SGLT inhibitors on weight and lipid metabolism in diabetes
Diabetes mellitus (DM), is a diagnostic term for a group of metabolic disorders characterized by abnormal glucose homeostasis resulting in elevated blood sugar. Almost 90% of people with diabetes have type 2 diabetes (T2DM). Currently, more than 463 million people are living with diabetes worldwide. More alarmingly, it is predicted that nearly 230 million-plus new cases will be added to already discomforting diabetes statistics by 2045.
SGLT inhibitors and diabetes
Sodium-glucose cotransporter (SGLT) inhibitors are a new type of oral AHAs used to treat type 2 diabetes. Dapagliflozin (DAPA), canagliflozin (CANA), empagliflozin (EMPA), ertugliflozin (ERTU), and sotagliflozin (SOTA) are the five important SGLT inhibitors. Among the five, only SOTA is a dual SGLT-1/2 inhibitor. SGLT inhibitors work by blocking the glucose reabsorption of SGLT transporters, thereby reducing blood glucose.
SGLT2 accounts for 80 – 90% of renal glucose reabsorption. The roles of SGLT2 and SGLT1 in glucose reabsorption were confirmed by human studies. In humans, familial renal glycosuria, a rare benign condition, arises from SGLT2 mutations that reduce renal glucose reabsorption. Some pharmacokinetics data suggested that SGLT2 inhibitors can reduce renal glucose reabsorption by 80 – 97%. However, some clinical studies have shown that SGLT2 inhibitors can inhibit only 30 -50% of glucose reabsorption. One possible explanation is that SGLT1 may contribute to glucose reabsorption when SGLT2 is inhibited.
SGLT inhibitors and T2DM treatment
Numerous clinical trials regarding the mechanism of action of SGLT inhibitors have been conducted in recent years. SGLT inhibitors were also found to be effective in handling hyperglycemia, hyperlipidemia, hypertension, and reducing body weight. It is well known that hyperlipidemia is common in patients with diabetes mellitus and is partly responsible for the increased heart diseases in these patients. This also means SGLT inhibitors have an edge over other drugs in treating diabetes.
That being said, with regards to the effect of SGLT inhibitors on lipid metabolism in T2DM patients, there are not much reliable systematic reviews available.
STUDY OBJECTIVE
Obesity and lipid metabolism are closely related to various complications of type 2 diabetes. The objective of this study was to evaluate the effect of SGLT inhibitors on lipid metabolism in T2DM patients at 24-weeks of treatment.
STUDY METHODS
Design and registration
The analytic protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO), with registration number: CRD42020198516. Ethics approval was not required for this network meta-analysis because it used data that were already in the public domain.
Subjects
This study selected patients with type 2 diabetes. Although there were no restrictions on age, weight, HbA1c (Hemoglobin A1c) levels, or drug history, patients with underlying acute or chronic diseases, and heart or kidney failure were excluded.
Interventions
This network meta-analysis only included single-drug studies. Drug combination studies were excluded. Two different doses were administered for each of the five drugs (dapagliflozin (DAPA), canagliflozin (CANA), empagliflozin (EMPA), ertugliflozin (ERTU), and sotagliflozin (SOTA), making a total of 10 interventions. Besides the placebo group, a total of 11 interventions were included.
Outcome measures
Weight was the primary outcome measure. There were changes in the levels of ALT, cholesterol, triglycerides, high-density lipoprotein/high-density lipoprotein cholesterol (HDL/HDL-C), and low-density lipoprotein/low-density lipoprotein cholesterol (LDL/LDL-C). To reduce heterogeneity among the studies, limitations were placed on the treatment duration. Results after 24-weeks of treatment were included because the weight remained relatively stable in the subjects. Therefore, 24 ±2weeks was chosen as the time point for data selection.
Data collection, screening, and extraction
The Web of Science, PubMed, Cochrane Library, Embase, and Clinical Trials databases were electronically searched to collect data from randomized controlled trials (RCTs) involving T2DM patients through June 2020. “SGLT,” “diabetes,” and “Mellitus” were the keywords used.
Two reviewers independently screened the title, abstract, and full text to identify the studies eligible for inclusion. Studies with data that could not be extracted or utilized, animal studies, and literature reviews were excluded. All screening disagreements were discussed. The extracted data was inclusive of,
- the basic information about the study, including title, first author’s name, year of publication
- the characteristics of the included study, for example, study duration, sample sizes of test and control groups, intervention measures, etc
- outcome measures and data
- all information needed to assess the risk of bias.
Risk of bias assessment
The Cochrane Risk of Bias tool was used to assess the risk of bias (RoB) among randomized controlled trials (RCTs).
Statistical analysis
The Bayesian method was used to perform this network meta-analysis. Statistical software STAT MP 16 and ADDIS 1.16.5 were used to draw the plots and to perform network meta-analyses. RevMan 5.4 software was used for the common meta-analysis. The continuous variables are expressed as the mean difference (MD) as an effective indicator. Effect estimates and 95% confidence intervals (CIs) were also calculated.
A network meta-analysis was performed for weight, and a common meta-analysis was performed for other outcome indicators because the data were insufficient. A random-effects model was used in the network meta-analysis, whereas a fixed model was used in the common meta-analysis. The core results of the network meta-analysis had a network evidence plot, network SUCRA plot, pairwise comparison plot, and network node-splitting analysis of inconsistency. All inconsistencies were observed, the cause was identified, and explained in detail
RESULTS
Included studies and subjects
Of the 7,657 studies retrieved from electronic search, 36 studies were selected and included. Gray literature was excluded in this study. A total of 17,561 patients were chosen from the included studies. The researchers’ original plan was to include five SGLT inhibitors. However, SOTA-related RCT data did not meet the inclusion criteria, so SOTA data were excluded from these results.
