
==== Front
J Int Med Res
J Int Med Res
IMR
spimr
The Journal of International Medical Research
0300-0605
1473-2300
SAGE Publications Sage UK: London, England

39216017
10.1177/03000605241272639
10.1177_03000605241272639
Preclinical Study
Mendelian randomization study of sodium–glucose cotransporter 2 inhibitors in cardiac and renal diseases
Chen Lei
Zuo Yongdi
He Manrong
Duo Lijin
https://orcid.org/0000-0001-6709-5591
Tang Wanxin
Department of Nephrology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
Wanxin Tang, Department of Nephrology, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu, Sichuan 610041, China. Email: kidney123@163.com
8 2024
31 8 2024
52 8 0300060524127263916 5 2024
11 7 2024
© The Author(s) 2024
2024
SAGE Publications
https://creativecommons.org/licenses/by-nc/4.0/ Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
Objective

Sodium–glucose cotransporter 2 inhibitors (SGLT2i) target the reabsorption of sodium and glucose in the kidney proximal tubules to reduce blood sugar levels. However, clinical randomized controlled trials on SGLT2i have yielded inconsistent results, necessitating further research into their efficacy and safety for specific cardiac and renal diseases.

Methods

“Sodium in urine” was selected as a downstream biomarker of SGLT2i. Single nucleotide polymorphisms were extracted from genome-wide association study data as instrumental variables. Mendelian randomization analysis was then conducted for cardiac and renal diseases and potential adverse events. The causal effects of SGLT2i on these diseases were determined based on inverse variance weighted results, followed by sensitivity and pleiotropy tests.

Results

SGLT2i had a significant protective effect against nephrotic syndrome (odds ratio [OR] 0.0011, 95% confidence interval [CI] 0.000–0.237), chronic glomerulonephritis (OR 0.0002, 95% CI 0.000–0.21), and hypertensive nephropathy (OR 0.0003, 95% CI 0.000–0.785). No causal effects were observed between SGLT2i and cardiac diseases or potential adverse events.

Conclusions

SGLT2i can act as protective factors against nephrotic syndrome, chronic glomerulonephritis, and hypertensive nephropathy.

Sodium–glucose cotransporter 2 inhibitor
Mendelian randomization
drug target
cardiac disease
chronic kidney disease
causal effect
Chengdu Science and Technology Bureau https://doi.org/10.13039/501100010822 2019-YF09-00090-SN Science and Technology Department of Sichuan Province https://doi.org/10.13039/501100004829 24ZDYF1187 typesetterts2
==== Body
pmcIntroduction

Sodium–glucose cotransporter 2 inhibitors (SGLT2i) reduce blood glucose by inhibiting glucose reabsorption in the proximal renal tubules. 1 Large-scale, multicenter, randomized controlled trials have demonstrated the effectiveness of SGLT2i in reducing proteinuria, preserving the glomerular filtration rate, and slowing the progression of chronic kidney diseases (CKD).2–4 Studies such as DAPA-CKD (Dapagliflozin in Patients with Chronic Kidney Disease) and EMPA-KIDNEY (Empagliflozin in Patients with Chronic Kidney Disease) have shown the significant protective effects of SGLT2i on CKD with heterogeneous etiologies including diabetic nephropathy, glomerulonephritis, and immunoglobulin A (IgA) nephropathy.5–7 However, the diverse spectrum of CKD etiologies warrants further investigation into the effects of SGLT2i. Cardiac outcomes studies such as DAPA-HF (Dapagliflozin and Prevention of Adverse Outcomes in Heart Failure), the EMPEROR-Reduced (Empagliflozin in Patients With Heart Failure, Reduced Ejection Fraction, and Volume Overload) trial, EMPEROR-Preserved (Empagliflozin in Heart Failure with a Preserved Ejection Fraction), and EMPA-REG OUTCOME (Empagliflozin, Cardiovascular Outcomes, and Mortality in Type 2 Diabetes) have indicated that SGLT2i significantly reduce the risks of hospitalization and cardiac death in patients with heart failure.8–10 However, EMPA-KIDNEY and DECLARE-TIMI 58 (Dapagliflozin Effect on Cardiovascular Events–Thrombolysis in Myocardial Infarction 58) did not find a significant protective effect against major adverse cardiovascular events.3,11 Notably, these trials have focused more on heart failure and less on atrial fibrillation, stroke, myocardial infarction, and coronary artery disease, which are common comorbidities in patients with CKD and significant risk factors for morbidity, hospitalization, and mortality. 12 To date, large-scale clinical trials exploring the impact of SGLT2i on these cardiovascular conditions are lacking. In addition, the CANVAS (Canagliflozin and Cardiovascular and Renal Events in Type 2 Diabetes) study found an increased incidence of adverse events such as genital infection, amputation, and fracture in patients receiving canagliflozin as compared with those in the placebo group. 13 The CREDENCE (Canagliflozin and Renal Outcomes in Type 2 Diabetes and Nephropathy) study found a high occurrence of diabetic ketoacidosis.3,4 Although studies on other SGLT2i such as empagliflozin and dapagliflozin have reported similar rates for these adverse events, the potentially severe risks of acute kidney injury, hypoglycemia, diabetic ketoacidosis, fracture, and amputation remain a concern and limit the broad use of SGLT2i. Further evidence is needed to clarify the efficacy of SGLT2i in cardiac and renal diseases and to establish their safety profile.

