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Aref H, Hammad S, Darwish KM, Elgawish MS. Unveiling Pharmacokinetics and Drug Interaction of Linagliptin and Pioglitazone HCl in Rat Plasma Using LC-MS/MS. Chem Res Toxicol 2024; 37:779-790. [PMID: 38684131 DOI: 10.1021/acs.chemrestox.4c00038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/02/2024]
Abstract
The linagliptin (LIN) and pioglitazone HCl (PIO) combination, currently undergoing phase III clinical trials for diabetes mellitus treatment, demonstrated significant improvements in glycemic control. However, the absence of an analytical method for simultaneous determination in biological fluids highlights a crucial gap. This underscores the pressing need for sensitive bioanalytical methods, emphasizing the paramount importance of developing such tools to advance diabetes management strategies and enhance patient care. Herein, a sensitive reverse-phase high-performance liquid chromatography-electrospray ionization-tandem mass spectrometry method was developed for simultaneous determination of LIN and PIO in rat plasma using alogliptin as an internal standard. Chromatographic separation was performed on an Agilent Eclipse Plus C18 (4.6 × 100 mm, 3.5 μm) using an isocratic mobile phase system consisting of ammonium formate (pH 4.5) and methanol using an acetonitrile-induced protein precipitation technique for sample preparation. Multiple reaction monitoring in positive ion mode was used for quantitation of the precursor to production at m/z 473.2 → 419.9 for LIN, 357.1 → 134.2 for PIO, and 340.3 → 116.1 for ALO. The linearity range was 0.5 to 100 and 1 to 2000 ng/mL for LIN and PIO, respectively. The developed method was validated as per US-FDA guidelines and successfully applied to clinical pharmacokinetic and drug-drug interaction studies with a single oral administration of LIN and PIO in rat plasma. Pharmacokinetic parameters of LIN were significantly influenced by the concomitant administration of PIO and vice versa. Molecular modeling revealed the significant interaction of LIN and PIO with P-glycoprotein. Therefore, the drug-drug interaction between LIN and PIO deserves further study to improve drug therapy and prevent dangerous adverse effects.
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Affiliation(s)
- Heba Aref
- Medicinal Chemistry Department, Faculty of Pharmacy, Suez Canal University, Ismailia 41522, Egypt
- Medicinal Chemistry Department, Faculty of Pharmacy, El Menoufia University, El Menoufia, Shebin El Kom 32511, Egypt
| | - Sherin Hammad
- Analytical Chemistry Department, Faculty of Pharmacy, Tanta University, Tanta 31511, Egypt
| | - Khaled M Darwish
- Medicinal Chemistry Department, Faculty of Pharmacy, Suez Canal University, Ismailia 41522, Egypt
| | - Mohamed S Elgawish
- Medicinal Chemistry Department, Faculty of Pharmacy, Suez Canal University, Ismailia 41522, Egypt
- Chemistry Department, Korea University, Seoul 02841, Korea Republic
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Kanie T, Mizuno A, Takaoka Y, Suzuki T, Yoneoka D, Nishikawa Y, Tam WWS, Morze J, Rynkiewicz A, Xin Y, Wu O, Providencia R, Kwong JS. Dipeptidyl peptidase-4 inhibitors, glucagon-like peptide 1 receptor agonists and sodium-glucose co-transporter-2 inhibitors for people with cardiovascular disease: a network meta-analysis. Cochrane Database Syst Rev 2021; 10:CD013650. [PMID: 34693515 PMCID: PMC8812344 DOI: 10.1002/14651858.cd013650.pub2] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
