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Related Concept Videos

Drug Dosing in Renal Diseases: Measurement of Glomerular Filtration Rate01:25

Drug Dosing in Renal Diseases: Measurement of Glomerular Filtration Rate

The glomerular filtration rate (GFR) is a critical indicator of kidney health, reflecting how well the kidneys filter blood. Changes in GFR can signal potential kidney impairment, necessitating accurate measurement methods to monitor kidney function effectively.Various molecules can serve as markers for GFR measurement, with the ideal marker meeting several specific criteria. It must freely filter at the glomerulus, avoid reabsorption or secretion by the renal tubules, remain unmetabolized, not...
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...
Glomerular Filtration Rate and its Regulation01:28

Glomerular Filtration Rate and its Regulation

The Glomerular Filtration Rate (GFR) is a measure of kidney function, reflecting the volume of filtrate formed per minute in the kidneys. On average, GFR is approximately 125 mL/min in males and 105 mL/min in females. Maintaining a relatively constant GFR is essential for the kidneys to effectively regulate body fluid homeostasis and maintain extracellular stability.
GFR regulation involves two primary intrinsic controls: the myogenic and tubuloglomerular feedback mechanisms.
The myogenic...
Drug Dosing in Renal Diseases: Measurement of Serum Creatinine Concentration and Clearance01:25

Drug Dosing in Renal Diseases: Measurement of Serum Creatinine Concentration and Clearance

In healthy individuals, serum creatinine levels remain stable due to a balance between its constant production—primarily from muscle metabolism—and renal excretion. Creatinine is freely filtered by the glomeruli, making it a valuable marker for estimating renal function. When the glomerular filtration rate (GFR) decreases, the kidneys can only eliminate less creatinine, causing serum levels to rise.Serum creatinine concentration is widely used to estimate creatinine clearance (Clcr), a...
Renal Clearance01:23

Renal Clearance

The glomerular filtration rate (GFR) is a critical marker of kidney function, reflecting the efficiency of filtration by the glomeruli. Renal clearance of specific substances, such as inulin or creatinine, is commonly used to measure GFR.
Renal clearance refers to the volume of plasma cleared of a specific substance, such as creatinine, per unit of time. To measure clearance, urine samples are collected over a 24-hour period during each bladder voiding, followed by a single blood sample at the...
Factors Affecting Renal Clearance: Renal Impairment01:17

Factors Affecting Renal Clearance: Renal Impairment

Renal dysfunction significantly impairs the renal clearance of drugs, leading to potential complications in drug therapy. Renal failure, which can be caused by various factors, poses a significant challenge in the elimination of drugs from the body.
One condition associated with renal failure is uremia. Uremia is characterized by impaired glomerular filtration and fluid accumulation in the body. This condition hinders the renal clearance of drugs, resulting in drug accumulation and potential...

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A High-throughput Method for Measurement of Glomerular Filtration Rate in Conscious Mice
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Using multiple measures for quantitative trait association analyses: application to estimated glomerular filtration

Adrienne Tin1, Elizabeth Colantuoni, Eric Boerwinkle

  • 1Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. atin@jhsph.edu

Journal of Human Genetics
|March 29, 2013
PubMed
Summary

Using multiple measures of kidney function, like estimated glomerular filtration rate (eGFR), increases statistical power in genetic association studies. Careful consideration of measurement error correlations is key for accurate results.

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Area of Science:

  • Genetics
  • Biostatistics
  • Nephrology

Background:

  • Genetic association studies often use single quantitative trait measures.
  • Measurement error in quantitative traits can impact statistical power and precision.
  • The benefits of multiple trait measures in genetic studies with measurement error models are underexplored.

Purpose of the Study:

  • To investigate the impact of measurement error models on the precision of genetic association studies using multiple quantitative trait measures.
  • To evaluate the effect of correlated systematic and random errors on parameter estimates.
  • To compare the performance of single, three, and six measure models in genome-wide association studies (GWAS) of kidney function.

Main Methods:

  • Developed measurement error models for a quantitative trait (eGFR) with systematic and random error components.
  • Simulated the effects of varying error correlations and contributions on parameter estimate precision.
  • Conducted three empirical GWAS of kidney function in European Americans using single, three, and six measures of kidney function.

Main Results:

  • Simulations indicated that measures with less correlated systematic errors yield greater precision gains for a given total error.
  • Empirical GWAS revealed that both three- and six-measure models identified more eGFR-associated genomic loci with stronger associations than the single-measure model.
  • Despite some heterogeneity among measures, multiple measures enhanced statistical power.

Conclusions:

  • Employing multiple measures of a quantitative trait can significantly increase statistical power in genetic association studies without recruiting more participants.
  • Careful attention to the correlation of systematic errors and potential inconsistencies is crucial when using diverse biomarkers or measurement methods.
  • This approach offers a viable strategy to improve the precision and power of genetic association studies for quantitative traits.