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Saudi Journal of Kidney Diseases and Transplantation
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Table of Contents   
ORIGINAL ARTICLE  
Year : 2019  |  Volume : 30  |  Issue : 3  |  Page : 648-654
Creatinine and cystatin C-based evaluation of renal function among obese subjects in Benin City, Nigeria


1 Department of Chemical Pathology, Obafemi Awolowo University, Ile-Ife, Nigeria
2 Department of Medical Rehabilitation, Obafemi Awolowo University, Ile-Ife, Nigeria
3 Department of Chemical Pathology, University of Benin Teaching Hospital, Benin City, Nigeria

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Date of Submission14-Jan-2018
Date of Decision03-Apr-2018
Date of Acceptance04-Apr-2018
Date of Web Publication26-Jun-2019
 

   Abstract 


Obesity is a recognized worldwide epidemic with increasing prevalence in developing nations. Studies have shown that obesity is an independent risk factor for the development of chronic kidney disease (CKD) besides its link with diabetes mellitus and hypertension. We evaluated the renal status of obese patients using both the established [creatinine (Cr)] and new (cystatin C) markers of renal function. This was a cross-sectional study. Fifty-nine consenting adults attending the clinic for routine medical checks were recruited for this study. They were divided into obese and non-obese based on their body mass index. Serum from specimens collected were assayed for Cr and cystatin C. CKD equations were used to estimate glomerular filtration rate based on Cr (eGFR-Cr), cystatin C (GFR-Cystatin), and Cr/cystatin C (GFRCr/cystatin) while modification of diet in renal disease equation was also used to eGFR-Cr. The eGFR results generated were compared in assessing renal function. The obese participants and the controls were age-matched (50.6 ± 9.7 vs. 50.7 ± 7.8 years, P = 0.2). The obese participants had a significantly higher serum cystatin C (1.3 ± 0.7 vs. 0.9 ± 0.4 mg/L, P < 0.001) and significantly lower eGFR-cystatin C (75.4 ± 38.9 mL/min/1.73 m2 vs. 90.9 ± 25.1 mL/min/1.73 m2, P < 0.001) than the controls, respectively. There was a significant difference between the eGFR-Cr and eGFR-cystatin C in the obese participants (97.4 ± 21.4 vs. 75.4 ± 38.9 mL/min/1.73 m2), P = 0.019). The results showed that mild renal impairment exists among obese participants. Routine assessment is recommended to pre-empt deterioration in renal function. Cystatin C appears to be a better marker of renal function in obesity than serum Cr.

How to cite this article:
Alaje AK, Adedeji TA, Adedoyin AR, Idogun SE. Creatinine and cystatin C-based evaluation of renal function among obese subjects in Benin City, Nigeria. Saudi J Kidney Dis Transpl 2019;30:648-54

How to cite this URL:
Alaje AK, Adedeji TA, Adedoyin AR, Idogun SE. Creatinine and cystatin C-based evaluation of renal function among obese subjects in Benin City, Nigeria. Saudi J Kidney Dis Transpl [serial online] 2019 [cited 2019 Nov 22];30:648-54. Available from: http://www.sjkdt.org/text.asp?2019/30/3/648/261339



   Introduction Top


The prevalence of obesity is increasing worldwide and there is an effort to curb the epidemic.[1] Obesity was once considered as a disease of the affluence commonly seen in the developed countries of the world.[2] However, there is a rising prevalence of obesity in the developing countries. This may be due to increasing level of education, urbanization, improved socioeconomic status, and westerni-zation.[3]

Obesity has been linked to so many clinical conditions including cardiovascular diseases, type 2 diabetes mellitus (DM), nonalcoholic fatty liver disease, obstructive sleep apnea, chronic kidney disease (CKD), and some malignancies.[4] Obesity is directly and indirectly linked with CKD through different but related mechanisms. Directly, obesity impacts the renal hemodynamics by increasing the glomerular filtration rate (GFR) and renal blood flow with afferent arteriole dilation and increased albumin excretion clinically evident as increased albuminuria. Stimulation of renin-angiotensin aldosterone system and increased renal sympathetic tone all contribute to and aggravate the hemodynamic changes.[6],[7],[8],[9] Obesity indirectly causes CKD through the metabolic syndrome and development of type 2 DM.[10],[11],[12],[13] Accumulation of adipose tissue functions as endocrine and exocrine glands-producing cytokines and growth factors involved in mesangial cell expansion and podocyte injury of the kidneys.[11],[12],[13],[14],[15],[16],[17],[18] In a study, it was reported that body mass index (BMI) >25 kg/m2 was associated with a 3-fold risk of developing CKD even after correction for hypertension and DM.[19] The coexistence of diabetes and obesity double the risk of new-onset kidney disease.[20]

