Introduction

Undoubtedly, sodium glucose co-transporter 2 (SGLT2) inhibitors offer benefits beyond the main action for glycemic control. SGLT2 inhibitors are now recognized as crucial for slowing chronic kidney disease progression in real-world studies [1, 2]. Consequently, these medications are frequently prescribed for individuals with chronic kidney disease.

Recently, SGLT2 inhibitors have been linked to lipids. They impact fat storage and substrate utilization and regulate lipid synthesis, transportation, and fatty acid oxidation. They also promote weight loss and reduce body fat which in turn also affects the lipids level [3].

Meta-analyses of 60 randomized trials involving 147,130 individuals documented that SGLT2-inhibitor treatment was associated with increased total cholesterol, LDL cholesterol, and HDL cholesterol, while triglyceride levels decreased [4]. Elevated (LDL-C) levels can occur due to diminished lipid transfer between triglyceride-rich lipoprotein (TRL)-TG and LDL-C. Additionally, enhanced insulin sensitivity leads to increased lipoprotein lipase activity, promoting the conversion of very-low-density lipoprotein-C (VLDL-C) to LDL-C. However, these changes were documented mainly for patients diagnosed with diabetes, and this elevation in LDL-C in patients who used SGLT2-inhibitor was not accompanied with an increased cardiovascular diseases risk [5].

There is currently no existing literature specifically addressing the impact of SGLT2-inhibitor on cholesterol fractions in patients with exclusive chronic kidney disease (CKD).

Dyslipidemia frequently occurs in patients with chronic kidney disease (CKD). In this context, dyslipidemia refers to elevated triglyceride (TG) levels and low high-density lipoprotein cholesterol (HDL-C) levels [6]. Patients with chronic kidney disease (CKD) are at high risk for cardiovascular disease (CVD). Dyslipidemia, along with other factors like chronic inflammation, vascular remodeling, and metabolic disturbances, contributes to coronary artery disease, heart failure, atherosclerosis, arrhythmias, and sudden cardiac death in these patients [7].

CKD patients are often undertreated with cholesterol lowering agents due to lacked evidence to evaluate LDL-C levels’ impact across different CKD stages on cardiovascular disease risk or mortality and due to the fact that individuals with chronic kidney disease (CKD) face an increased risk of side effects from lipid medications due to reduced renal excretion and the associated poly pharmacy [8].

The accumulating evidences that SGLT2 inhibitors have potential benefits in preventing complications associated with dyslipidemia in diabetes patients [9, 10] prompt us to study the impact of dapagliflozin on cholesterol fractions in chronic kidney disease (CKD) patients. It is possible that SLUT2 inhibitor effects may differ from those observed in individuals with diabetes alone.

Therefore, the objective of our study is to investigate how dapagliflozin influences blood cholesterol profiles in stage 3 CKD patients.

Methods

Thirty stage 3 chronic kidney disease patients with dyslipidemia were enrolled in this single blinded randomized–placebo controlled study (only patients were unaware of the allocated treatment) from outpatient clinic of Cairo University Hospitals between August and November 2023. The sample size was determined based on the formula for clinical trials of mean differences. Specifically, with n = 15 patients per group, the study aimed to detect a significant 15% difference compared to baseline in cholesterol fractions.

Following the acquisition of informed consent, participants were allocated randomly by sealed envelope (1:1) either to receive a daily regimen of dapagliflozin 10 mg in the morning or using placebo alongside their existing conservative CKD medications. The intended duration of the treatment is 3 months.

Intervention group (n = 15) received dapagliflozin 10 mg + conservative CKD medications.

Control group (n = 15) received placebo + conservative CKD medications.

The study enrolled adults diagnosed with stage 3 CKD (who had an estimated glomerular filtration rate (GFR) between 30 and 59 ml/min per 1.73 m2) with disease duration of at least 6 months and had dyslipidemia required to be receiving a consistent dose of statins for minimum 3 months before enrollment in the study.

All enrolled patients in both groups received a moderate-intensity statins (10–20 mg atorvastatin).

