Chronicle of Diabetes Research and Practice

ORIGINAL ARTICLE
Year
: 2022  |  Volume : 1  |  Issue : 1  |  Page : 3--8

Insulin resistance in early and advanced diabetic kidney disease


Vedavati B Purandare1, Arjun L Kakrani2, Charan B Bale3, Shalbha Tiwari4, Ambika G Unnikrishnan1,  
1 Department of Diabetes and Endocrinology, Chellaram Diabetes Institute, Pune, Maharashtra, India
2 Department of Medicine, Dr. D. Y Patil Medical College, Hospital and Research Centre, Pune, Maharashtra, India
3 Department of Diabetes and Endocrinology, Chellaram Diabetes Institute; Department of Nephrology, Dr. D. Y Patil Medical College, Hospital and Research Centre, Pune, Maharashtra, India
4 Department of Research, Chellaram Diabetes Institute, Pune, Maharashtra, India

Correspondence Address:
Ambika G Unnikrishnan
Chellaram Diabetes Institute, Pune, Maharashtra
India

Abstract

Background: Insulin resistance (IR) is commonly seen in diabetic kidney disease (DKD) and could contribute to the progression of renal disease and cardiovascular risk. In this study, we aim to measure homeostasis model assessment IR (HOMA-IR) in DKD and see the effect of advancing kidney disease on HOMA IR. Material and Methods: We recruited 120 subjects with type 2 diabetes mellitus and divided them into people without kidney disease (controls; n = 20), early DKD (n = 40), and advanced DKD (n = 60). Biochemical tests including fasting plasma glucose and fasting serum C-peptide were done in 120 subjects. IR was calculated by the HOMA model in 109 subjects. Data were presented as median (interquartile range [IQR]). Univariable and multivariable analysis was done. Results: Median of HOMA-IR in the control group was 2.0 (IQR: 1.5–2.8; n = 20), early DKD group was 2.3 (1.8–2.9; n = 37), and advanced DKD group was 3.67 (1.6–3.9; n = 52). P = 0.03 indicated a significant increase in the HOMA IR with advancing kidney disease. Conclusion: In patients with DKD, with advancing kidney disease, there was a significant increase in the HOMA IR, a marker of IR. IR is a modifiable metabolic risk factor, and if it is managed by novel therapeutic ways, it might improve clinical outcomes in DKD.



How to cite this article:
Purandare VB, Kakrani AL, Bale CB, Tiwari S, Unnikrishnan AG. Insulin resistance in early and advanced diabetic kidney disease.Chron Diabetes Res Pract 2022;1:3-8


How to cite this URL:
Purandare VB, Kakrani AL, Bale CB, Tiwari S, Unnikrishnan AG. Insulin resistance in early and advanced diabetic kidney disease. Chron Diabetes Res Pract [serial online] 2022 [cited 2023 Jun 2 ];1:3-8
Available from: https://cdrpj.org//text.asp?2022/1/1/3/335259


Full Text



 Introduction



Diabetic kidney disease (DKD) is a clinical syndrome characterized by gradually increasing urine albumin excretion, rising blood pressure, and decline in glomerular filtration rate in absence of other causes.[1] DKD is associated with insulin resistance (IR) which increases the risk of cardiovascular disease and morbidity.[2] IR adversely impacts glucose control as well as kidney disease. A study published in 2018 showed that severe insulin-resistant type 2 diabetes mellitus (T2DM) patients have a higher risk of developing DKD and coronary artery disease.[3] Therefore, IR could become a therapeutic target in patients with diabetes and kidney disease.

