|Year : 2016 | Volume
| Issue : 1 | Page : 24-28
Study of Dyslipidemia and Cystatin C Levels as a Predictive Marker of Chronic Kidney Disease in Type 2 Diabetes Mellitus Patients at a Teaching Hospital in Central India
Kamal Kachhawa1, Meena Varma1, Poonam Kachhawa2, Ankita Sahu1, M.K.S. Shaikh1, Sanjay Kumar3
1 Department of Biochemistry, Sri Aurobindo Institute of Medical Sciences, Indore, Madhya Pradesh, India
2 Department of Biochemistry, Saraswati Institute of Medical Sciences, Hapud, Uttar Pradesh, India
3 Department of Pharmacology, IMS and SUM Hospital, SOA University, Bhubaneswar, Odisha, India
|Date of Web Publication||1-Feb-2016|
Department of Biochemistry, Sri Aurobindo Institute of Medical Sciences, Indore - 453 555, Madhya Pradesh
Source of Support: None, Conflict of Interest: None
Background and Objective: Diabetic nephropathy is the most common cause of microvascular chronic complication of Type 2 diabetes mellitus (T2DM), which is associated with considerable morbidity and mortality. Chronic kidney diseases (CKD) may result from diabetes mellitus (34%), hypertension (29%), glomerulonephritis (14%), and others (23%). The present study was undertaken to explore the possibility of the serum cystatin C level as a marker of early renal impairment in T2DM patient. Materials and Methods: The study was conducted in 75 patients of T2DM and 75 healthy individuals were included as control in this study. After 12 h fasting, 8 mL venous blood sample was collected and allowed to clot for h and serum was separated. Lipid profile and cystatin C level of serum were measured by using commercially available kit of auto analyzer. Results: The level of serum cystatin C was significantly increased in T2DM patients as compared to control. In T2DM patients, high-density lipoprotein cholesterol significantly decreased (P < 0.001), while other parameters of lipid profile were significantly increased (P < 0.001) as compared to control group. Conclusion: Present study suggests that cystatin C measurement in serum is a useful, practical, noninvasive tool for the evaluation of renal involvement in the course of diabetes, especially patients, and the study also shows significant lipoprotein abnormalities in T2DM patients when compared to control.
Keywords: Chronic kidney disease, cystatin C, renal impairment, Type 2 diabetes mellitus
|How to cite this article:|
Kachhawa K, Varma M, Kachhawa P, Sahu A, Shaikh M, Kumar S. Study of Dyslipidemia and Cystatin C Levels as a Predictive Marker of Chronic Kidney Disease in Type 2 Diabetes Mellitus Patients at a Teaching Hospital in Central India. J Integr Nephrol Androl 2016;3:24-8
|How to cite this URL:|
Kachhawa K, Varma M, Kachhawa P, Sahu A, Shaikh M, Kumar S. Study of Dyslipidemia and Cystatin C Levels as a Predictive Marker of Chronic Kidney Disease in Type 2 Diabetes Mellitus Patients at a Teaching Hospital in Central India. J Integr Nephrol Androl [serial online] 2016 [cited 2021 Dec 4];3:24-8. Available from: http://www.journal-ina.com/text.asp?2016/3/1/24/175401
| Inroduction|| |
Diabetic nephropathy (DN) is the most common cause of microvascular chronic complication of Type 2 diabetes mellitus (T2DM) which is associated with considerable morbidity and mortality, finally leading to end-stage renal disease.  According to the World Health Organization, the prevalence of diabetes for all age-groups worldwide was estimated to be 2.8% in 2000 and 4.4% in 2030.  To prevent this increase, screening for DN and early intervention are necessary.
Chronic kidney disease (CKD) results in profound dysregulation of several key enzymes and metabolic pathways that eventually contributes to disordered high-density lipoprotein (HDL) cholesterol and triglyceride-rich lipoproteins.  Higher total cholesterol, higher non-HDL-cholesterol, and lower HDL-cholesterol were significantly associated with an increased risk of developing renal dysfunction in healthy men. 
Cystatin C, a cysteine protease inhibitor, is freely filtered by the renal glomeruli, metabolized by the proximal tubule and identified as a promising marker of renal failure.  Cystatin C is produced at a constant rate by nucleated cells and released into the bloodstream with a half-life of 2 h. Its concentration is almost totally dependent on glomerular filtration rate (GFR). Other studies have demonstrated that serum cystatin C is an early renal marker in diabetic patients,  but not all studies have done so. 