Mendelian randomization (MR) leverages genetic variations in the analysis of causal effects between exposures and outcomes, offering new insights into disease etiology.14,15 This approach is less susceptible to confounding factors and reverse causation compared with traditional observational studies. 15 Under the assumptions of relevance, independence, and exclusivity, MR analyses remain a principled and reliable means to probe causal questions, regardless of whether the results are positive or negative.16,17 For example, MR studies found no causal effect of interleukin 6 signaling on the risk of pulmonary arterial hypertension, and no evidence that elevated urate levels reduce the risk of neurodegenerative outcomes, demonstrating the crucial value of MR in negative interaction between exposure and outcome.18,19 Recent proteomic MR analyses have focused on establishing positive relationships between proteins and diseases such as multiple sclerosis and diabetic nephropathy, aiming to identify drug targets and provide new insights for diagnosis and treatment.20,21

Drug-target MR uses single nucleotide polymorphisms (SNPs) within or near genes encoding drug targets as proxies for drug efficacy, simulating pharmacological effects to explore potential causal relationships between exposures and outcomes from a genetic perspective.22–25 To address inconsistencies in clinical observations and the lack of in-depth research on SGLT2i and common cardiac diseases, genome-wide association study (GWAS) data were used in two-sample drug-target MR analysis. In our study, we evaluated the causal relationships between SGLT2i and CKD with various etiologies, multiple cardiac conditions, and potential adverse reactions to enhance understanding of the efficacy and safety of SGLT2i (Figure 1).

Figure 1. Overview diagram of SGLT2i drug-target Mendelian randomization analysis. Note: The diagram was created with MedPeer (www.medpeer.cn). SGLT2i: Sodium–glucose cotransporter 2 inhibitors; OR, odds ratio; CI, confidence interval.

Methods

Data sources

In this MR study, we used exposure and outcome data derived from publicly available GWAS datasets, focusing on European populations. The data were located and downloaded after searching by GWAS ID in the Medical Research Council Integrative Epidemiology Unit (IEU) OpenGWAS project (https://gwas.mrcieu.ac.uk), as detailed in Table 1. All summary-level GWAS data used in the analyses are publicly available; therefore, this study was exempt from ethics review and the need for informed consent. Ethical approval for the GWASs can be found in the corresponding GWAS publications cited in the manuscript.

Table 1. Outcome data information.

Outcome	GWAS ID	ncase	ncontrol	Sample size	PMID	
Diabetic nephropathy	finn-b-DM_NEPHROPATHY	3283	210463	213746		
Immunoglobulin A nephropathy	ebi-a-GCST90018866	15587	462197	477787	30594039	
Nephrotic syndrome	ebi-a-GCST90018884	775	475255	476030	30594039	
Chronic glomerulonephritis	ebi-a-GCST90018820	566	475255	475821	30594039	
Pyelonephritis	ebi-a-GCST90018909	7992	454495	462487	30594039	
Chronic tubulo-interstitial nephritis	finn-b-14_CHRONTUBULOINTNEPHRITIS	620	201028	201648		
Hypertensive renal disease	finn-b-I9_HYPTENSRD	468	162837	163305		
Atrial fibrillation	ebi-a-GCST006414	60620	970216	1030836	30061737	
Coronary artery disease	ebi-a-GCST003116	42096	99121	141217	26343387	
Heart failure	ebi-a-GCST009541	47309	930014	977323	31919418	
Stroke	ebi-a-GCST90038613	6925	477673	484598	33959723	
Hypertension	ebi-a-GCST90038604	129909	354689	484598	33959723	
Myocardial infarction	ebi-a-GCST90038610	11081	473517	484598	33959723	
Diabetic ketoacidosis	finn-b-DM_KETOACIDOSIS	4510	162201	166711		
Urinary tract infection	ukb-b-8814	5447	457563	463010		
Back pain	ebi-a-GCST90038698	2866	481732	484598	33959723	
Pain in limb	ukb-d-M13_LIMBPAIN	3674	357520	361194		
Diabetic hypoglycemia	finn-b-DM_HYPOGLYC	3724	162201	165925		
Surgery/amputation of toe or leg	ukb-d-5540_0	25604	287	25891		
Fractures	ebi-a-GCST90038703	8844	475754	484598	33959723	
Hypotension	finn-b-I9_HYPOTE	1857	216463	218320		
Acute renal failure	ebi-a-GCST90018790	7695	474571	482266	34594039	

