Renal hyperfiltration (RHF) is a well-known phenomenon that occurs early in the development of nephropathy in patients with diabetes . RHF is thought to be followed by the development of proteinuria and progressive decline in renal function . Recently, it has been reported that RHF correlates with prediabetes [3–6], making it an early marker for the onset of diabetes. RHF is associated with renal prognosis and all-cause mortality in patients with diabetes .
The following points are important when investigating RHF: 1) the definition of RHF; 2) the method of measurement of glomerular filtration rate (GFR); and 3) whether GFR should be adjusted for body surface area (BSA).
1) There is no universal definition of RHF. Some studies have defined RHF as estimated glomerular filtration rate (eGFR) ≥120 ml/min , while others have used eGFR to define RHF as the 95th percentile or +2 SD in healthy subjects. According to a systematic review by Cachat et al., 30% of the studies did not justify the choice of the threshold values . From a methodological point of view, they argued that an age-and gender-matched control group should be used to define the RHF threshold.
2) The gold standard for GFR measurement is the inulin clearance test; however, it is not performed in epidemiological studies because it is a complex and time-consuming test. In clinical practice, eGFR, which is estimated from serum creatinine (Cr) values, is used as a measure of GFR. Different formulas are used to determine eGFR across regions and countries; notably, the serum Cr levels vary according to sex, age, race, and other factors. The Modification of Diet in Renal Disease Study (MDRD)-eGFR and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI)-eGFR formulas are the most commonly used formulas for estimating the GFR. In Japan, the MDRD-eGFR formula has been modified for use in the Japanese population and the modified formula is widely used . For men, eGFR (ml/min/1.73 m2) = (194 × Cr -1.094 × Age-0.287), and for women, it was further multiplied by 0.739. However, the MDRD-eGFR equation was developed mainly for chronic kidney disease (CKD) patients; therefore, when it was applied to patients with normal renal function (eGFR ≥ 60), the GFR was estimated to be low in several cases . The CKD-EPI equation was developed to improve on this point by using different equations for estimating the eGFR according to the serum Cr levels (Cr 0.9 for men and 0.7 for women) . The coefficient in the CKD-EPI formula modified for the Japanese population was 0.813 . The CKD-EPI equation has been noted to be a superior surrogate marker of GFR in patients with hyperfiltration ; additionally, the majority of studies on RHF based on eGFR used the CKD-EPI formula. However, studies on Japanese subjects are limited [4–6], and all of the studies used the MDRD-eGFR formula.
3) There is a clinicopathological syndrome associated with obesity called obesity-related glomerulopathy (ORG). The histological feature is glomerulomegaly, which may be due to increased metabolic demand, and functionally, there is an increase in the total glomerular filtration rate . ORG has also been postulated to be a kidney lesion caused by metabolic syndrome. However, studies evaluating the relationship between obesity and RHF are controversial because the results vary depending on whether the GFR is indexed with BSA. Most previous RHF studies that evaluated GFR have found a positive relationship between the BMI and RHF that disappears upon adjustment of GFR to BSA [16–18]. The indexed GFR with BSA in obese individuals may underestimate the GFR. There are few large cohort studies of RHF using estimated GFR that have evaluated its correlation with BMI.
In addition to RHF, non-alcoholic fatty liver disease (NAFLD) is an independent risk factor for cardiovascular diseases. Recently, apart from the general cardiorenal risk factors, such as obesity, hypertension, diabetes, and hyperlipidemia, a strong association between the presence and severity of NAFLD and the prevalence and incidence of CKD has been clarified . It has been suggested that insulin resistance may be a common pathogenic mechanism in NAFLD and CKD . However, only one study has indicated an association between NAFLD (diagnosed by ultrasound or MRI) and RHF . In that study, eGFR was converted to absolute value (mL/min) using the following equation: (eGFR mL/min/1.73 m2 * BSA)/1.73 m2. BSA was calculated using the DuBois and DuBois formula (BSA = 0.007184 × Weight0.425 × Height0.725) . Patients with NAFLD presented higher levels of eGFR and a significantly increased prevalence of hyperfiltration (73.2%) compared to the patients without NAFLD. Moreover, NAFLD and increased weight were associated with an increased probability of hyperfiltration.
The diagnosis of NAFLD is usually made by ultrasonography; however, as a simpler marker, the fatty liver index (FLI), which can be calculated from the BMI, waist circumference (WC), triglyceride (TG), and gamma-glutamyl transferase (GGT) was reported by Bedgni et al. , and validation studies have been carried out in each region since it was first reported. In addition, there have been several studies showing that FLI is not only a marker for NAFLD, but also a predictive marker for diabetes and CKD. However, the relationship between FLI and RHF has so far been reported in only one small cohort study in Finnish men . In that study, no correlation was noted between the FLI and RHF; both were independently associated with all-cause and cardiovascular mortality.
The aim of the present study was to assess the correlations of BMI and FLI with RHF in non-diabetic subjects, taking into account the age, sex, and BSA. For the purpose of this study, RHF was defined as the 95th percentile or higher of CKD-EPI eGFR by sex and age in healthy subjects at health check-ups. In addition, the analysis was also adjusted for BSA.