The oxidative stress generated by hyperglycemia increases reactive oxygen species (ROS), which leads to the activation of various redox-sensitive cell signaling molecules and the production of cytotoxic materials. This is followed by cellular dysfunction and damage and ultimately results in diabetic micro- and macro-vascular complications. 
The present study was undertaken to explore the possibility of the serum cystatin C level as marker of early renal impairment in T2DM patient and also studied alter lipoprotein level in T2DM patients.
| Materials and methods|| |
The study was conducted in the Department of Biochemistry at SAIMS Medical College and Hospital, Indore, Madhya Pradesh. The study was approved by the Ethical Committee of the Institute. Informed consent was obtained from all patients. The study population comprised total 150 subjects in which 75 healthy control and 75 patients of T2DM, who were consecutively recruited from medicine OPD/Nephrology OPD of the hospital between September 2012 and November 2014, in which 61 patients was microalbuminuria and remaining was normoalbuminuria. However, they all are long-term diabetic patients more than 10 years. Healthy controls were enrolled from age- and sex-matched volunteers from the college and the hospital.
The Type 2 diabetic patients diagnosed by the Department of Medicine and Nephrology in SAIMS hospitals were included in this research work by their consent. A structured questionnaire regarding the demographic data such as age, sex, address, past and present history, duration of diabetes, height, and body weight were measured while wearing light weight clothing but not shoes. Blood pressure, smoking habit, renal disease, and hypertension were recorded for each patient. Diabetic patients suffering from any other medical problems were excluded from the study.
About 8 mL of blood sample was withdrawn from the anticubital vein following overnight fasting. The blood sample was collected in plain, fluoride, and ethylenediaminetetraacetic acid vacutainers. The blood sample was centrifuged for 15 min at 3000 rpm at room temperature. The serum was stored at 4°C for biochemical investigations. Blood sugar level was estimated by glucose oxidase and peroxidase method. Urea, creatinine, and uric acid were estimated by enzymatic method. Serum total cholesterol, HDL cholesterol, and TG were measured using commercially available kit of auto analyzer. LDL cholesterol and very low-density lipoprotein (VLDL) cholesterol concentration calculated using Friedewald formula. All biochemical investigation was done by fully automated analyzer Hitachi 902. The cystatin C levels of serum measured by turbidimetric immunoassay test (ACCUREX Biomedical Pvt. Ltd.). Microalbuminuria was tested with commercially available dipsticks "Micral-test" procured from the Roche Diagnostics India Pvt. Ltd.
The estimated GFR (eGFR) level was calculated using the modification of diet in renal disease (MDRD) formula: MDRD = 186 × (serum creatinine [mg/dL])−1.154 × age−0.203 .  A correction factor of 0.742 was used for women. The cystatin C estimated eGFR level was calculated by eGFR (mL/min) = 99.43 × (cystatin C in mg/L)−1.5837 . 
Subjects were divided into two groups, as under:
Group 1: Healthy control (n = 75).
Group 2: T2DM (n = 75).
Statistical analysis was done by using SPSS version 17 (SPSS Inc., 233, South Wacker Drive, 11 th Floor, Chicago, IL, 60606-6412). Results were expressed as mean ± standard deviation and were analyzed by unpaired Student's t-test. The level of significant was set as P < 0.05: Significant and P > 0.05: Nonsignificant.
| Results|| |
[Table 1] showed age, sex, body mass index (BMI), blood glucose level, and renal profile of Type 2 diabetic patients. There was no significant difference in age and sex between the two groups. BMI of Type 2 diabetic patients was found significantly increase from control. Blood glucose level of Group 2 nd was significantly increase compare to control (P < 0.001).
|Table 1: Renal profile of Type 2 diabetes mellitus patients and control (mean ± standard deviation)|
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[Table 2] showed lipid profile in Type 2 diabetic patients. In Group 2, we found total cholesterol, Triglycerides, VLDL cholesterol, and LDL cholesterol levels were significantly increase compare than control, whereas HDL cholesterol levels were significantly lower (P < 0.001) compare with control group.
|Table 2: Lipid profile of Type 2 diabetes mellitus patients and control (mean ± standard deviation)|
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[Table 3] showed serum cystatin C level and eGFR in Type 2 diabetes patients. Serum cystatin C level was significantly increase in Group 2 nd compared with control. However, eGFR were significantly lower (P < 0.001) in the Group 2 nd compared with control.