IR is commonly seen as an early metabolic alteration in DKD.[2] There are various mechanisms contributing to IR in DKD. Factors such as obesity, metabolic acidosis, inflammation, oxidative stress, Vitamin D deficiency, and uremia contribute to IR in CKD patients.[4],[5],[6] Anemia, a hallmark of advanced renal disease, could be an additional contributing factor of IR in DKD[7]

In clinical practice, there is no single laboratory test to measure IR. Although the standard test to measure IR is hyperinsulinemic–euglycemic clamp, it is not feasible in routine practice.[8],[9] The most used methods to measure IR are the homeostasis model assessment of IR (HOMA-IR) and the quantitative insulin sensitivity check index.[9] HOMA is a method for assessing beta-cell function and IR from fasting glucose and insulin or C-peptide concentrations. HOMA-IR, though not validated in kidney disease, provides satisfactory estimates of IR in DKD.[10] Higher values of HOMA IR represent greater IR. The advantage of HOMA-IR is its simplicity as it requires only a few investigations such as fasting plasma glucose and fasting serum insulin or fasting serum C-peptide estimation.[11]

Understanding of DKD-related IR is of importance, and its role in a clinical setting requires documentation. Hence, we aimed to estimate IR in DKD and assess the effect of advancing kidney disease on HOMA-IR.

 Material and Methods



This study was an observational study carried at a tertiary care diabetes institute in the western part of India in Pune district of Maharashtra state. The study was approved by the institutional ethics committee. Written informed consent was obtained from participants.

Subject selection

Subjects with T2DM with or without kidney disease reporting to the outpatient department of a tertiary care diabetes institute were enrolled in the study. Subjects with type 1 diabetes mellitus, advanced liver disease, known malignancy, hemodynamic instability, hospitalized patients, and any other critical illness were excluded from the study. Fasting blood samples were collected for the estimation of fasting plasma glucose, glycated hemoglobin (A1c), serum creatinine, serum insulin, and serum C-peptide levels. Urine spot sample was collected for the measurement of urine microalbumin and urine creatinine for urine albumin-to-creatinine ratio (ACR). Participants were enrolled using the purposive sampling method.

Laboratory investigations

Plasma glucose level (mg/dl) was measured by the glucose method used on the Roche Cobas Integra 400 clinical chemistry system. Glycated hemoglobin (A1c) (%) was measured by high-performance liquid chromatography. Serum creatinine (mg/dl) was measured by Jaffe's method enzymatic colorimetric method. The value of estimated glomerular filtration rate (eGFR) (ml/min/1.73 m2) was calculated by CKD- EPI. Serum insulin(μU/mL) and serum C-peptide levels (ng/mL) were measured by the Chemiflex method on Abbott Architect 1000i instrument. Urine microalbumin was measured by the MAUD method used on the Roche Cobas Integra 400 clinical chemistry system and urine creatinine was measured by enzymatic colorimetric method on the Roche Cobas Integra 400 clinical chemistry system.

Study groups

The staging of CKD was done based on the serum creatinine and eGFR. Urine ACR was used to categorize subjects into control group (ACR below 30 mg/g) and Stage 1 CKD group (ACR above 30 mg/g).

Control group included subjects with T2DM without evidence of kidney disease, i.e., ACR <30 mg/g and eGFR >90 ml/min/1.73 m2.

As per the National Kidney Foundation-Kidney Disease Outcomes Quality Initiative guidelines, CKD in diabetes subjects is classified into five stages with a declining glomerular filtration rate. Participants from Stage 1 to Stage 5 CKD were recruited in the study.

A total number of participants enrolled were 120. Subjects in the control group were 20 and subjects with kidney disease were 100. Patients were divided into three groups for the purpose of statistical analysis [Figure 1].{Figure 1}

Group 1 – Control group (n = 20) – T2DM without kidney disease – e GFR ≥90 ml/min/1.73 m2 and ACR below 30 mg/g.

Group 2 – Early kidney disease group (n = 40) – Stage 1 CKD (e GFR ≥90 ml/min/1.73 m2

and ACR above 30 mg/g) and Stage 2 CKD (eGFR 60–89 ml/min/1.73 m2). In this group, eGFR of subjects was above 60 ml/min/1.73 m2.

Group 3 – Advanced kidney disease (n = 60) – Stages 3, 4, and 5 – eGFR of subjects was below 60 ml/min/1.73 m2. Out of 60 subjects in Group 3, ten were on hemodialysis.

Measurement of homeostasis model assessment of insulin resistance

The HOMA computer model (HOMA 2 calculator) was used to calculate HOMA IR. HOMA IR was calculated by HOMA 2 calculator by entering fasting plasma glucose value (mg/dl) and fasting C-peptide value (ng/ml).