BACKGROUND Cardiovascular disease (CVD) is a leading cause of death globally. Recently, dipeptidyl peptidase-4 inhibitors (DPP4i), glucagon-like peptide-1 receptor agonists (GLP-1RA) and sodium-glucose co-transporter-2 inhibitors (SGLT2i) were approved for treating people with type 2 diabetes mellitus. Although metformin remains the first-line pharmacotherapy for people with type 2 diabetes mellitus, a body of evidence has recently emerged indicating that DPP4i, GLP-1RA and SGLT2i may exert positive effects on patients with known CVD. OBJECTIVES To systematically review the available evidence on the benefits and harms of DPP4i, GLP-1RA, and SGLT2i in people with established CVD, using network meta-analysis. SEARCH METHODS We searched CENTRAL, MEDLINE, Embase, and the Conference Proceedings Citation Index on 16 July 2020. We also searched clinical trials registers on 22 August 2020. We did not restrict by language or publication status. SELECTION CRITERIA We searched for randomised controlled trials (RCTs) investigating DPP4i, GLP-1RA, or SGLT2i that included participants with established CVD. Outcome measures of interest were CVD mortality, fatal and non-fatal myocardial infarction, fatal and non-fatal stroke, all-cause mortality, hospitalisation for heart failure (HF), and safety outcomes. DATA COLLECTION AND ANALYSIS Three review authors independently screened the results of searches to identify eligible studies and extracted study data. We used the GRADE approach to assess the certainty of the evidence. We conducted standard pairwise meta-analyses and network meta-analyses by pooling studies that we assessed to be of substantial homogeneity; subgroup and sensitivity analyses were also pursued to explore how study characteristics and potential effect modifiers could affect the robustness of our review findings. We analysed study data using the odds ratios (ORs) and log odds ratios (LORs) with their respective 95% confidence intervals (CIs) and credible intervals (Crls), where appropriate. We also performed narrative synthesis for included studies that were of substantial heterogeneity and that did not report quantitative data in a usable format, in order to discuss their individual findings and relevance to our review scope. MAIN RESULTS We included 31 studies (287 records), of which we pooled data from 20 studies (129,465 participants) for our meta-analysis. The majority of the included studies were at low risk of bias, using Cochrane's tool for assessing risk of bias. Among the 20 pooled studies, six investigated DPP4i, seven studied GLP-1RA, and the remaining seven trials evaluated SGLT2i. All outcome data described below were reported at the longest follow-up duration. 1. DPP4i versus placebo Our review suggests that DPP4i do not reduce any risk of efficacy outcomes: CVD mortality (OR 1.00, 95% CI 0.91 to 1.09; high-certainty evidence), myocardial infarction (OR 0.97, 95% CI 0.88 to 1.08; high-certainty evidence), stroke (OR 1.00, 95% CI 0.87 to 1.14; high-certainty evidence), and all-cause mortality (OR 1.03, 95% CI 0.96 to 1.11; high-certainty evidence). DPP4i probably do not reduce hospitalisation for HF (OR 0.99, 95% CI 0.80 to 1.23; moderate-certainty evidence). DPP4i may not increase the likelihood of worsening renal function (OR 1.08, 95% CI 0.88 to 1.33; low-certainty evidence) and probably do not increase the risk of bone fracture (OR 1.00, 95% CI 0.83 to 1.19; moderate-certainty evidence) or hypoglycaemia (OR 1.11, 95% CI 0.95 to 1.29; moderate-certainty evidence). They are likely to increase the risk of pancreatitis (OR 1.63, 95% CI 1.12 to 2.37; moderate-certainty evidence). 2. GLP-1RA versus placebo Our findings indicate that GLP-1RA reduce the risk of CV mortality (OR 0.87, 95% CI 0.79 to 0.95; high-certainty evidence), all-cause mortality (OR 0.88, 95% CI 0.82 to 0.95; high-certainty evidence), and stroke (OR 0.87, 95% CI 0.77 to 0.98; high-certainty evidence). GLP-1RA probably do not reduce the risk of myocardial infarction (OR 0.89, 95% CI 0.78 to 1.01; moderate-certainty evidence), and hospitalisation for HF (OR 0.95, 95% CI 0.85 to 1.06; high-certainty evidence). GLP-1RA may reduce the risk of worsening renal function (OR 0.61, 95% CI 0.44 to 0.84; low-certainty evidence), but may have no impact on pancreatitis (OR 0.96, 95% CI 0.68 to 1.35; low-certainty evidence). We are uncertain about the effect of GLP-1RA on hypoglycaemia and bone fractures. 