Individuals were excluded if they had diabetes mellitus, altered their statin dosage or therapy within the last 3 months, had an active urinary tract infection at the time of inclusion, suffered from alcoholism, had triglyceride levels of 600 mg/dl or higher, were allergic to dapagliflozin, had an eGFR below 30, were taking omega-3 fatty acids, were pregnant or breastfeeding, or were unable to provide informed consent.

Age, gender, body mass index (BMI), systolic and diastolic blood pressure, smoking assessment of the enrolled participants alongside with, serum creatinine, eGFR, urinary albumin/creatinine ratio ACR (mg/g), HbA1c at the baseline, and after 3 months were recorded.

Ten-hour fasting blood samples were obtained at baseline and after 12 weeks for assessment lipid profile (total cholesterol, HDL-C and LDL-C, and triglycerides (TGs)).

Primary outcome was the change in cholesterol fractions (total cholesterol, LDL-C, HDL-C) and TG levels 3 months of intervention versus baseline.

The CKD-EPI formula was used to estimate glomerular filtration rate (eGFR) [11]. Microalbuminuria in spot urine specimens is defined as excretion of 30–300 mg of albumin/gram creatinine [12]. Lipid fractions were measured by conventional direct methods.

All patients were aware by symptoms and signs of hypoglycemia for safety issue.

Ethical committee approval.

The study protocol obtains approval from the Faculty of Medicine, Cairo University Research Ethics Committee (REC), at 27–5-2023, with the approval number N-152–2023.

Statistical analysis

Microsoft Excel 2013 was employed for data entry, while the Statistical Package for the Social Sciences (SPSS) version 23 (SPSS, Armonk, NY: International Business Machines Corporation) was utilized for statistical analysis. Simple descriptive statistics (average and standard deviation) provided a concise overview for the quantitative data and frequencies express qualitative data. Bivariate relationship was explored in cross-tabulations and comparison of proportions was done using the chi-square test or fisher exact whenever appropriate. T-independent test and paired T-test were applied to compare normally distributed quantitative data. Pearson correlation was performed to detect correlation between quantitative variables. Multiple linear regression models were used to assess the impact of several factors on the lipid profile parameters in the intervention group. The level of significance was set at probability (P) value < 0.05.

Results

Thirty patients with stage 3 chronic kidney disease (CKD) and dyslipidemia were enrolled in the study. Fifteen participants were administered dapagliflozin for 3 months as an intervention, in addition to conservative care for CKD, while the remaining fifteen participants were assigned to the control group, receiving a placebo alongside their conservative care for CKD too.

Demographic data and laboratory measurements are presented in Table 1. Both the intervention and control groups displayed comparable baseline results, with no statistically significant differences observed in levels of total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG)—the primary variables of interest.

Table 1 Patients’ characters at baseline and after 3 months of follow-up in both groups, N=30
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Compared to control group, after 3 months, the intervention group exhibited a significant lower serum creatinine levels (p-value = 0.005) and a corresponding higher estimated glomerular filtration rate (eGFR) (p-value = 0.005), and regarding the lipid profile of the patients, the intervention group showed lower levels of total cholesterol and low-density lipoprotein cholesterol (LDL-C), while high-density lipoprotein cholesterol (HDL-C) and triglyceride (TG) levels were elevated. However, these differences were statistically significant only for LDL-C (p-value = 0.022, Table 1).

Compared to baseline, patients who received dapagliflozin showed improvement in serum creatinine and eGFR levels after 3 months with highly significant p-values of less than 0.001 and 0.001, respectively. Additionally, there was a notable reduction in total cholesterol and LDL-C levels among those receiving the treatment, evidenced by significant p-values of 0.010 and 0.006, respectively. While there was an increase in HDL-C levels and a decrease in TG, these changes did not reach statistical significance. Tendency towards significance were observed post-treatment in the decrease of ACR levels suggesting a positive trend, although this finding was not statistically significant (Table 2).

Table 2 Baseline laboratory data compared to follow-up after 3 months within the studied groups
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Same laboratory variables were tested after 3 months for the control group without intervention. The results indicated significant deterioration in serum creatinine levels, and estimated glomerular filtration rate (eGFR) (p value = 0.008 and 0.011, respectively). However, there was no statistically significant increase in total cholesterol, LDL-C, HDL-C, triglycerides (TG), or albumin-to-creatinine ratio (ACR) in this group (as shown in Table 2).