Out of 120 total subjects, HOMA IR could be calculated in 109 subjects, as shown in [Figure 1] (20 in control and 89 in kidney disease group). C-peptide value was either low or high in the three subjects in the early kidney disease group and eight subjects in the advanced kidney disease. Hence, we could get HOMA IR in 109 subjects.

Data analysis

Statistical analysis was carried out using STATA 14.2 software (StataCorp LLC,4905 Lakeway Drive, College Station, Texas 77845-4512,USA). Medians and interquartile range (IQR) of HOMA IR in the three groups were compared. Data were presented as median (IQR). Univariable and multivariable analysis was done. Multivariate regression analysis was done to ascertain the association between various parameters and to minimize the effect of confounders. P < 0.05 was considered statistically significant.

 Results



Baseline characteristics of cases and controls are depicted in [Table 1]. There was a significant difference in the median age of the controls, early DKD, and advanced DKD subjects (P < 0.001). There was variable representation of gender in controls, early DKD, and advanced DKD, respectively (male: female – 2:3; 3:5; and 2:1; P = 0.008). There was a significantly higher number of male participants in the advanced DKD group. The median duration of diabetes in the control, early DKD, and advanced DKD was 5, 14, and 20 years, respectively. Systolic blood pressure was significantly higher in the advanced DKD as compared to the control and early DKD group. Past history of hypertension, coronary artery disease, retinopathy, and neuropathy was statistically higher in the advanced DKD group as compared to the control and the early kidney disease group (P < 0.001).{Table 1}

Antidiabetic therapy of participants included oral antidiabetic medications and insulin. Majority of the patients in the control group (95%) and the early DKD (98%) were taking metformin and 17% of patients in the advanced DKD group were on metformin. A statistically significant number of patients in the advanced DKD group (75%) were taking insulin as compared to the control group (P = 0.006). The markers of glycemic control fasting plasma glucose and HbA1C in the control, early DKD, and late DKD groups were similar. The difference was statistically insignificant. The median serum C-peptide levels were 2.3 ng/ml, 2.7 ng/ml, and 3.6 ng/ml, respectively, in control, early DKD, and late DKD group, which was statistically significant. Patients in the advanced DKD group had significantly lower hemoglobin levels (P = 0.0001).

Median (IQR) of HOMA-IR in the control group was 2.0 (IQR: 1.5–2.8; n = 20), the early DKD group was 2.3 (1.8–2.9; n = 37), and the advanced DKD group was 3.67 (1.6–3.9; n = 52). P = 0.03 indicated a significant increase in the HOMA IR with advancing kidney disease.

The box plot analysis in [Figure 2] shows the HOMA IR in control group, in the early DKD, and in the advanced DKD group.{Figure 2}

Effect of baseline characteristics on homeostasis model assessment of insulin resistance

As mentioned in [Table 2] in the univariable analysis when the control group was considered as reference and it was compared with early and advanced DKD, P value was 0.64 and 0.005, respectively. Hence, the difference in HOMA IR was statistically significant in the control group when compared with the advanced DKD group. In the multivariable analysis [Table 2] also, the P value was significant (P = 0.004); hence, the confounding factors did not have any impact on the results. Based on these observed data, the study is powered at 93%.{Table 2}

 Discussion



In this study, IR was significantly higher in the advanced DKD group as compared to the control group. Advanced DKD subjects had higher fasting serum C-peptide levels as compared to control group (P = 0.01). Serum C-peptide is a marker of endogenous insulin production. Higher serum C-peptide in advanced DKD group may not mean that beta-cell secretory function is better in patients with advanced kidney disease, but this could be because of decrease in the insulin and C-peptide clearance with decreasing GFR.

