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Related Concept Videos

Type II Diabetes I: Introduction01:26

Type II Diabetes I: Introduction

Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder characterized by insulin resistance, in which target tissues such as the liver, muscle, and adipose tissue respond poorly to insulin. It is also associated with inadequate compensatory insulin secretion, where pancreatic β-cells fail to produce sufficient insulin. Together, these abnormalities lead to persistent hyperglycemia.EtiologyT2DM develops through a complex interaction of genetic predisposition and environmental or...
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Pharmacogenetic Phenotypes: Alterations in Pharmacokinetics, Drug Targets and Biologic Milieu

Genetic variations significantly influence drug response through pharmacokinetics, receptor interactions, and biologic milieu modifications. Pharmacokinetic alterations impact drug metabolism and clearance, affecting efficacy and toxicity. Variants in drug-metabolizing enzymes, such as CYP2C9 and CYP2C19, alter drug activation and elimination. For example, CYP2C9 loss-of-function variants require lower warfarin doses to prevent excessive bleeding, while CYP2C19 variants reduce clopidogrel...
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Type II Diabetes II: Pathophysiology

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Drug Dosing in Renal Diseases: Estimation of Glomerular Filtration Rate Based on Serum Creatinine Concentration01:28

Drug Dosing in Renal Diseases: Estimation of Glomerular Filtration Rate Based on Serum Creatinine Concentration

Glomerular filtration rate (GFR) can be estimated from serum creatinine using the modification of diet in renal disease (MDRD) formula or the chronic kidney disease–epidemiology collaboration (CKD–EPI) equation. Both methods are widely used in clinical practice to assess kidney function and guide treatment decisions.The MDRD equation does not require weight or height measurements and is normalized to the body surface area of 1.73 m², considered the average adult surface area. This equation is...
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Comparative Proteomic Analysis of Whole Kidney, Medulla, and Cortical Tubules in Diabetic Pathogenesis of Kidney Injury in Mice
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Comparative Proteomic Analysis of Whole Kidney, Medulla, and Cortical Tubules in Diabetic Pathogenesis of Kidney Injury in Mice

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Phenotype-genotype interactions on renal function in type 2 diabetes: an analysis using structural equation

X Y Song1, S Y Lee, R C W Ma

  • 1Department of Statistics, The Chinese University of Hong Kong, Shatin, Hong Kong, SAR, People's Republic of China.

Diabetologia
|May 30, 2009
PubMed
Summary
This summary is machine-generated.

Structural equation modeling reveals how obesity, lipids, and blood pressure interact with genetic factors to impact kidney function in type 2 diabetes. These findings highlight potential therapeutic targets for managing diabetic kidney disease.

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Modeling and Evaluation of Murine Diabetic Cardiomyopathy Model

Published on: November 29, 2024

Area of Science:

  • Cardiovascular and renal medicine
  • Genetics and personalized medicine
  • Diabetes research

Background:

  • Cardiovascular and renal diseases share common risk factors.
  • Type 2 diabetes is a major risk factor for both cardiovascular and renal complications.
  • Understanding the interplay between genetic and phenotypic factors is crucial for managing these conditions.

Purpose of the Study:

  • To evaluate the independent and combined effects of cardiovascular disease-related phenotypes and genotypes on renal function in type 2 diabetes.
  • To utilize structural equation modeling (SEM) to analyze complex interactions.
  • To identify key determinants of renal function in diabetic patients.

Main Methods:

  • 1,188 type 2 diabetic patients were stratified into high-risk and low-risk groups.
  • Non-linear SEMs with Bayesian estimation were used to model inter-relationships among variables and latent factors.
  • Analysis included continuous and categorical data, assessing goodness-of-fit.

Main Results:

  • Phenotypic factors (obesity, glycaemia, lipids, blood pressure) and genotypes (NOS, ADRB, RAS, PPARG, etc.) were loaded onto latent factors.
  • Latent factors of obesity, lipids, and blood pressure interacted with ADRB and RAS genotypes to influence renal function.
  • These combined factors explained 39-80% of the variance in renal function across risk groups.

Conclusions:

  • SEM is effective for quantifying interactions between biological pathways and genetic determinants.
  • Combined effects of blood pressure, lipids, and obesity on renal function have therapeutic implications.
  • Targeting these interactive pathways may be beneficial for type 2 diabetic individuals with genetic predispositions to kidney disease.