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Related Concept Videos

Factors Affecting Renal Clearance: Renal Impairment01:17

Factors Affecting Renal Clearance: Renal Impairment

69
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...
69

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A methylation risk score for chronic kidney disease: a HyperGEN study.

Alana C Jones1,2, Amit Patki3, Vinodh Srinivasasainagendra3

  • 1Medical Scientist Training Program, University of Alabama at Birmingham, 912 18th St S, Birmingham, AL, 35233, USA. acjones@uab.edu.

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|July 31, 2024
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Summary

African Americans face a higher burden of chronic kidney disease (CKD). A new methylation risk score (MRS) using DNA methylation at CpG sites shows promise for predicting CKD risk in this population.

Keywords:
Chronic kidney diseaseEpigeneticsMethylation risk scoreeGFR

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Area of Science:

  • Nephrology
  • Epigenetics
  • Genomics

Background:

  • Chronic kidney disease (CKD) disproportionately affects African Americans (AAs).
  • Epigenetic modifications, specifically DNA methylation at cytosine-phosphate-guanine (CpG) sites, are linked to kidney function.
  • AAs may exhibit heightened sensitivity to environmental factors influencing methylation patterns relevant to CKD.

Purpose of the Study:

  • To develop and validate a methylation risk score (MRS) for predicting prevalent CKD in African American cohorts.
  • To assess the clinical utility of an MRS based on CpG methylation sites associated with estimated glomerular filtration rate (eGFR).

Main Methods:

  • Selected nine CpG sites previously associated with eGFR from epigenome-wide association studies.
  • Constructed a MRS using these CpG sites within the Hypertension Genetic Epidemiology Network (HyperGEN) cohort.
  • Validated the MRS in independent cohorts using logistic mixed models and sensitivity analyses.

Main Results:

  • The developed MRS was significantly associated with prevalent CKD in logistic mixed models.
  • The association remained robust across multiple sensitivity analyses, accounting for known CKD risk factors.
  • Modest replication of the MRS predictive capability was observed in validation cohorts.

Conclusions:

  • An eGFR-based CpG methylation risk score (MRS) independently predicts prevalent CKD.
  • The MRS demonstrates potential for clinical utility in assessing CKD risk and progression.
  • Further investigation is warranted to explore the clinical application of this epigenetic biomarker in diverse populations.