G vs. A: P = 0.041).

CONCLUSION

The MCP-1 rs1024611 polymorphism is associated with susceptibility to T2DM in Caucasians and DN in Asians. Larger, well-designed cohort studies are needed in the future to verify this association.

Amino acid analysis as a method of discovering biomarkers for diagnosis of diabetes and its complications

Diabetes mellitus (DM) is a severe chronic diseases with a global prevalence of 9%, leading to poor health and high health care costs, and is a direct cause of millions of deaths each year. The rising epidemic of diabetes and its complications, such as retinal and peripheral nerve disease, is a huge burden globally. A better understanding of the molecular pathways involved in the development and progression of diabetes and its complications can facilitate individualized prevention and treatment. High diabetes mellitus incidence rate is caused mainly by lack of non-invasive and reliable methods for early diagnosis, such as plasma biomarkers. The incidence of diabetes and its complications in the world still grows so it is crucial to develop a new, faster, high specificity and more sensitive diagnostic technologies. With the advancement of analytical techniques, metabolomics can identify and quantify multiple biomarkers simultaneously in a high-throughput manner, and effective biomarkers can greatly improve the efficiency of diabetes and its complications. By providing information on potential metabolic pathways, metabolomics can further define the mechanisms underlying the progression of diabetes and its complications, help identify potential therapeutic targets, and improve the prevention and management of T2D and its complications. The application of amino acid metabolomics in epidemiological studies has identified new biomarkers of diabetes mellitus (DM) and its complications, such as branched-chain amino acids, phenylalanine and arginine metabolites. This study focused on the analysis of metabolic amino acid profiling as a method for identifying biomarkers for the detection and screening of diabetes and its complications. The results presented are all from recent studies, and in all cases analyzed, there were significant changes in the amino acid profile of patients in the experimental group compared to the control group. This study demonstrates the potential of amino acid profiles as a detection method for diabetes and its complications.

Prevalence of Diabetic Retinopathy and Use of Common Oral Hypoglycemic Agents Increase the Risk of Diabetic Nephropathy-A Cross-Sectional Study in Patients with Type 2 Diabetes

OBJECTIVE

This study investigated the effect of amino acid metabolism on the risk of diabetic nephropathy under different conditions of the diabetic retinopathy, and the use of different oral hypoglycemic agents.

METHODS

This study retrieved 1031 patients with type 2 diabetes from the First Affiliated Hospital of Liaoning Medical University in Jinzhou, which is located in Liaoning Province, China. We conducted a spearman correlation study between diabetic retinopathy and amino acids that have an impact on the prevalence of diabetic nephropathy. Logistic regression was used to analyze the changes of amino acid metabolism in different diabetic retinopathy conditions. Finally, the additive interaction between different drugs and diabetic retinopathy was explored.

RESULTS

It is showed that the protective effect of some amino acids on the risk of developing diabetic nephropathy is masked in diabetic retinopathy. Additionally, the additive effect of the combination of different drugs on the risk of diabetic nephropathy was greater than that of any one drug alone.

CONCLUSIONS

We found that diabetic retinopathy patients have a higher risk of developing diabetic nephropathy than the general type 2 diabetes population. Additionally, the use of oral hypoglycemic agents can also increase the risk of diabetic nephropathy.

AMINO ACIDS METABOLOMIC SIGNATURE OF BLOOD PRESSURE VARIABILITY In Type 2 Diabetes

Context

Accumulating data supports the key role of disrupted amino acids (AAs) metabolism in diabetes. Conflicting data regarding the relevance of serum AAs in diabetes and hypertension suggest that their relationship needs further investigation.

Objective

To investigate serum AAs as biomarkers of increased BP variability evaluated during 24-hour ambulatory BP monitoring in the presence of type 2 diabetes.

Design

Cross-sectional.

Subjects and Methods

We analyzed serum AAs using targeted metabolomics (ultrahigh-performance liquid chromatography/mass spectrometry) in patients with type 2 diabetes (n=80). BP variability was assessed using 24-hour ambulatory BP monitoring. Participants were divided into two groups based on the 24-hour diastolic BP variability median value.