Creatinine (Cr) is an endogenous marker routinely used to assess GFR based on its renal clearance or GFR equations.[21] However, Cr is limited in its use as a renal marker in that it is not sensitive to small variations in GFR. This necessitated the evaluation of other endogenous markers like cystatin C.[22] Cystatin C is a low-molecular-weight protein of 12 KDa synthesized by all nucleated cells, it is freely filtered by the glomeruli and neither reabsorbed nor secreted by the renal tubules. Previous reports on the utility of cystatin C as a renal marker suggested that cystatin C is more sensitive and superior to Cr for estimating GFR.[23] Therefore, the increasing prevalence of obesity in Nigeria would necessitate evaluation of the renal status of these patients as there is a parallel increase of type 2 DM and CKD using the routine (creatinine) and new (cystatin C) makers of GFR.


   Materials and Methods Top


This was a cross-sectional study carried out at the Centre for Disease Control of the University of Benin Teaching Hospital, Benin City, South-South, Nigeria. The clinic offers primary care services and routine medical screening for adults with no form of referral needed. The laboratory investigations offered at the clinic include a complete blood count, fasting plasma glucose (FPG), urinalysis, electrolytes/urea/Cr, lipid profile, prostate-specific antigen, and  Pap smear More Details. The clinic is highly subsidized making it affordable for patients from different socioeconomic class.

The participants recruited for this study were normotensive, euglycemic, normocholestero-lemic overweight groups (obese adults) aged 18-60 years not on any routine medication but attending the clinic for routine medical examination. Those with anemia were excluded from the study and most of the females were peri-menopausal. They were compared with age- and sex-matched controls which were equally normotensive, euglycemic and normocholeste-rolemic adults with normal weight.

Fifty-nine consenting adults were recruited including 27 males and 32 females using a simple random sampling. A self-administered questionnaire was given to each subject to obtain information on their demographic, past medical, family, and social history.

Ethical clearance was obtained from the Institutional Research and Ethics Committee. Informed written consent was obtained from each subject. Confidentiality and privacy were ensured by not indicating the names of the participants on the questionnaire, and only the investigators had access to the data.

A physical medical examination was carried out on each participant. The resting blood pressure (BP) of each participant was mea-sured with an Accosson® mercury sphygmo-manometer using standard techniques. Weight of each participant was taken and the average calculated while the height was measured using a stadiometer. BMI was calculated as weight in kg divided by height in kg/m2. BMI considered values >30 as obese, 25–29.9 as overweight, and 18.5–24.9 as normal weight. A nonstretching tape was used to measure the waist circumference of each subject at the level of the umbilicus.

Five milliliter of blood was collected from each participant into a plain bottle for crea-tinine and cystatin C assays. Blood specimen was allowed to clot and retract for 4 h after which it was spun at 1500 gravity (g) for 10 min. The supernatant was separated from red cells using a Pasteur’s pipette into a plain tube and stored at -20°C (temperature was monitored and charted twice daily) until sufficient samples were pooled for analysis. Serum Cr was assayed using the Kinetic Jaffe method and absorbance read by Spectrumlab 22PC spectrophotometer. Cystatin C was assayed using the immunoturbidimetric method. Estimated GFR (eGFR) was calculated for each analyte using eGFR equations by CKD- epidemiology collaboration (EPI). The eGFR results generated were compared in assessing renal function.

Data were analyzed using the Statistical Package for the Social Sciences (SPSS) version 22.0 (IBM Corp., Armonk, NY, USA). Numerical variables were expressed as mean and standard deviations. Means were compared using the Student’s /-test. Pearson’s correlation test was used for correlation study. The value of P < 0.05 was taken as the cutoff level for significance.


