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Related Concept Videos

DNA Microarrays02:34

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Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
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Genetic polymorphisms in drug targets have emerged as critical determinants of interindividual variability in drug response and toxicity. Pharmacogenomic investigations increasingly focus on identifying these variations to personalize and optimize therapeutic interventions. A drug target may be a receptor, enzyme, or signaling protein involved in pharmacologic responses or disease-related pathways. While early pharmacogenetic studies focused primarily on drug metabolism, current research...
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Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
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Therapeutic Drug Monitoring (TDM) is the clinical practice of measuring specific drug levels in a patient's blood or body tissues to manage and optimize therapy. TDM is crucial for drugs with narrow therapeutic windows, like warfarin and phenytoin, where incorrect doses can lead to treatment failure or severe side effects. This monitoring ensures the dosage administered is within a safe and effective range. The factors affecting therapeutic drug monitoring include:Patient-Specific Factors:a.

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Array Comparative Genomic Hybridization (Array CGH) for Detection of Genomic Copy Number Variants
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Published on: February 21, 2015

Chromosomal microarray impacts clinical management.

E R Riggs1, K E Wain, D Riethmaier

  • 1Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA.

Clinical Genetics
|January 26, 2013
PubMed
Summary
This summary is machine-generated.

Chromosomal microarray analysis (CMA) is a key genetic test for developmental disabilities. Despite its utility, insurance coverage is limited due to perceived lack of clinical management impact, hindering patient access.

Keywords:
array comparative genomic hybridizationchromosomal microarray analysisgenetic testingpatient care management

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Published on: January 28, 2014

Area of Science:

  • Genetics
  • Clinical Diagnostics
  • Genomic Medicine

Background:

  • Chromosomal microarray analysis (CMA) is the standard first-tier test for detecting copy number variations in patients with developmental disabilities.
  • While CMA offers higher diagnostic yield than traditional cytogenetic methods, its impact on clinical management remains understudied.
  • Barriers to CMA utilization, including insurance coverage issues linked to perceived clinical utility, affect patient care.

Purpose of the Study:

  • To assess the clinical management impact of CMA findings in patients with developmental disabilities.
  • To identify genomic regions associated with conditions having documented management recommendations.
  • To evaluate the frequency of CMA-diagnosed conditions with management implications in a large patient cohort.

Main Methods:

  • Surveyed genetic service providers on CMA ordering practices and reimbursement perceptions.
  • Compiled a list of genomic regions with documented management implications for haploinsufficiency/triplosensitivity conditions.
  • Compared this list against a clinical CMA database (n=28,526) to determine the proportion of cases with actionable diagnoses.

Main Results:

  • At least 146 genetic conditions diagnosable by CMA have published management recommendations.
  • Approximately 7% of all analyzed CMA cases involved genomic regions with documented management implications.
  • Lack of insurance coverage due to perceived lack of clinical utility was a frequently cited reason for not ordering CMA.

Conclusions:

  • CMA diagnoses have a significant impact on clinical management, comparable to other approved genetic tests.
  • The study provides evidence to address insurance barriers and improve patient access to CMA testing.
  • Addressing these barriers is crucial for reducing inequities in genetic testing and patient care.