Study design

Sodium in urine (GWAS ID: ebi-a-GCST90013989) was selected as a downstream biomarker for MR analysis using the TwoSampleMR package (version 0.5.7) in R (version 4.2.3; www.r-project.org) to mimic the pharmacological effects of SGLT2i. The extract_instruments function was applied to retrieve GWAS data with P < 5 × 10−5. Linkage disequilibrium was addressed using the ld_clump function in the ieugwasr package (kb = 10,000, r2 = 0.3). We selected SNPs located within 1 Mb of the gene’s start site, specifically, on chromosome 16, positions 31,483,123–31,490,769 (GRCh37). Using this process, we identified four SNPs: rs11642632, rs72800849, rs8060136, and rs8063700 (Supplementary Table 1). All SNPs demonstrated F-statistics greater than 10 without weak instrument bias. PhenoScanner examination (www.phenoscanner.medschl.cam.ac.uk) revealed no association between these SNPs and known diseases. The identified SNPs satisfied the core assumptions of relevance, independence, and exclusivity required for MR.

With the four SNPs as exposures and potassium in urine (GWAS ID: ebi-a-GCST90013988) as a positive control, relevant outcome data were extracted using the extract_outcome_data function. Data were harmonized using the harmonise_data function. MR analysis was conducted according to five methods: inverse variance weighted (IVW), MR-Egger, weighted median, simple mode, and weighted mode. On the basis of the IVW results, we assessed the ability of the four SNPs to reflect the clinical effects of SGLT2i. The exposure of these SNPs in relation to kidney diseases, cardiac diseases, and certain potential adverse effects were then analyzed through MR analysis, including sensitivity and pleiotropy tests (Figure 2). The results were visualized using the forestploter package (version 1.1.1) in R.

Figure 2. Workflow of Mendelian randomization analysis for SGLT2i. The F-statistic was calculated as R2 = β2/(β2 + N × SE2) and F = (R2 × (N − 2))/(1 − R2), where β represents the effect size of the SNP, N is the total sample size, and SE is the standard error of the effect size. SLC5A2, solute carrier family 5 member 2 gene, encoding sodium–glucose cotransporter; SGLT2i, sodium–glucose cotransporter 2 inhibitor; SNP, single nucleotide polymorphism; IgA, immunoglobulin A; Chr, chromosome.

Results

In the MR analysis with urinary potassium as a positive control, the IVW method yielded a significant result, with P = 3.86 × 10−7 and odds ratio (OR) > 1 (Supplementary Table 2), consistent with the clinical observation that an increased urinary sodium level leads to increased potassium excretion. This finding demonstrated that the four SNPs identified through preliminary screening can reflect the pharmacological action of SGLT2i.

MR analysis suggested that SGLT2i can provide substantial protection against a variety of CKD (Figure 3, Supplementary Table 3). Significant protection effects were observed for nephrotic syndrome (OR 0.0011, 95% confidence interval [CI] 0.000–0.237, P = 0.013), chronic glomerulonephritis (OR 0.0002, 95% CI 0.000–0.210, P = 0.017), and hypertensive nephropathy (OR 0.0003, 95% CI 0.000–0.785, P = 0.043). For diabetic nephropathy (OR 0.143, 95% CI 0.008–2.690) and chronic interstitial nephritis (OR 0.432, 95% CI 0.001–315), a protective effect was indicated, although the results were not statistically significant. No causal relationship was observed for pyelonephritis (OR 1.577, 95% CI 0.251–9.901) or IgA nephropathy (OR 1.462, 95% CI 0.431–4.963).