   Results Top


[Table 1] shows the demographic characteristics of the study population in obese and non-obese individuals. The mean age of the participants and controls were 50.6 ± 9.7 years and 52.7 ± 7.8 years, respectively (P = 0.2). The male-to-female ratio was 1:1.6 and 1.1:1 in participants and controls, respectively. The participants had a significantly higher BMI (32.4 ± 5.5 vs. 23.4 ± 2.4 kg/m2, P < 0.001) but nonsignificantly higher abdominal circumference (104.1 ± 13.6 cm vs. 90.6 ± 8.5 cm, P = 0.18) than that of the controls.
Table 1: Demography of study participants and controls.

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Majority of the participants (48.3%) were overweight with 31% in the mild obesity class and 13.8% were morbidly obese [Table 2].
Table 2: Frequency distribution of participants based on body mass index

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The mean systolic and diastolic blood pressure for the participants and controls were 121.4 ± 9.2 versus 116.7 ± 12.4 mm Hg (P = 0.27) and 81.5 ± 6.8 versus 77.9 ± 7.6 mm Hg (P = 0.07), respectively. The participants had a nonsignificant higher mean FPG (5.5 ± 1.2 vs. 4.8 ± 1.0 mmol/L; P = 0.67) and total choles terol (4.3 ± 1.1 vs. 4.1 ± 1.0; P = 0.37) [Table 3].
Table 3: Measured parameters of participants and controls.

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The were no statistically significant differences in the mean serum Cr (93.0 ± 29.4 vs. 91.4 ± 24.4 μmol/L; P = 0.25), eGFR-CroKD-EPI (97.4 ± 21.4 vs. 99.3 ± 22.4 mL/min/1.73 m2; P = 0.73), and eGFR-CrMDRD (92.0 ± 25.3 vs. 97.5 ± 23.6 mL/min/1.73 m2) of the participants and controls. However, the participants had a significantly higher mean serum Cystatin C (1.3 ± 0.7 vs. 0.9 ± 0.4 mg/L; P < 0.01), lower eGFR-Cystatin C (77.4 ± 38.9 vs. 91.0 ± 25.1 mL/min/1.73 m2; P < 0.01), and lower CKD-EPI derived eGFRCr and Cystatin C (83.8 ± 30.5 vs. 95.2 ± 19.5 mL/min/1.73 m2) than the controls [Table 3].

eGFR-Cr(CKD-EPI) was compared with that of Cystatin C and a statistically significant difference was observed for only the participants (94.7 ± 24.0 mL/min/1.73 m2 and 77.3 ± 38.4 mL/min/1.73 m2; P = 0.019) [Table 4]. A significant difference was also observed among the participants when eGFR-Cr(MDRD) was compared with eGFR-Cystatin C (92.0 ± 25.3 mL/min/1.73 m2 vs. 77.3 ± 38.4 mL/min/1.73 m2; P= 0.046). The eGFR(CKD-EPI) using both serum Cr and Cystatin C was significantly lower than eGFR-CrCKD-EPI (83.8 ± 30.5 mL/ min/1.73 m2 vs. 94.7 ± 24.0 mL/min/ 1.73m2; P = 0.024) and significantly higher than eGFR-Cystatin C (83.8 ± 30.5 mL/min/ 1.73 m2 vs. 77.3 ± 38.4 mL/min/1.73 m2; P = 0.018) [Table 4]. The controls showed a significant difference between GFR-CrCKD-EPI and GFR- CrMDRD (99.3 ± 22.4 mL/min/1.73 m2 and 97.5 ± 23.6 mL/min/1.73 m2; P = 0.04) [Table 4].
Table 4: Comparison of glomerular filtration rate equations among participants and controls.

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   Discussion Top


The finding of higher serum Cr and cystatin C in our obese nondiabetic participants than the controls corroborate the earlier reports that obesity is an independent risk for the development of CKD along with other diseases such as diabetes, hypertension, cardiovascular disease, metabolic syndrome, and certain malignancies.[24],[25]

In this study, the obese participants were all normotensive. This is probably because most of the participants were in class 1 obesity category. The participants having higher mean FPG than the upper reference limit is suggestive of evolving impairment in glucose metabolism (dysglycemia observed in obesity) which may represent an early stage in disease progression to hyperglycemia as associated with metabolic syndrome. This is further evident by some of our subjects (n = 12) having impaired fasting glucose (defined as 6.1–6.9 mmol/L). Furthermore, our positive findings of some components of diagnostic criteria for metabolic syndrome in our participants including elevated FPG, increase abdominal circumference, elevated systolic/diastolic BP and high BMI are suggestive of existing Raeven’s syndrome. The mean FPG observed in this study is similar to those reported in previous studies among obese participants.[26],[27]

The renal function assessment of our subjects as evaluated by serum Cr showed that these patients had a preserved renal function in contrast to serum cystatin C. This finding supports earlier reports on the limitation of serum Cr in evaluating renal function.[28],[29] It was reported that >50% of renal function would have been lost before a rise in serum Cr is detected.[21] This prevents most patients to be detected in the early stages of CKD, especially in our own environment where the provision of health services is limited and expensive. This may be the reason for the high prevalence of end-stage renal disease in this environment.