Male sex exhibited significantly higher eGFR at baseline and after 3 months in the intervention group compared to female sex (p value = 0.025 and 0.048, respectively). In contrast, smoking demonstrated a non-specific correlation with the tested variables (p value > 0.05, Table 3).

Table 3 Comparison between the qualitative independent variables and parameters pre- and post-dapagliflozin administration (intervention group, N = 15)
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Total cholesterol at baseline showed a moderate significant correlation with BMI (p value = 0.028, R value = 0.566). The same correlation was observed for total cholesterol after 3 months (p value = 0.032, R value = 0.554) (Table 4).

Table 4 Comparison between the quantitative independent variables and parameters pre- and post-dapagliflozin administration (intervention group, N = 15)
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A multiple linear regression was conducted to predict post-intervention total cholesterol levels based on certain independent variables. However, none of these variables significantly predicted the decrease in cholesterol levels (F (10, 15) = 1.218, p = 0.460, R2 = 0.135, Table 5). Similarly, another multiple linear regression aimed to predict post-intervention LDL-C levels using the same independent variables. Again, none of these variables significantly predicted LDL-C levels (F (10, 15) = 0.638, p = 0.743, R2 =  − 0.349, Table 5). However, when predicting post-intervention urinary albumin/creatinine levels, only the baseline urinary albumin/creatinine level emerged as a statistically significant predictor (F (10, 15) = 17.460, p = 0.007, R2 = 0.922). This variable significantly contributed to the prediction (p < 0.05, Table 6).

Table 5 Predictors of total cholesterol level and LDL-C post-intervention (logistic regression)
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Table 6 Predictors of urinary albumin/creatinine ratio-post intervention (logistic regression)
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Discussion

There is currently no existing literature addressing the impact of dapagliflozin on cholesterol fractions in patients with chronic kidney disease (CKD). To our knowledge, this is the first trial examining the impact of SGLT2 inhibitors on lipids in chronic kidney patients. We found that dapagliflozin has a favorable effect on cholesterol fractions in stage 3 CKD patients without diabetes mellitus.

Data regarding SGLT2 inhibitors and lipids in patients with diabetes exist. Only a few relevant studies have included the effect of SGLT2 inhibitors on cholesterol fractions in patients with both diabetes and renal impairment. It is worth noting that this was not the primary focus of those studies [13,14,15,16].

In our study, compared to baseline, patients who received dapagliflozin exhibited a significant decrease in LDL-C and total cholesterol values. Favorable outcomes were observed regarding triglyceride (TG) and HDL-C levels. In contrast, there was no significant change in the lipid profile of patients in the control group. These findings partially align with multiple clinical trials that have demonstrated SGLT-2 inhibitors’ ability to decrease plasma TG levels and increase HDL-C levels [17]. However, it is important to note that these studies were conducted in patients with type 2 diabetes [18, 19]. In our study, we did not discern the anticipated increase in LDL-C levels associated with dapagliflozin treatment. While the precise impact of dapagliflozin on LDL-C levels remains incompletely understood, several mechanisms may contribute. These mechanisms include promoting weight loss, enhancing insulin sensitivity, increasing urinary glucose excretion, and potentially influencing liver function and lipid metabolism, which could ultimately lead to reduced LDL-C production. Although these mechanisms hint at a potential association between SGLT2 inhibitors and decreased LDL-C, further research is necessary to fully comprehend this relationship in patients with chronic kidney disease (CKD) [3]. Individual responses to statins vary due to genetic factors [20], with some people exhibiting better responsiveness. Additionally, the intervention group may have adhered more rigorously to dietary modifications, exercise, or weight management, or demonstrated better adherence to statin therapy. Furthermore, unmeasured confounders in our study could also play a role. However, these factors could introduce bias to the results.

Studies on individuals with DM reported that people whose LDL-C levels increased after receiving dapagliflozin experienced higher triglyceride (TG) levels (which were already slightly elevated compared to the reference range at baseline in our patients). This suggests a pivotal role of TG in the SGLT2 inhibitor-induced LDL-C elevation [21, 22].