Figure 3. Results of Mendelian randomization analysis. Outcome: events included in the analysis; Beta: effect estimate of SGLT2 inhibitors on outcomes. IgA, immunoglobulin A; Pval, P-value. OR, odds ratio. CI, confidence interval.

In the MR analysis for cardiac diseases such as atrial fibrillation, coronary artery disease, stroke, heart failure, and myocardial infarction, SGLT2i were identified as potentially protective factors for most conditions (95% CI 0.30–2.19 for atrial fibrillation, 95% CI 0.18–1.91 for coronary artery disease, 95% CI 0.31–2.61 for heart failure, 95% CI 0.96–1.01 for stroke, and 95% CI 0.96–1.02 for myocardial infarction). However, the P-values did not show statistical significance (Figure 3, Supplementary Table 4).

MR analysis was conducted for adverse events commonly reported in clinical trials on SGLT2i. Conditions such as diabetic ketoacidosis, acute kidney injury, fracture, amputation, back and leg pain, and urinary tract infection did not show a definitive causal relationship with SGLT2i from the perspective of genetic variations (Figure 3, Supplementary Table 5).

All Mendelian analyses were subjected to heterogeneity and sensitivity tests, revealing no pleiotropy or heterogeneity. Scatter plots were used to illustrate the association strength between the SNPs and the exposure/outcome, with different colored lines representing fits from various models. Leave-one-out tests demonstrated stability in the MR outcomes between the exposure and outcome after the removal of any of the SNPs (Figure 4).

Figure 4. Scatter plots and sensitivity analysis. (a, b) Scatter plot and leave-one-out analysis for the Mendelian randomization (MR) of SGLT2 inhibitors and nephrotic syndrome. (c, d) Scatter plot and leave-one-out analysis for the Mendelian randomization of SGLT2 inhibitors and chronic glomerulonephritis and (e, f) Scatter plot and leave-one-out analysis for the Mendelian randomization of SGLT2 inhibitors and hypertensive nephropathy. SGLT2, sodium–glucose cotransporter 2; SNP, single nucleotide polymorphism.

Discussion

The MR results indicated that SGLT2i can delay the progression of CKD with most etiologies, particularly hypertensive nephropathy, chronic glomerulonephritis, and nephrotic syndrome. SGLT2i exhibit significant protective effects, corroborating the clinical trial finding that drugs such as dapagliflozin and empagliflozin significantly slow the progression of glomerulonephritis and hypertensive nephropathy.5,7 The renoprotective mechanisms of SGLT2i extend beyond direct glucose reduction and proteinuria reduction to lowering the glomerular filtration rate, improving oxidative stress, protecting renal microvasculature, and alleviating renal hypoxia.1,26,27 In mouse models, SGLT2i have been shown to modulate inflammation and metabolism, enhance mitochondrial function, and reduce inflammation and fibrosis, contributing to nephroprotective effects.28–30 These actions likely delay the onset and progression of hypertensive nephropathy and chronic glomerulonephritis. Furthermore, the analysis of SGLT2i in relation to nephrotic syndrome can provide new insights into the treatment of this disease. Nephrotic syndrome, characterized by substantial proteinuria, hypoalbuminemia, severe edema, and hyperlipidemia, can be inhibited or delayed with use of SGLT2i by significantly reducing proteinuria and exhibiting anti-inflammatory and antifibrotic effects.31,32 Although large-scale clinical trials specifically investigating the impact of SGLT2i on nephrotic syndrome are yet to be conducted, the MR analysis results and the clinical efficacy of SGLT2i in current studies suggest that these drugs may become a frontline medication for treating nephrotic syndrome in the future.

