Insulin resistance is associated with incident chronic kidney disease in population with normal renal function

Background

Insulin resistance is prevalent in chronic kidney disease and may accelerate the progression of chronic kidney disease. This study aimed to investigate whether insulin resistance is associated with the development of incident chronic kidney disease in a population with normal renal function.

Methods

A total of 3,331 participants from a community-based cohort with normal renal function were prospectively analyzed. We determined the relationship of insulin resistance indices with the incident chronic kidney disease using the Cox proportional hazard model and Kaplan-Meier survival analysis.

Results

During a mean follow-up of 11.03 ± 4.22 years, incident chronic kidney disease occurred in 414 participants (12.4%). The high homeostasis model assessment-insulin resistance level group had an increased risk of incident chronic kidney disease (hazard ratio [HR], 1.40; 95% confidence interval [CI], 1.13-1.74; p = 0.002) compared to the normal group after adjustment for age, sex, history of hypertension, body mass index, total cholesterol, alcohol drinking status, smoking status, and baseline estimated glomerular filtration rate. The risk of incident chronic kidney disease also increased with the lower quantitative insulin sensitivity check index level (HR, 0.62; 95% CI, 0.41-0.92; p = 0.02) and higher leptin-adiponectin ratio level (HR, 1.23; 95% CI, 1.06-1.42; p = 0.006).

Conclusion

Higher insulin resistance indices are associated with the incidence of chronic kidney disease. Our data suggest that increased insulin resistance may be involved in the development of incident chronic kidney disease in a population with normal renal function.

Relationship between asymmetric dimethylarginine in umbilical cord plasma and birth weight follows a U-shaped curve

Asymmetric dimethylarginine (ADMA) is a nonselective nitric oxide (NO) synthase inhibitor associated with cardiovascular and metabolic disorders. NO regulates placental blood flow, which plays an important role in fetal growth. Many epidemiological studies have disclosed that restricted fetal growth is associated with an increased risk of insulin resistance in adult life. We studied the relationship between ADMA in cord blood and birth size. Nine small for gestational age (SGA) and 32 appropriate for gestational age (AGA) infants were studied. Their cord plasma ADMA, insulin, insulin-like growth factor-1 (IGF-1), and adipocytokine levels were determined using enzyme-linked immunosorbent assays. The relationship between birth weight and ADMA levels followed a U-shaped curve rather than inverse linear associations expected over a full range of birth weight distribution. ADMA positively correlated with birth weight in the AGA group (p<0.001, R=0.590), and inversely correlated with birth weight in the SGA group (p<0.05, R=-0.741). ADMA inversely correlated with adiponectin (p<0.05, R=-0.289) and quantitative insulin sensitivity check index (QUICKI) (p<0.05, R=-0.294) in all subjects, and did not correlate with nitrogen oxides (NO_X). Insulin, IGF-1, leptin, adiponectin and QUICKI were lower in the SGA than the AGA group. Plasma ADMA levels in cord blood may be a marker of fetal growth and insulin resistance.

Optimal cutoff points for HOMA-IR and QUICKI in the diagnosis of metabolic syndrome and non-alcoholic fatty liver disease: A population based study

AIMS

The present study was carried out to determine the optimal cutoff points for homeostatic model assessment (HOMA-IR) and quantitative insulin sensitivity check index (QUICKI) in the diagnosis of metabolic syndrome (MetS) and non-alcoholic fatty liver disease (NAFLD).

METHODS

The baseline data of 5511 subjects aged ≥18years of a cohort study in northern Iran were utilized to analyze. Receiver operating characteristic (ROC) analysis was conducted to determine the discriminatory capability of HOMA-IR and QUICKI in the diagnosis of MetS and NAFLD. Youden index was utilized to determine the optimal cutoff points of HOMA-IR and QUICKI in the diagnosis of MetS and NAFLD.

RESULTS

The optimal cutoff points for HOMA-IR in the diagnosis of MetS and NAFLD were 2.0 [sensitivity=64.4%, specificity=66.8%] and 1.79 [sensitivity=66.2%, specificity=62.2%] in men and were 2.5 [sensitivity=57.6%, specificity=67.9%] and 1.95 [sensitivity=65.1%, specificity=54.7%] in women respectively. Furthermore, the optimal cutoff points for QUICKI in the diagnosis of MetS and NAFLD were 0.343 [sensitivity=63.7%, specificity=67.8%] and 0.347 [sensitivity=62.9%, specificity=65.0%] in men and were 0.331 [sensitivity=55.7%, specificity=70.7%] and 0.333 [sensitivity=53.2%, specificity=67.7%] in women respectively.

CONCLUSION

Not only the optimal cutoff points of HOMA-IR and QUICKI were different for MetS and NAFLD, but also different cutoff points were obtained for men and women for each of these two conditions.

Dyslipidemia, but not hyperglycemia and insulin resistance, is associated with marked alterations in the HDL lipidome in type 2 diabetic subjects in the DIWA cohort: impact on small HDL particles

In this study we have used mass spectrometry in order to characterize the HDL lipidome in three groups of women from the DIWA cohort; one control group, plus two groups with type 2 diabetes with insulin resistance; one dyslipidemic and one normolipidemic. The aim was to investigate whether dyslipidemia is required in addition to insulin resistance for the occurrence of an altered HDL lipidome, which in turn might impact HDL functionality. The dyslipidemic type 2 diabetic subjects were distinguished by obesity, hypertriglyceridemia with elevated apoC3, low HDL-cholesterol and chronic low grade inflammation. In a stepwise multivariate linear regression analysis, including biomarkers of dyslipidemia and insulin resistance as independent variables, only dyslipidemia showed a significant correlation with HDL lipid classes. Small HDL-particles predominated in dyslipidemic subjects in contrast to the normolipidemic diabetic and control groups, and were enriched in lysophosphatidylcholine (+13%), a product of proinflammatory phospholipases, and equally in two core lipids, palmitate-rich triacylglycerols and diacylglycerols (+77 %), thereby reflecting elevated CETP activity. Dyslipidemic small HDL particles were further distinguished not only as the primary carrier of ceramides, which promote inflammation and insulin resistance, but also by a subnormal plasmalogen/apoAI ratio, consistent with elevated oxidative stress typical of type 2 diabetes. From these data we conclude that in type 2 diabetes, dyslipidemia predominates relative to hyperglycemia for the occurrence of an altered HDL lipidome. Furthermore, dyslipidemia alters the cargo of bioactive lipids, with implications for HDL function.

Surrogate markers of insulin resistance: A review

Insulin resistance is a hallmark of obesity, diabetes, and cardiovascular diseases, and leads to many of the abnormalities associated with metabolic syndrome. Our understanding of insulin resistance has improved tremendously over the years, but certain aspects of its estimation still remain elusive to researchers and clinicians. The quantitative assessment of insulin sensitivity is not routinely used during biochemical investigations for diagnostic purposes, but the emerging importance of insulin resistance has led to its wider application research studies. Evaluation of a number of clinical states where insulin sensitivity is compromised calls for assessment of insulin resistance. Insulin resistance is increasingly being assessed in various disease conditions where it aids in examining their pathogenesis, etiology and consequences. The hyperinsulinemic euglycemic glucose clamp is the gold standard method for the determination of insulin sensitivity, but is impractical as it is labor- and time-intensive. A number of surrogate indices have therefore been employed to simplify and improve the determination of insulin resistance. The object of this review is to highlight various aspects and methodologies for current and upcoming measures of insulin sensitivity/resistance. In-depth knowledge of these markers will help in better understanding and exploitation of the condition.