Network meta-analysis
Weight
36 studies reported weight comparisons among the test subjects. The node-splitting analysis confirmed the reliability of the consistency model used in this study. According to the pairwise comparison plot, among the 4 SGLT-2 inhibitors, the SUCRA plot shows that 300mg CANA and 100mg CANA were the most effective. The Funnel plots generated were bilaterally symmetrical. Also, most studies fell within the confidence interval of 95%. These results indicate that this study has no publication bias.
Common meta-analysis results
Cholesterol
Three studies reported significant differences in cholesterol levels between the SGLT inhibitor and the placebo groups A fixed-effect model adopted revealed that with an increase in the dose of SGLT inhibitors, serum cholesterol also increased (low dose: I 2=0% [MD=0.03, 95% CI (3.18, 3.24), P=.99]; high dose: I 2=46% [MD=2.52, 95% CI (0.19, 5.23), P=.07]).
Triglyceride
Five studies reported significant differences in triglyceride levels between the SGLT inhibitor and the placebo groups. A random-effect model adopted revealed that with an increase in the dose of SGLT inhibitors, the serum triglyceride level decreased (low dose: I 2=0% [MD=9.65, 95% CI (15.41, 3.88), P= 0.001]; high dose: I 2=54% [MD=8.65, 95% CI (16.65, 0.66), P=.03]).
HDL/HDL-C
Five studies reported significant differences in HDL/ HDL-C levels between the SGLT inhibitor and the placebo groups. According to the fixed effect model, compared with the placebo, oral SGLT inhibitors were associated with increased serum HDL/HDL-C levels (low dose: I 2=0% [MD=4.52, 95% CI (2.14,6.90), P=.0002]; high dose: I 2=0% [MD=4.57, 95% CI (2.51, 6.63), P<0.0001])
LDL/LDL-C
Five studies reported significant differences in LDL/ LDL-C levels between the SGLT inhibitor and the placebo groups. A fixed-effect model showed that with an increase in the dose of SGLT inhibitors, the serum LDL/LDL-C level also increased (low dose: I 2=0% [MD=2.54, 95% CI (1.23,6.31), P=0.19]; high dose: I 2=48% [MD=6.54, 95% CI (3.15, 9.93), P =.0002]).
ALT
Three studies reported significant differences in ALT levels between the SGLT inhibitor and the placebo groups. A fixed-effect model showed that compared with the placebo, oral SGLT inhibitors were associated with decreased serum ALT levels (low dose: I2=0% [MD=3.08, 95% CI (5.19, 0.97), P=.004]; high dose: I 2=0% [MD=3.86, 95% CI (5.93, 1.78), P=.0003]).
DISCUSSION
In this study, the authors examined the effect of SGLT inhibitors on weight and lipid metabolic parameters in patients with type 2 diabetes. Since dual SGLT-1/2 inhibitors were excluded, the results in this study only relate to SGLT-2 inhibitors. RCTs on SOTA were excluded as the duration of the intervention didn’t meet the inclusion criteria.
This network meta-analysis showed that SGLT-2 inhibitors can effectively,
- induce weight loss in patients with type 2 diabetes; CANA being the most effective, and DAPA, the least effective.
- reduce triglyceride and increase both HDL-C and LDL-C levels.
- decrease serum ALT levels and may protect the liver.
Some authors suggested that SGLT inhibitors may induce weight loss in T2DM patients. This is probably by reducing the body’s total energy intake and promoting osmotic diuresis.
SGLT inhibitors increase glucagon-like peptide 1 (GLP-1) levels. GLP-1 plays a key role in promoting the glucose-dependent production and release of insulin and inhibits glucagon secretion, gastric emptying, food intake, and nutrient absorption. Thus, GLP-1 can reduce blood sugar levels and may help control weight, similar to SGLT inhibitors. An RCT by Zambrowicz B showed that 300mg of SOTA substantially increased GLP-1 levels in T2DM patients.
This study verified the role of SGLT inhibitors in improving lipid metabolism in type 2 diabetes patients. An epidemiological investigation reported that SGLT inhibitors improved atherosclerosis and reduced the risk of cardiovascular diseases. The Comparative Effectiveness of Cardiovascular Outcomes in New Users of SGLT-2 Inhibitors (CVDREAL) study involving 300,000 T2DM patients showed that compared with hypoglycemic drugs, SGLT2 inhibitors reduced all-cause mortality and heart failure in-hospital mortality by 51% and 39% respectively. It was also reported that SGLT inhibitors may also have positive effects on myocardial fibers by activating the Stat3 signaling pathway or by inhibiting the Na+/H+ exchange in cardiomyocytes.
Limitations
There are several limitations to this network meta-analysis.
- Limited laboratory data related to lipid metabolism. So, the authors could not conduct a network meta-analysis for all the outcomes; a common meta-analysis was conducted instead.
- The highly dynamic laboratory test results for triglycerides and cholesterol, which could have interfered with the results.
- Different types of SGLT inhibitors might have different effects on triglyceride, cholesterol, and serum ALT levels in T2DM patients.
Conclusion
Based on the study, SGLT inhibitors can induce weight loss and improve lipid metabolism in patients with type 2 diabetes mellitus. Therefore, diabetic patients with obesity should consider additional pharmacological treatments with SGLT inhibitors whenever lifestyle changes are not enough for weight management. Moreover, SGLT2 inhibitors are proved to be safe among patients with mild to moderate hepatic and renal dysfunction. However, further studies on the clinical utility of SGLT inhibitors are needed for better diabetes management.
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