3. SGLT2i versus placebo This review shows that SGLT2i probably reduce the risk of CV mortality (OR 0.82, 95% CI 0.70 to 0.95; moderate-certainty evidence), all-cause mortality (OR 0.84, 95% CI 0.74 to 0.96; moderate-certainty evidence), and reduce the risk of HF hospitalisation (OR 0.65, 95% CI 0.59 to 0.71; high-certainty evidence); they do not reduce the risk of myocardial infarction (OR 0.97, 95% CI 0.84 to 1.12; high-certainty evidence) and probably do not reduce the risk of stroke (OR 1.12, 95% CI 0.92 to 1.36; moderate-certainty evidence). In terms of treatment safety, SGLT2i probably reduce the incidence of worsening renal function (OR 0.59, 95% CI 0.43 to 0.82; moderate-certainty evidence), and probably have no effect on hypoglycaemia (OR 0.90, 95% CI 0.75 to 1.07; moderate-certainty evidence) or bone fracture (OR 1.02, 95% CI 0.88 to 1.18; high-certainty evidence), and may have no impact on pancreatitis (OR 0.85, 95% CI 0.39 to 1.86; low-certainty evidence). 4. Network meta-analysis Because we failed to identify direct comparisons between each class of the agents, findings from our network meta-analysis provided limited novel insights. Almost all findings from our network meta-analysis agree with those from the standard meta-analysis. GLP-1RA may not reduce the risk of stroke compared with placebo (OR 0.87, 95% CrI 0.75 to 1.0; moderate-certainty evidence), which showed similar odds estimates and wider 95% Crl compared with standard pairwise meta-analysis. Indirect estimates also supported comparison across all three classes. SGLT2i was ranked the best for CVD and all-cause mortality. AUTHORS' CONCLUSIONS Findings from both standard and network meta-analyses of moderate- to high-certainty evidence suggest that GLP-1RA and SGLT2i are likely to reduce the risk of CVD mortality and all-cause mortality in people with established CVD; high-certainty evidence demonstrates that treatment with SGLT2i reduce the risk of hospitalisation for HF, while moderate-certainty evidence likely supports the use of GLP-1RA to reduce fatal and non-fatal stroke. Future studies conducted in the non-diabetic CVD population will reveal the mechanisms behind how these agents improve clinical outcomes irrespective of their glucose-lowering effects.
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Affiliation(s)
- Takayoshi Kanie
- Department of Cardiology, St. Luke's International Hospital, Tokyo, Japan
| | - Atsushi Mizuno
- Department of Cardiology, St. Luke's International Hospital, Tokyo, Japan
- Penn Medicine Nudge Unit, University of Pennsylvania Philadelphia, Philadelphia, PA, USA
- Leonard Davis Institute for Health Economics, University of Pennsylvania, Philadelphia, PA, USA
- Division of Cardiovascular Medicine, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
| | - Yoshimitsu Takaoka
- Department of Cardiology, St. Luke's International Hospital, Tokyo, Japan
| | - Takahiro Suzuki
- Department of Cardiology, St. Luke's International Hospital, Tokyo, Japan
| | - Daisuke Yoneoka
- Division of Biostatistics and Bioinformatics, Graduate School of Public Health, St. Luke's International University, Tokyo, Japan
| | - Yuri Nishikawa
- Department of Gerontological Nursing and Healthcare Systems Management, Graduate School of Health Care Sciences, Tokyo Medical and Dental University, Tokyo, Japan
- Department of Gerontological Nursing, Kyorin University, Tokyo, Japan
| | - Wilson Wai San Tam
- Alice Lee Center for Nursing Studies, NUS Yong Loo Lin School of Medicine, Singapore, Singapore
| | - Jakub Morze
- Department of Human Nutrition, University of Warmia and Mazury, Olsztyn, Poland
| | - Andrzej Rynkiewicz
- Department of Cardiology and Cardiosurgery, School of Medicine, University of Warmia and Mazury, Olsztyn, Poland
| | - Yiqiao Xin
- Health Economics and Health Technology Assessment (HEHTA), Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Olivia Wu
- Health Economics and Health Technology Assessment (HEHTA), Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Rui Providencia
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, UK
| | - Joey Sw Kwong
- Global Health Nursing, Graduate School of Nursing Science, St. Luke's International University, Tokyo, Japan
