The Role of CYP8B1 Polymorphisms in Modulating the Biochemical Pathways Affected by SGLT2 Inhibitors in T2DM and Obesity

Overview

This study explores the long-term effects of dapagliflozin and empagliflozin on CYP8B1 gene expression and a range of metabolic, oxidative, and inflammatory biomarkers in obese patients with Type 2 Diabetes Mellitus (T2DM). Over a 6-month period, participants are assigned to three treatment arms: metformin (control), dapagliflozin, and empagliflozin. The study aims to determine how these medications influence bile acid metabolism, oxidative stress, leptin, GLP-1, IL-10, and IFN-γ, providing insight into the broader metabolic benefits of SGLT2 inhibitors

Detailed Description Type 2 Diabetes Mellitus (T2DM) and obesity are major global health burdens with shared pathophysiological mechanisms, including insulin resistance, chronic inflammation, and altered lipid metabolism. SGLT2 inhibitors, such as empagliflozin and dapagliflozin, have emerged as effective glucose-lowering agents that also offer additional benefits, including weight reduction, cardiovascular protection, and renal function preservation. Despite these advantages, the therapeutic response to SGLT2 inhibitors is variable, often influenced by individual genetic differences. A key genetic determinant is CYP8B1 (cytochrome P450 family 8 subfamily B member 1), a gene encoding sterol 12-alpha-hydroxylase, which regulates bile acid synthesis and lipid metabolism. Polymorphisms in CYP8B1 may impact drug metabolism and alter bile acid-mediated metabolic regulation, potentially affecting both the efficacy and safety profile of SGLT2 inhibitors. This clinical trial aims to investigate the role of CYP8B1 genetic variations in modifying the clinical and biochemical responses to empagliflozin and dapagliflozin therapy among obese patients recently diagnosed with T2DM. Participants will be randomized into three groups: * Group 1: Empagliflozin 10 mg daily * Group 2: Dapagliflozin 10 mg daily * Group 3 (Control): Standard care (lifestyle modification and/or metformin) The intervention period is 6 months, during which multiple parameters will be monitored: 1. Obesity-Related Metrics: Body weight, BMI, waist circumference, and body fat percentage. 2. Adipokines: adiponectin. 3. Lipid Profile: Total cholesterol, HDL, LDL, and triglycerides. 4. Glycemic Control: Fasting glucose, HbA1c, and C-peptide. 5. Oxidative Stress \& Inflammation 6. Ketone Bodies \& Free Fatty Acids: To assess shifts in metabolic fuel utilization. 7. Insulin Sensitivity: Using QUICKI and Adipo-IR indices. 8. CYP8B1 Genotyping \& Expression: PCR-based genotyping and qPCR-based expression profiling to evaluate genetic and transcriptional regulation. The study integrates molecular genetics (Sanger sequencing and RT-PCR) with clinical biochemistry and metabolic phenotyping to provide a holistic understanding of pharmacogenomic effects. Expected outcomes include: • Determining whether CYP8B1 polymorphisms influence the degree of weight loss, lipid and glucose metabolism, and adipokine modulation. * Comparing the efficacy of empagliflozin vs dapagliflozin in the presence of different CYP8B1 genotypes. * Proposing a framework for personalized T2DM and obesity management based on genetic screening. Study Type Observational Clinical Trial \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Study Duration Estimated Study Period: 6 months per participant \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Eligibility Criteria Inclusion Criteria: * Aged ≥18 years * Newly diagnosed T2DM (\<6 months) * BMI ≥30 kg/m² * No prior antidiabetic treatment * Consent to genetic testing Exclusion Criteria: • Type 1 diabetes or secondary diabetes • Severe renal impairment (eGFR \<45 mL/min/1.73 m²) • Liver dysfunction or active liver disease * Pregnancy or lactation * Allergy to SGLT2 inhibitors Primary Outcome Measures • Change in body weight and BMI at 6 months * Genotype-specific differences in weight loss Secondary Outcome Measures * Changes in adipokine levels * Lipid profile changes * HbA1c and fasting blood glucose improvement * Differences in insulin sensitivity indices * Expression levels of CYP8B1 mRNA * Relationship between genotype and biochemical/metabolic outcomes Statistical Analysis Plan * Paired t-tests and ANOVA for within-group and between-group comparisons * Genotype-phenotype association using chi-square and regression models * ROC curve analysis for predicting treatment response * Cox regression for time-to-event data