Proteinuria shows a correlation with an atherogenic subspecies of LDL. Reducing proteinuria has a beneficial effect on lipid levels, regardless of the method used (such as medication or dietary changes). This effect was observed in the intervention group, as evidenced by a notable reduction in albumin-to-creatinine ratio (ACR), which may contribute to a reduction in LDL-C levels [23, 24].

While the dapagliflozin group experienced an approximate 22% reduction in LDL-C levels from the initial values, this decrease did not meet the desired target. According to current recommendations and large-scale observational studies, adults with CKD stages 1–4 who have been diagnosed with atherosclerotic cardiovascular disease (ASCVD), diabetes mellitus, or apparent proteinuria (similar to our patients) should strive for LDL cholesterol levels below 70 mg/dl [6].

The synergistic effect of using SGLT2 inhibitors (SGLT2i) and statins together in humans remains unclear due to the limited availability of studies. However, research conducted on mice has demonstrated that combined treatment with dapagliflozin and atorvastatin improves lipid oxidation and reduces kidney lipid accumulation. This combination yields favorable effects on metabolic parameters and contributes to the reduction of oxidative stress, fibrosis, and apoptosis in an insulin-resistant model induced by a high-fat, high-fructose diet [25, 26].

In this study, we anticipated that either the estimated glomerular filtration rate (eGFR) would decrease or remain stable upon initiation of SGLT2 inhibitors (SLUT2i). However, we observed a noticeable improvement in these parameters within the intervention group, which contradicted the expected trend. In contrast, the control group experienced significant worsening. Despite these findings, predicting the duration and identifying individuals who will experience an acute eGFR dip remain challenging. In SGLT2 inhibitor trials, individuals who did experience an acute eGFR dip generally had a lower absolute eGFR than non-dippers [27].

The findings from two studies involving patients with diabetes and chronic kidney disease (CKD) were matched with our results. In a study by Barnett et al., patients with stage 2–4 CKD who received empagliflozin treatment experienced only minor reductions in estimated glomerular filtration rate (eGFR). Importantly, these slight decreases promptly returned to baseline levels by the end of the 3-week follow-up after treatment completion [13]. Similarly, in the study by Haneda M et al., patients with type 2 diabetes mellitus and CKD initially saw a decline in eGFR during the first 2 weeks of luseogliflozin treatment. However, shortly thereafter, eGFR rebounded and consistently remained above baseline levels across all eGFR groups [14]. These findings highlight the impact of SGLT2 inhibitors on kidney function and suggest that any initial declines in eGFR may be reversible or even followed by improvement.

SGLT-2 inhibitors (SGLT2i) confer several indirect benefits for kidney function. They enhance glycemic control, promote weight loss, and reduce blood pressure. Furthermore, SGLT2 inhibitors (SGLT2i) may have a valuable impact on reducing proteinuria, not only in cases of microalbuminuria but also in more severe nephrotic-range proteinuria. This reduction in proteinuria contributes to slowing down the progression of chronic kidney disease. In the intervention group of this study, micro albuminuria significantly decreased following dapagliflozin administration [28,29,30]. The control group did not achieve the benefit of slowing down the progression of CKD with SGLT2 inhibitor use [31].

Regardless the dapagliflozin use, it has been found that, despite the typical relentless decline in renal function among most patients with chronic kidney disease (CKD), certain studies (REIN follow-up study, MDRD study, and the African-American Study of Kidney Disease and Hypertension (AASK) trial) have shed light on an intriguing phenomenon: a notable proportion of CKD patients experience sustained improved kidney function over time. These observations suggest that GFR improvement is possible at any CKD stage even through stage 4–5 [32,33,34,35].

Although this study had limitations due to a small patient cohort and short treatment duration, additionally, it lacked measurements of some confounders which may affect LDL-C levels; it underscores the need for additional research, particularly long-term clinical trials, to comprehensively explore the lipid-lowering and lipid-modifying effects of these medications in patients with chronic kidney disease.

Conclusion

Dapagliflozin favorably influences cholesterol fractions and kidney function in patients with stage 3 chronic kidney disease. SGLT2 inhibition is associated with a decrease in total cholesterol, LDL-C, triglycerides (TG), serum creatinine, and albumin-creatinine ratio, as well as increases in HDL-C, and estimated glomerular filtration rate (eGFR) in this population.