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Wei Y, Yu J, Zhang X, Mu J, Zhang J, Zeng W, Feng B. ICAT acts as a Coactivator in Regulating PPARγ Transcriptional Activity in Mesangial Cells. Exp Clin Endocrinol Diabetes 2020; 129:365-373. [PMID: 32937668 DOI: 10.1055/a-0879-1846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
AIMS Our study aims to explore the role of β-catenin interaction protein-1(ICAT) in regulating peroxisome proliferator-activated receptor γ (PPARγ) transcriptional activity in mesangial cells. The abnormal ICAT expression in mesangial cells under high glucose(HG) contributes to the development of diabetes and its complications such as diabetic nephropathy (DN). METHODS Human mesangial cells (HMCs) were cultured in either 5.5 (normal control) or 30 (high glucose) mmol/L glucose medium. Overexpression and knock-down of ICAT or β-catenin were carried out by transient transfection. PPARγ transcriptional activity was evaluated by luciferase assay. Protein-protein interactions were tested by Coimmunoprecipitation and GST-pull down assay. Cell phenotype transition of HMCs was detected by the expression level of α-SMA and fibronectin, as well as MTT assay. RESULTS High β-catenin protein expression but low ICAT was accompanied by low PPARγ transcriptional activity in HMCs cultured in HG. By using bioinformatics prediction, protein-protein and protein-DNA interaction experimental methods, ICAT and β-catenin were confirmed to act as coactivators in regulating PPARγ transcriptional activity. Overexpression of ICAT could mitigate the decrease of PPARγ transcriptional activity and partly relieve cell phenotype transition in HMCs. CONCLUSIONS β-catenin and ICAT interact as coactivator to modulate PPARγ transcriptional activation. In HMCs cultured in HG, the low expression of ICAT leads to low PPARγ transcriptional activation.
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Affiliation(s)
- Yi Wei
- Department of Nephrology, Xinqiao Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - Jiawei Yu
- Department of Nephrology, Xinqiao Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | | | - Jiao Mu
- Department of Nephrology, Xinqiao Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - Jun Zhang
- Department of Nephrology, Xinqiao Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - Wei Zeng
- Department of Nephrology, Xinqiao Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - Bing Feng
- Department of Nephrology, Xinqiao Hospital, Third Military Medical University (Army Medical University), Chongqing, China
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Maloney A, Rosenstock J, Fonseca V. A Model-Based Meta-Analysis of 24 Antihyperglycemic Drugs for Type 2 Diabetes: Comparison of Treatment Effects at Therapeutic Doses. Clin Pharmacol Ther 2019; 105:1213-1223. [PMID: 30457671 DOI: 10.1002/cpt.1307] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Accepted: 11/08/2018] [Indexed: 11/11/2022]
Abstract
Model-based meta-analysis was used to compare glycemic control, weight changes, and hypoglycemia risk across 24 antihyperglycemic drugs used to treat type 2 diabetes. Electronic searches identified 229 randomized controlled studies comprising 121,914 patients. To ensure fair and unbiased treatment comparisons, the analyses adjusted for important differences between studies, including duration of treatment, baseline glycated hemoglobin, and drug dosages. At the approved doses, glycemic control was typically greatest with glucagon-like peptide 1 receptor agonists (GLP-1RAs), and least with dipeptidyl peptidase-4 (DPP-4) inhibitors. Weight loss was highly variable across GLP-1RAs but was similar across sodium-glucose cotransporter 2 (SGLT2) inhibitors. Large weight increases were observed with sulfonylureas and thiazolidinediones. Hypoglycemia risk was highest with sulfonylureas, although gliclazide was notably lower. Hypoglycemia risk for DPP-4 inhibitors, SGLT2 inhibitors, and thiazolidinediones was generally very low but increased slightly for both GLP-1RAs and metformin. In summary, important differences between and within drug classes were identified.