HOMA IR is used in various studies to assess the prevalence and severity of IR in CKD with or without diabetes. Kanauchi et al. and Kobayashi et al. published prevalence studies of IR using HOMA IR in the Japanese patients with moderate-to-severe CKD. As per these studies, the prevalence of IR in CKD was 30 and 44%, respectively.[12],[13] In the study published by Kobayashi et al., insulin-resistant group was defined as patients with HOMA-IR 2.0 and more, and the insulin-sensitive group as those with HOMA-IR <2.0.[13]

Dogra et al. studied the association of IR and vascular dysfunction in CKD. In this study, 105 patients with Stage 3–5 CKD were recruited, of which 22% of patients had T2 DM, HOMA-IR was used to assess IR in patients. The study showed that IR was associated with vascular dysfunction in patients with CKD.[14] Chan et al. studied the association between IR and vascular function in CKD. Seventy-one patients with Stage 3–4 CKD subjects (type 2 DM, 22.5%) were studied. CKD subjects with HOMA-IR scores above the median had significantly higher body mass index and waist circumference. They also had higher triglycerides with lower high-density lipoprotein levels.[15] A cohort study in patients on peritoneal dialysis confirmed HOMA-IR as an independent predictor of CV mortality in end-stage kidney disease.[16] A study comparing HOMA IR in subjects with end-stage renal disease (ESRD) with or without diabetes published by Bodlaj et al. showed that median HOMA-IR was significantly higher in the ESRD patients with diabetes than in the ESRD patients without diabetes (6.3 [range 0.7–61.7] vs. 2.4 [range 0.3–5.7]; P < 0.001). Systolic blood pressure was significantly higher in patients with higher HOMA-IR. Prevalence of vascular disease was significantly higher in patients with diabetes with higher HOMA-IR than in those with lower HOMA-IR. The prevalence of vascular diseases is associated with higher HOMA-IR in ESRD patients also.[17]

Viswanathan et al. studied 128 subjects divided into four groups: control group, normoalbuminuria group, microalbuminuria group, and macroalbuminuria group. IR was calculated using the HOMA method. This cross-sectional study showed that mean HOMA IR increased significantly with increasing albuminuria and decreasing renal function.[18] A study published by El-Messallamy et al. demonstrated a strong relationship between IR and CKD.[19]

Fragoso et al. followed 119 DKD patients (Stages 2–4) for 56 months without a history of cardiovascular disease at the baseline. IR was estimated by the HOMA-IR. In this study, IR was found to be an important risk factor for cardiovascular morbidity and progression of kidney disease in DKD.[20] A study published by Akalın et al. demonstrated that IR was higher in patients with chronic kidney disease compared to healthy population.[21]

In an observational, prospective, cohort study recruiting 15,773 patients with T2DM, insulin sensitivity was assessed as estimated glucose disposal rate (eGDR), which was validated against the euglycemic–hyperinsulinemic clamp technique. This study investigated the ability of IR, as assessed as eGDR, in predicting mortality in T2DM. Participants in the lowest eGDR tertile (highest IR) had a worse CVD risk profile and the highest prevalence of DKD and prior CVD events, as compared with those in the highest eGDR tertile (lowest IR).[22] Similar studies are needed in the Indian population, including newer parameters such as adiponectin-to-leptin ratio which is emerging as an important marker of IR.[23]

Taken together, these studies suggest a clustering of cardiovascular risk factors as well as vascular complications with IR in DKD.

One limitation of the study is its small sample size. However, despite this limitation, the study showed a significant association between IR and DKD. Another limitation is that the other tests such as clamp studies could not be conducted to study IR in this population.

Importantly, our study highlights that established insulin sensitizers such as metformin or newer insulin sensitizers be studied to ascertain their effects on IR as well as vascular outcomes in people with DKD.

 Conclusion



IR calculated by HOMA IR was significantly higher in patients with diabetes with late kidney disease and showed an increasing trend with advancing kidney disease.

Financials support and sponsorship

Chellaram Foundation.

Conflicts of interest

There are no conflicts of interest.