In this study, it was found that the participants had elevated serum cystatin C which likely suggests reduced renal perfusion. Earlier study had reported that cystatin C appears earlier in serum than Cr in reduced glomerular function.[23] This is because cystatin C is only cleared by the glomeruli and is neither secreted nor reabsorbed by renal tubules. In contrast, Cr is secreted (7%–10%) by the renal tubules. In fact, about 40% of Cr may be secreted by the tubules in certain conditions.[21] This blunts the rise of Cr in human serum. This finding of an elevated serum cystatin C is similar to a previous study. Although it was suggested that subcutaneous and omental adipocytes probably contributed to the elevated serum cystatin C observed in that study, this could not be substantiated as a direct GFR was not measured. In addition, there was no report on the degree of abdominal obesity evidenced by increase abdominal circumference of their participants and its relationship with results of omental and subcutaneous cystatin C repor-ted.[27] The participants recruited for this study had abdominal circumference not different from the controls and almost half were overweight suggesting that the influence of subcutaneous and visceral adipose fat to serum cystatin C levels in this study is most likely slim. The finding of elevated serum cystatin C only in the obese participants probably demonstrated an underlying renal injury in obesity. This renal injury is probably too early in the disease progression to be detected by Cr.

The difference observed between CKD-EPI and modification of diet in renal disease (MDRD) equations for serum Cr in the controls probably reflects the absence of renal disease in them. This is similar to report that differences between MDRD and CKD-EPI equations are especially larger for the highest eGFR values.[30] This suggests that the two equations are not well correlated at higher levels of GFR and may not be used in the healthy population free of renal disease and the presence of renal disease tends to bring the

GFR by the two equations together, which was observed in the participants although insignificant. Therefore, it was suggested that the performance of the new CKD-EPI equation will probably be better than the MDRD study equation in population free from renal disease.[30] However, this study found that GFR-Cr by CKD-EPI was consistently higher than MDRD among the controls and participants which is similar to several reports that CKD-EPI over-eGFR.[31],[32],[33] This is most likely responsible for reports that CKD-EPI reduces the prevalence of CKD[30] and classify patients higher than MDRD equation for staging.[34] A previous study has demonstrated a higher accuracy of MDRD for eGFR when compared with a reference method.[35] Despite the difference that exists between MDRD and CKD- EPI equations, they were both significantly lower than GFR-Cystatin only demonstrated by the participants. The finding of a difference between eGFR-Cr by different GFR equations and cystatin C-based equation demonstrated only in the participants and not in the controls further support the presence of renal damage in them. The GFR-Cr equations will classify the participants into Stage 1 CKD, while eGFR-cystatin C will place them in stage 2 CKD. This further support the renal impact of obesity as earlier reported that obesity is an independent risk factor for CKD.[20]

Therefore, obtaining a normal serum Cr and eGFR-Cr in an obese individual should be further investigated as these parameters are inadequate to detect early mild renal impairment found in obesity. Furthermore, obese participants should be extensively screened and monitored for the development of CKD as part of their management.

The study has some limitations which include the fact that the eGFR have not been compared with a reference method to ascertain the performance of the two biomarkers. In addition, the participants were only sampled once instead of two or more sampling over a three months necessary to define CKD.

It was observed that obesity is a risk factor for developing CKD and routine markers like Cr is inadequate to evaluate early in the disease course. Therefore, a high index of suspicion is required when managing obese nondiabetic participants as a subtle renal injury may underlie the disease state. Weight loss campaign and lifestyle modification are a necessary tool for the general populace

Conflict of interest: None declared.



 
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Correspondence Address:
Abiodun K Alaje
Department of Chemical Pathology, Obafemi Awolowo University, Ile-Ife
Nigeria
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DOI: 10.4103/1319-2442.261339

PMID: 31249229

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    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]



 

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