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Affiliation(s)
| | - Julio Rosenstock
- Dallas Diabetes Research Center at Medical City, Dallas, Texas, USA
| | - Vivian Fonseca
- Tulane University Health Sciences Center, New Orleans, Louisiana, USA
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Gomes GKA, de Camargos Ramos AI, de Sousa CT, Sanches C, Pereira ML, Baldoni AO. Linagliptin safety profile: A systematic review. Prim Care Diabetes 2018; 12:477-490. [PMID: 29853297 DOI: 10.1016/j.pcd.2018.04.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2017] [Revised: 04/24/2018] [Accepted: 04/25/2018] [Indexed: 01/26/2023]
Abstract
OBJECTIVE To describe the safety profile of linagliptin. METHODOLOGY Systematic review using PubMed/MEDLINE, BVS and Web of Science. The search strategy "Linagliptin" AND "safety" was used. The inclusion criteria were clinical trials with a control group composed of conventional DM2 pharmacotherapy. RESULTS We identified 16 studies, and the most frequent adverse events (AEs) were nasopharyngitis with linagliptin at 5 and 10mg in monotherapy (31.6% and 29.6%, respectively) and gastrointestinal events (>10.0%) with linagliptin in combination. Of the AEs, 14.9 (±3.1)% were associated with the use of linagliptin in monotherapy, and 17.6 (±6.0)% in combination. The linagliptin AEs have a varied occurrence and frequency, ranging from mild to moderate intensity.
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Affiliation(s)
- Gabrielle Kéfrem Alves Gomes
- Universidade Federal de São João del-Rei, Campus Centro Oeste Dona Lindu, Rua Sebastião Gonçalves Coelho, 400, Bairro Chanadour, CEP 35501-296, Divinópolis, MG, Brazil; Grupo de Pesquisa em Epidemiologia e Avaliação de Novas Tecnologias em Saúde, GPEANTS, UFSJ/CNPq, Brazil.
| | - Aline Istéfane de Camargos Ramos
- Universidade Federal de São João del-Rei, Campus Centro Oeste Dona Lindu, Rua Sebastião Gonçalves Coelho, 400, Bairro Chanadour, CEP 35501-296, Divinópolis, MG, Brazil; Grupo de Pesquisa em Epidemiologia e Avaliação de Novas Tecnologias em Saúde, GPEANTS, UFSJ/CNPq, Brazil.
| | - Camila Tavares de Sousa
- Universidade Federal de São João del-Rei, Campus Centro Oeste Dona Lindu, Rua Sebastião Gonçalves Coelho, 400, Bairro Chanadour, CEP 35501-296, Divinópolis, MG, Brazil; Grupo de Pesquisa em Epidemiologia e Avaliação de Novas Tecnologias em Saúde, GPEANTS, UFSJ/CNPq, Brazil.
| | - Cristina Sanches
- Universidade Federal de São João del-Rei, Campus Centro Oeste Dona Lindu, Rua Sebastião Gonçalves Coelho, 400, Bairro Chanadour, CEP 35501-296, Divinópolis, MG, Brazil; Grupo de Pesquisa em Epidemiologia e Avaliação de Novas Tecnologias em Saúde, GPEANTS, UFSJ/CNPq, Brazil.
| | - Mariana Linhares Pereira
- Universidade Federal de São João del-Rei, Campus Centro Oeste Dona Lindu, Rua Sebastião Gonçalves Coelho, 400, Bairro Chanadour, CEP 35501-296, Divinópolis, MG, Brazil; Grupo de Pesquisa em Epidemiologia e Avaliação de Novas Tecnologias em Saúde, GPEANTS, UFSJ/CNPq, Brazil.
| | - André Oliveira Baldoni
- Universidade Federal de São João del-Rei, Campus Centro Oeste Dona Lindu, Rua Sebastião Gonçalves Coelho, 400, Bairro Chanadour, CEP 35501-296, Divinópolis, MG, Brazil; Grupo de Pesquisa em Epidemiologia e Avaliação de Novas Tecnologias em Saúde, GPEANTS, UFSJ/CNPq, Brazil.
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