Results

Aspartic acid, isoleucine, leucine, and phenylalanine were significantly lower, while glutamine was significantly higher in the group with higher diastolic BP variability (p-value <0.05 and variable importance in the projection >1). Corresponding pathways identified as disrupted in patients with diabetes and a higher 24-hour diastolic BP variability were phenylalanine, tyrosine, and tryptophan biosynthesis, phenylalanine metabolism, and alanine, aspartate, and glutamate metabolism (pathway impact value >0).

Conclusions

We identified specific changes in serum AAs and target AAs pathways in relation to increased 24-hour diastolic BP variability in patients with type 2 diabetes.

The Effect of Mild Renal Dysfunction on the Assessment of Plasma Amino Acid Concentration and Insulin Resistance in Patients with Type 2 Diabetes Mellitus

BACKGROUND

An increase in the levels of branched-chain amino acids (BCAAs) and certain aromatic amino acids, such as alanine, in plasma is correlated with insulin resistance (IR) in type 2 diabetes mellitus (T2DM). T2DM is a leading risk factor for chronic kidney disease. Meanwhile, renal dysfunction causes changes in plasma amino acid levels. To date, no study has examined how mild renal dysfunction and IR interact with plasma amino acid levels. This study examines the effects of IR and renal dysfunction on plasma amino acid concentrations in T2DM.

METHODS

Data were collected from healthy male participants (controls) and male patients with T2DM between May 2018 and February 2022. Blood samples were collected after overnight fasting. IR and renal function were evaluated using the homeostasis model assessment of IR (HOMA-IR) and serum cystatin C (CysC), respectively.

RESULTS

A total of 49 and 93 participants were included in the control and T2DM groups, respectively. In the T2DM group, eight amino acids (alanine, glutamic acid, glutamine, glycine, isoleucine, leucine, tyrosine, and valine) and total BCAA showed a significant correlation with HOMA-IR (p < 0.01), whereas six amino acids (γ-aminobutyric acid, citrulline, cysteine, glycine, methionine, and valine) and total BCAA showed a significant correlation with 1/CysC (p < 0.02). However, only alanine, glutamic acid, and each BCAA showed significant differences between the control group and the IR T2DM subgroup. Increases in the BCAA levels with T2DM were canceled by renal dysfunction (CysC ≥ 0.93) in patients with intermediate IR.

CONCLUSION

To use plasma BCAA concentration as a marker of IR, renal function must be considered, even in mild renal dysfunction. Increased alanine and glutamic acid levels indicate IR, regardless of mild renal dysfunction.

The Association Between Leucine and Diabetic Retinopathy in Different Genders: A Cross-Sectional Study in Chinese Patients With Type 2 Diabetes

OBJECTIVE

To explore the association between serum leucine (leu) and diabetic retinopathy (DR) in patients with type 2 diabetes (T2D) and then to analyze the influence of gender on the association.

METHOD

The electronic medical records of 1,149 T2D patients who met inclusion and exclusion criteria were retrieved from the Second Affiliated Hospital of Dalian Medical University and the First Affiliated Hospital of Jinzhou Medical University. Serum leu levels of all subjects were measured by liquid chromatography-mass spectrometry. Logistic regression was used to obtain the odds ratio (OR) and CI of leu-DR risk in multiple models. When using these models, restricted cubic spline (RCS) was used to test the potential non-linear relationship between multiple continuous independent variables, such as leu and DR (classification), and dependent variables. We also used the additive interaction method to evaluate the interaction effect between leu and gender on DR.

RESULTS

Leu was a protective factor of DR [0.78 (0.66, 0.92)]. When gender was divided into male and female, the above relationship was statistically significant only in men [0.73 (0.58, 0.94)]. Three indicators of additive interaction-RERI, AP, and S-suggested that there is no interaction between gender and leu on the risk of DR.

CONCLUSIONS

Male T2D patients with high leu levels may have a lower risk of DR.