MR analysis did not establish a causal relationship between SGLT2i and cardiac events such as atrial fibrillation, coronary artery disease, heart failure, stroke, and myocardial infarction. These negative results warrant careful interpretation and consideration of several factors. The genetic variants used as instrumental variables in the analysis may not fully capture the complex pharmacological effects of SGLT2i. Studies including DAPA-HF, EMPEROR-Reduced, EMPEROR-Preserved, EMPA-REG OUTCOME, CREDENCE, and CANVAS have demonstrated that SGLT2i significantly reduce the risk of cardiac death and hospitalization in patients with heart failure, decrease the incidence of atrial fibrillation, and improve the prognosis of myocardial infarction.33–36 The discrepancy between our results and those of clinical studies could be attributed to differences in study populations, endpoints, or unmeasured confounding in observational studies, which MR aims to address. Negative MR findings do not negate these mechanisms but suggest that the overall causal impact on cardiovascular disease may be more complex than can be captured through genetic instruments alone. SGLT2i may exert direct effects against myocardial hypertrophy, fibrosis, and remodeling37,38 or indirectly protect the heart by slowing the deterioration of renal function, diuresis, glucose control, stimulation of erythropoiesis, and inhibition of the sympathetic nervous system.39–42 Further large-scale clinical studies are necessary to clarify the long-term influence of SGLT2i on cardiac diseases.

Our analyses did not identify a causal link between SGLT2i and potential adverse events such as amputation, fracture, dehydration, urinary tract infection, and acute kidney injury. It is essential to interpret these findings within the context of the existing literature. The findings from well-designed systematic reviews and meta-analyses of randomized clinical trials that have established a causal relationship between SGLT2i and certain adverse effects, particularly urinary and reproductive tract infections and diabetic ketoacidosis.43,44 Little or no evidence was found for the effect of SGLT2i on limb amputation, blindness, eye disease, neuropathic pain, or health-related quality of life. 45 These findings highlight the importance of closely monitoring and managing potential safety concerns associated with SGLT2i use in clinical practice.

In summary, we analyzed the causal relationship between SGLT2i and diseases from a genetic variation perspective through the innovative use of MR. Our results indicated that SGLT2i may have potential protective effects against chronic glomerulonephritis, hypertensive nephropathy, and nephrotic syndrome. However, these results need to be verified in further clinical trials. This study provides a theoretical basis for expanding the clinical application scope of SGLT2i.

This study has several limitations. First, MR analysis is not a true randomized controlled trial, and the clinical benefits of the medication cannot be directly estimated merely based on P-values and ORs. 22 Second, in selecting instrumental variables, the P-value threshold for SNPs was set at 5 × 10−5 instead of the conventional 5 × 10−8, increasing the risk of false positives. Finally, the exposure and outcome data were derived from GWAS studies of European populations, preventing the analysis of drug responses across different races and ethnicities as performed in multicenter clinical trials. This limitation may contribute to the negative MR results for diabetic nephropathy and IgA nephropathy.

Conclusions

SGLT2i may act as protective factors against nephrotic syndrome, chronic glomerulonephritis, and hypertensive nephropathy, as revealed in drug-target MR.

Supplemental Material

sj-pdf-1-imr-10.1177_03000605241272639 - Supplemental material for Mendelian randomization study of sodium–glucose cotransporter 2 inhibitors in cardiac and renal diseases

Supplemental material, sj-pdf-1-imr-10.1177_03000605241272639 for Mendelian randomization study of sodium–glucose cotransporter 2 inhibitors in cardiac and renal diseases by Lei Chen, Yongdi Zuo, Manrong He, Lijin Duo and Wanxin Tang in Journal of International Medical Research

Acknowledgements

This study extensively used GWAS data from the IEU database. The authors thank the participants and investigators from the contributing studies; this research would not be possible without them.

Data availability statement

All data are publicly available. The data in this study can be found and downloaded with a search by GWAS ID of the IEU OpenGWAS project (https://gwas.mrcieu.ac.uk).

Supplementary material

Supplemental material for this article is available online.

Author contributions: All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Lei Chen, Yongdi Zuo, Manrong He, and Lijin Duo. The first draft of the manuscript was written by Lei Chen and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

The authors declare that there is no conflict of interest.

Funding: This study was supported by a Chengdu Science and Technology Bureau Grant (grant no. 2019-YF09-00090-SN) and the Science and Technology Department of Sichuan Province (grant no. 24ZDYF1187).