|Table 3: Serum cystatin C level estimated glomerular filtration rate in Type 2 diabetes mellitus patients and control (mean±standard deviation)|
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[Table 4] Pearson correlation of microalbuminuria with eGFR showed [Figure 1] significant linear relationship (r = 0.756, P < 0.001) and also showed [Figure 2] significant linear relationship with mAlb (r = 0.689, P < 0.001).
|Figure 1: Positive Pearson correlation between microalbuminuria and estimated glomerular filtration rate|
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|Figure 2: Positive Pearson correlation between microalbuminuria and cystatin C|
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|Table 4: Correlation of cystatin C with estimated glomerular filtration rate and microalbuminuria|
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| Discussion|| |
In this study, we aimed at evaluating the cystatin C levels of serum of T2DM patients. In T2DM normoalbuminuria patients, the cystatin C levels of serum were significantly increased. It was thought that this increment was probably due to the tubular phase before glomerular manifestation. This suggests that the cystatin C levels of serum are related to subclinical tubular impairment and can be an earlier measurable marker of renal involvement before the onset of albuminuria. In these patients, the cystatin C levels of serum were independent factors to predict eGFR estimated by the MDRD equation. The routine classical evaluation of DN includes the appearance of microalbuminuria, decreased creatinine clearance, and increased serum creatinine.  About 20-30% of patients with Type 2 diabetes accompanied by renal insufficiency showed normoalbuminuria. , Other biomarkers for estimation of renal function have been searched for and one of them was cystatin C.  In our study results confirmed that cystain C could be one of the additional tubular factors, which represent kidney state of diabetic patients.
There is growing evidence that abnormalities in lipid metabolism contribute to renal disease progression.  In present study, we found elevated triglyceride in diabetic patients as compare to control. Hyperlipoproteinemia is common in the Western population in DN patients. However Indian literature shows variable findings, Sharma et al.  and others demonstrated the absence of significant hyper lipoproteinemia in CKD while Alam and Bhatt.  and Rao et al.  found that significant abnormalities of lipoproteins in CKD. We also found hypercholesterolemia in CKD patients.
In T2DM patients, we found that HDL cholesterol levels were significantly low, and other parameters of lipoproteins were significantly high as compare to control group. The low level of HDL cholesterol which exerts antiatherogenic and antioxidative effect when present in sufficient amount is the key feature for oxidative stress status.  Protein identified as key component of the VLDL assembly process leads to increase level of TG and reduce levels HDL cholesterol in addition the elevation of free fatty acid and glucose in diabetes mellitus can decrease activity of lipoprotein lipase a pivotal enzyme in the removal of these lipoproteins from circulation that control the TG rich lipoproteins and HDL proteins. 
How abnormalities of lipid metabolism affects renal injury
It is well known that dyslipidemia is associated with renal injury in diabetic patients in early stage of renal disease. However, lipid abnormalities are involved in the pathogenesis of renal injury is still a matter of research. Some possible mechanisms of lipid-induced renal injury are as follows:
- Abnormal serum lipid level increases cell proliferation, matrix expansion, and cytokine formation by mesangial cells.  Increased cytokine formation could explain the infiltration of macrophages and foam cells observed in the glomeruli of diabetic patients with renal disease 
- Hyperlipidemia promotes the generation of ROS such as superoxide anion and hydrogen peroxide by monocytes,  mesangial cells may oxidize lipoproteins. Oxidized LDL particles further stimulate inflammatory cytokine production, serve as chemoattractants for macrophages and T-lymphocytes and increase apoptosis of podocytes, endothelial cells, and mesangial cells.  They also cause increased production of vasoactive substances as well as reduce production of vasodilators such as prostacyclin and nitric oxide, which results in an enhanced vasoconstriction by vasoconstrictor such as angiotensin II, endothelial-1, and plasminogen activator inhibitor-1 has significant vascular and renal consequences.  It is, therefore, possible that hypertension and dyslipidemia act in concert, each enhancing the other adverse effect on the kidneys.
| Conclusion|| |
The results of this study suggest that cystatin C estimation in serum is a useful, early detection marker, practical, noninvasive tool for the evaluation of renal disease in the course of diabetes patients. The present study also shows that significant lipoprotein abnormalities in CKDs and Type 2 diabetic patients when compared with control subjects.
The author is thankful to colleague and the participants for their valuable support and cooperation.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4]