References

1American Diabetes Association. 11. Microvascular complications and foot care: Standards of Medical Care in Diabetes-2021. Diabetes Care 2021;44 Suppl 1:S151-67.
2Spoto B, Pisano A, Zoccali C. Insulin resistance in chronic kidney disease: A systematic review. Am J Physiol Renal Physiol 2016;311:F1087-108.
3Ahlqvist E, Storm P, Käräjämäki A, Martinell M, Dorkhan M, Carlsson A, et al. Novel subgroups of adult-onset diabetes and their association with outcomes: A data-driven cluster analysis of six variables. Lancet Diabetes Endocrinol 2018;6:361-9.
4Kopple JD, Kalantar-Zadeh K, Mehrotra R. Risks of chronic metabolic acidosis in patients with chronic kidney disease. Kidney Int Suppl 2005;95:S21-7.
5Mak RH. 1,25-Dihydroxyvitamin D3 corrects insulin and lipid abnormalities in uremia. Kidney Int 1998;53:1353-7.
6Marshall S, Podlecki DA, Olefsky JM. Low pH accelerates dissociation of receptor-bound insulin. Endocrinology 1983;113:37-42.
7Mak RH. Correction of anemia by erythropoietin reverses insulin resistance and hyperinsulinemia in uremia. Am J Physiol 1996;270:F839-44.
8DeFronzo RA, Tobin JD, Andres R. Glucose clamp technique: A method for quantifying insulin secretion and resistance. Am J Physiol 1979;237:E214-23.
9Pham H, Utzschneider KM, de Boer IH. Measurement of insulin resistance in chronic kidney disease. Curr Opin Nephrol Hypertens 2011;20:640-6.
10Wallace TM, Levy JC, Matthews DR. Use and abuse of HOMA modeling. Diabetes Care 2004;27:1487-95.
11Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: Insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985;28:412-9.
12Kanauchi M, Kimura K, Akai Y, Saito Y. Insulin resistance and pancreatic beta-cell function in patients with hypertensive kidney disease. Nephrol Dial Transplant 2004;19:2025-9.
13Kobayashi H, Tokudome G, Hara Y, Sugano N, Endo S, Suetsugu Y, et al. Insulin resistance is a risk factor for the progression of chronic kidney disease. Clin Nephrol 2009;71:643-51.
14Dogra G, Irish A, Chan D, Watts G. Insulin resistance, inflammation, and blood pressure determine vascular dysfunction in CKD. Am J Kidney Dis 2006;48:926-34.
15Chan DT, Watts GF, Irish AB, Ooi EM, Dogra GK. Insulin resistance and the metabolic syndrome are associated with arterial stiffness in patients with chronic kidney disease. Am J Hypertens 2013;26:1155-61.
16Li Y, Zhang L, Gu Y, Hao C, Zhu T. Insulin resistance as a predictor of cardiovascular disease in patients on peritoneal dialysis. Perit Dial Int 2013;33:411-8.
17Bodlaj G, Berg J, Pichler R, Biesenbach G. Prevalence, severity and predictors of HOMA-estimated insulin resistance in diabetic and nondiabetic patients with end-stage renal disease. J Nephrol 2006;19:607-12.
18Viswanathan V, Tilak P, Meerza R, Kumpatla S. Insulin resistance at different stages of diabetic kidney disease in India. J Assoc Physicians India 2010;58:612-5.
19El-Messallamy FA, El-Ashmawy HM, El Shabrawy AM, Radwan SE. Proinsulin/insulin ratio as a predictor of insulin resistance in patients with diabetic nephropathy. Diabetes Metab Syndr 2019;13:2057-60.
20Fragoso A, Mendes F, Silva AP, Neves PL. Insulin resistance as a predictor of cardiovascular morbidity and end-stage renal disease. J Diabetes Complications 2015;29:1098-104.
21Akalın N, Köroğlu M, Harmankaya Ö, Akay H, Kumbasar B. Comparison of insulin resistance in the various stages of chronic kidney disease and inflammation. Ren Fail 2015;37:237-40.
22Penno G, Solini A, Orsi E, Bonora E, Fondelli C, Trevisan R, et al. Insulin resistance, diabetic kidney disease, and all-cause mortality in individuals with type 2 diabetes: A prospective cohort study. BMC Med 2021;19:66.
23Jung CH, Rhee EJ, Choi JH, Bae JC, Yoo SH, Kim WJ, et al. The relationship of adiponectin/leptin ratio with homeostasis model assessment insulin resistance index and metabolic syndrome in apparently healthy Korean male adults. Korean Diabetes J 2010;34:237-43.