ORCID iD: Wanxin Tang https://orcid.org/0000-0001-6709-5591
==== Refs
References

1 Zelniker TA Braunwald E. Mechanisms of Cardiorenal Effects of Sodium-Glucose Cotransporter 2 Inhibitors: JACC State-of-the-Art Review. J Am Coll Cardiol 2020; 75 : 422–434. 2020/02/01. DOI: 10.1016/j.jacc.2019.11.031.32000955
2 Heerspink HJL Stefánsson BV Correa-Rotter R , et al . Dapagliflozin in Patients with Chronic Kidney Disease. N Engl J Med 2020; 383 : 1436–1446. 2020/09/25. DOI: 10.1056/NEJMoa2024816.32970396
3 Herrington WG Staplin N Wanner C , The EMPA-KIDNEY Collaborative Group , et al . Empagliflozin in Patients with Chronic Kidney Disease. N Engl J Med 2023; 388 : 117–127. 2022/11/05. DOI: 10.1056/NEJMoa2204233.36331190
4 Perkovic V Jardine MJ Neal B , et al . Canagliflozin and Renal Outcomes in Type 2 Diabetes and Nephropathy. N Engl J Med 2019; 380 : 2295–2306. 2019/04/17. DOI: 10.1056/NEJMoa1811744.30990260
5 Wheeler DC Stefánsson BV Jongs N , et al . Effects of dapagliflozin on major adverse kidney and cardiovascular events in patients with diabetic and non-diabetic chronic kidney disease: a prespecified analysis from the DAPA-CKD trial. Lancet Diabetes Endocrinol 2021; 9 : 22–31. 2020/12/19. DOI: 10.1016/s2213-8587(20)30369-7.33338413
6 Wheeler DC Toto RD Stefánsson BV , et al . A pre-specified analysis of the DAPA-CKD trial demonstrates the effects of dapagliflozin on major adverse kidney events in patients with IgA nephropathy. Kidney Int 2021; 100 : 215–224. 2021/04/21. DOI: 10.1016/j.kint.2021.03.033.33878338
7 EMPA-KIDNEY Collaborative Group . Impact of primary kidney disease on the effects of empagliflozin in patients with chronic kidney disease: secondary analyses of the EMPA-KIDNEY trial. Lancet Diabetes Endocrinol 2024; 12 : 51–60. 2023/12/08. DOI: 10.1016/s2213-8587(23)00322-4.38061372
8 Zannad F Ferreira JP Pocock SJ , et al . SGLT2 inhibitors in patients with heart failure with reduced ejection fraction: a meta-analysis of the EMPEROR-Reduced and DAPA-HF trials. Lancet 2020; 396 : 819–829. 2020/09/03. DOI: 10.1016/s0140-6736(20)31824-9.32877652
9 McMurray JJV DeMets DL Inzucchi SE , et al . A trial to evaluate the effect of the sodium-glucose co-transporter 2 inhibitor dapagliflozin on morbidity and mortality in patients with heart failure and reduced left ventricular ejection fraction (DAPA-HF). Eur J Heart Fail 2019; 21 : 665–675. 2019/03/22. DOI: 10.1002/ejhf.1432.30895697
10 Fitchett D Inzucchi SE Cannon CP , et al . Empagliflozin Reduced Mortality and Hospitalization for Heart Failure Across the Spectrum of Cardiovascular Risk in the EMPA-REG OUTCOME Trial. Circulation 2019; 139 : 1384–1395. 2018/12/28. DOI: 10.1161/circulationaha.118.037778.30586757
11 Wiviott SD Raz I Bonaca MP , et al . Dapagliflozin and Cardiovascular Outcomes in Type 2 Diabetes. N Engl J Med 2019; 380 : 347–357. 2018/11/13. DOI: 10.1056/NEJMoa1812389.30415602
12 Matsushita K Ballew SH Wang AY , et al . Epidemiology and risk of cardiovascular disease in populations with chronic kidney disease. Nat Rev Nephrol 2022; 18 : 696–707. 2022/09/15. DOI: 10.1038/s41581-022-00616-6.36104509
13 Neal B Perkovic V Mahaffey KW , et al . Canagliflozin and Cardiovascular and Renal Events in Type 2 Diabetes. N Engl J Med 2017; 377 : 644–657. 2017/06/13. DOI: 10.1056/NEJMoa1611925.28605608
14 Sanderson E Glymour MM Holmes MV , et al . Mendelian randomization. Nat Rev Methods Primers 2022; 2 : 6. 2022/02/10. DOI: 10.1038/s43586-021-00092-5.37325194
15 Davies NM Holmes MV Davey Smith G. Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians. BMJ 2018; 362 : k601. 2018/07/14. DOI: 10.1136/bmj.k601.30002074
16 Cohen P Cross D Jänne PA. Kinase drug discovery 20 years after imatinib: progress and future directions. Nat Rev Drug Discov 2021; 20 : 551–569. 2021/05/19. DOI: 10.1038/s41573-021-00195-4.34002056
17 Larsson SC Butterworth AS Burgess S. Mendelian randomization for cardiovascular diseases: principles and applications. Eur Heart J 2023; 44 : 4913–4924. 2023/11/08. DOI: 10.1093/eurheartj/ehad736.37935836
18 Woolf B Perry JA Hong CC , et al . Multi-biobank summary data Mendelian randomisation does not support a causal effect of IL-6 signalling on risk of pulmonary arterial hypertension. Eur Respir J 2024; 63 : 2302031. 2024/03/08. DOI: 10.1183/13993003.02031-2023.38453257
19 Zhang T An Y Shen Z , et al . Serum urate levels and neurodegenerative outcomes: a prospective cohort study and mendelian randomization analysis of the UK Biobank. Alzheimers Res Ther 2024; 16 : 106. 2024/05/11. DOI: 10.1186/s13195-024-01476-x.38730474
20 Zhang W Ma L Zhou Q , et al . Therapeutic Targets for Diabetic Kidney Disease: Proteome-Wide Mendelian Randomization and Colocalization Analyses. Diabetes 2024; 73 : 618–627. 2024/01/12. DOI: 10.2337/db23-0564.38211557
21 Lin J Zhou J Xu Y. Potential drug targets for multiple sclerosis identified through Mendelian randomization analysis. Brain 2023; 146 : 3364–3372. 2023/03/04. DOI: 10.1093/brain/awad070.36864689
22 Ference BA. Interpreting the Clinical Implications of Drug-Target Mendelian Randomization Studies. J Am Coll Cardiol 2022; 80 : 663–665. 2022/08/12. DOI: 10.1016/j.jacc.2022.06.007.35953132
23 Woolf B Rajasundaram S Cronjé HT , et al . A drug target for erectile dysfunction to help improve fertility, sexual activity, and wellbeing: mendelian randomisation study. BMJ 2023; 383 : e076197. 2023/12/13. DOI: 10.1136/bmj-2023-076197.38086555
24 Rosoff DB Bell AS Jung J , et al . Mendelian Randomization Study of PCSK9 and HMG-CoA Reductase Inhibition and Cognitive Function. J Am Coll Cardiol 2022; 80 : 653–662. 2022/08/12. DOI: 10.1016/j.jacc.2022.05.041.35953131
25 Schmidt AF Finan C Gordillo-Marañón M , et al . Genetic drug target validation using Mendelian randomisation. Nat Commun 2020; 11 : 3255. 2020/06/28. DOI: 10.1038/s41467-020-16969-0.32591531
26 Nangaku M. More reasons to use SGLT2 inhibitors: EMPEROR-reduced and DAPA-CKD. Kidney Int 2020; 98 : 1387–1389. 2020/10/18. DOI: 10.1016/j.kint.2020.10.002.33068607
27 Vallon V Verma S. Effects of SGLT2 Inhibitors on Kidney and Cardiovascular Function. Annu Rev Physiol 2021; 83 : 503–528. 2020/11/17. DOI: 10.1146/annurev-physiol-031620-095920.33197224
28 Wu H Gonzalez Villalobos R Yao X , et al . Mapping the single-cell transcriptomic response of murine diabetic kidney disease to therapies. Cell Metab 2022; 34 : 1064–1078.e1066. 2022/06/17. DOI: 10.1016/j.cmet.2022.05.010.35709763
29 Lee YH Kim SH Kang JM , et al . Empagliflozin attenuates diabetic tubulopathy by improving mitochondrial fragmentation and autophagy. Am J Physiol Renal Physiol 2019; 317 : F767–F780. 2019/08/08. DOI: 10.1152/ajprenal.00565.2018.31390268
30 Wu J Sun Z Yang S , et al . Kidney single-cell transcriptome profile reveals distinct response of proximal tubule cells to SGLT2i and ARB treatment in diabetic mice. Mol Ther 2022; 30 : 1741–1753. 2021/10/23. DOI: 10.1016/j.ymthe.2021.10.013.34678510
31 Jongs N Greene T Chertow GM , et al . Effect of dapagliflozin on urinary albumin excretion in patients with chronic kidney disease with and without type 2 diabetes: a prespecified analysis from the DAPA-CKD trial. Lancet Diabetes Endocrinol 2021; 9 : 755–766. 2021/10/08. DOI: 10.1016/s2213-8587(21)00243-6.34619106
32 Perkovic V De Zeeuw D Mahaffey KW , et al . Canagliflozin and renal outcomes in type 2 diabetes: results from the CANVAS Program randomised clinical trials. Lancet Diabetes Endocrinol 2018; 6 : 691–704. 2018/06/26. DOI: 10.1016/s2213-8587(18)30141-4.29937267
33 Packer M Butler J Zannad F , et al . Effect of Empagliflozin on Worsening Heart Failure Events in Patients With Heart Failure and Preserved Ejection Fraction: EMPEROR-Preserved Trial. Circulation 2021; 144 : 1284–1294. 2021/08/31. DOI: 10.1161/circulationaha.121.056824.34459213
34 Packer M Anker SD Butler J , et al . Effect of Empagliflozin on the Clinical Stability of Patients With Heart Failure and a Reduced Ejection Fraction: The EMPEROR-Reduced Trial. Circulation 2021; 143 : 326–336. 2020/10/22. DOI: 10.1161/circulationaha.120.051783.33081531
35 Zelniker TA Bonaca MP Furtado RHM , et al . Effect of Dapagliflozin on Atrial Fibrillation in Patients With Type 2 Diabetes Mellitus: Insights From the DECLARE-TIMI 58 Trial. Circulation 2020; 141 : 1227–1234. 2020/01/28. DOI: 10.1161/circulationaha.119.044183.31983236
36 Udell JA Jones WS Petrie MC , et al . Sodium Glucose Cotransporter-2 Inhibition for Acute Myocardial Infarction: JACC Review Topic of the Week. J Am Coll Cardiol 2022; 79 : 2058–2068. 2022/05/20. DOI: 10.1016/j.jacc.2022.03.353.35589167
37 Kaplinsky E. DAPA-HF trial: dapagliflozin evolves from a glucose-lowering agent to a therapy for heart failure. Drugs Context 2020; 9 : 2019-11-3. 2020/03/14. DOI: 10.7573/dic.2019-11-3.
38 Kang S Verma S Hassanabad AF , et al . Direct Effects of Empagliflozin on Extracellular Matrix Remodelling in Human Cardiac Myofibroblasts: Novel Translational Clues to Explain EMPA-REG OUTCOME Results. Can J Cardiol 2020; 36 : 543–553. 2019/12/16. DOI: 10.1016/j.cjca.2019.08.033.31837891
39 De Boer IH. The expanding résumé of SGLT2 inhibitors. Lancet Diabetes Endocrinol 2019; 7 : 585–587. 2019/06/15. DOI: 10.1016/s2213-8587(19)30183-4.31196816
40 Inzucchi SE Zinman B Fitchett D , et al . How Does Empagliflozin Reduce Cardiovascular Mortality? Insights From a Mediation Analysis of the EMPA-REG OUTCOME Trial. Diabetes Care 2018; 41 : 356–363. 2017/12/06. DOI: 10.2337/dc17-1096.29203583
41 Ferrannini E Muscelli E Frascerra S , et al . Metabolic response to sodium-glucose cotransporter 2 inhibition in type 2 diabetic patients. J Clin Invest 2014; 124 : 499–508. 2014/01/28. DOI: 10.1172/jci72227.24463454
42 Herat LY Magno AL Rudnicka C , et al . SGLT2 Inhibitor-Induced Sympathoinhibition: A Novel Mechanism for Cardiorenal Protection. JACC Basic Transl Sci 2020; 5 : 169–179. 2020/03/07. DOI: 10.1016/j.jacbts.2019.11.007.32140623
43 Xu C He L Zhang J , et al . The Cardiovascular Benefits and Infections Risk of SGLT2i versus Metformin in Type 2 Diabetes: A Systemic Review and Meta-Analysis. Metabolites 2022; 12 : 979. 2022/10/28. DOI: 10.3390/metabo12100979.36295882
44 Marilly E Cottin J Cabrera N , et al . SGLT2 inhibitors in type 2 diabetes: a systematic review and meta-analysis of cardiovascular outcome trials balancing their risks and benefits. Diabetologia 2022; 65 : 2000–2010. 2022/08/05. DOI: 10.1007/s00125-022-05773-8.35925319
45 Palmer SC Tendal B Mustafa RA , et al . Sodium-glucose cotransporter protein-2 (SGLT-2) inhibitors and glucagon-like peptide-1 (GLP-1) receptor agonists for type 2 diabetes: systematic review and network meta-analysis of randomised controlled trials. BMJ 2021; 372 : m4573. 2021/01/15. DOI: 10.1136/bmj.m4573.33441402
