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Is High Resolution Melting Analysis (HRMA) Accurate for Detection of Human Disease-Associated Mutations? A Meta Analysis

BACKGROUND: High Resolution Melting Analysis (HRMA) is becoming the preferred method for mutation detection. However, its accuracy in the individual clinical diagnostic setting is variable. To assess the diagnostic accuracy of HRMA for human mutations in comparison to DNA sequencing in different rou...

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Autores principales: Li, Bing-Sheng, Wang, Xin-Ying, Ma, Feng-Li, Jiang, Bo, Song, Xiao-Xiao, Xu, An-Gao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3237421/
https://www.ncbi.nlm.nih.gov/pubmed/22194806
http://dx.doi.org/10.1371/journal.pone.0028078
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author Li, Bing-Sheng
Wang, Xin-Ying
Ma, Feng-Li
Jiang, Bo
Song, Xiao-Xiao
Xu, An-Gao
author_facet Li, Bing-Sheng
Wang, Xin-Ying
Ma, Feng-Li
Jiang, Bo
Song, Xiao-Xiao
Xu, An-Gao
author_sort Li, Bing-Sheng
collection PubMed
description BACKGROUND: High Resolution Melting Analysis (HRMA) is becoming the preferred method for mutation detection. However, its accuracy in the individual clinical diagnostic setting is variable. To assess the diagnostic accuracy of HRMA for human mutations in comparison to DNA sequencing in different routine clinical settings, we have conducted a meta-analysis of published reports. METHODOLOGY/PRINCIPAL FINDINGS: Out of 195 publications obtained from the initial search criteria, thirty-four studies assessing the accuracy of HRMA were included in the meta-analysis. We found that HRMA was a highly sensitive test for detecting disease-associated mutations in humans. Overall, the summary sensitivity was 97.5% (95% confidence interval (CI): 96.8–98.5; I(2) = 27.0%). Subgroup analysis showed even higher sensitivity for non-HR-1 instruments (sensitivity 98.7% (95%CI: 97.7–99.3; I(2) = 0.0%)) and an eligible sample size subgroup (sensitivity 99.3% (95%CI: 98.1–99.8; I(2) = 0.0%)). HRMA specificity showed considerable heterogeneity between studies. Sensitivity of the techniques was influenced by sample size and instrument type but by not sample source or dye type. CONCLUSIONS/SIGNIFICANCE: These findings show that HRMA is a highly sensitive, simple and low-cost test to detect human disease-associated mutations, especially for samples with mutations of low incidence. The burden on DNA sequencing could be significantly reduced by the implementation of HRMA, but it should be recognized that its sensitivity varies according to the number of samples with/without mutations, and positive results require DNA sequencing for confirmation.
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spelling pubmed-32374212011-12-22 Is High Resolution Melting Analysis (HRMA) Accurate for Detection of Human Disease-Associated Mutations? A Meta Analysis Li, Bing-Sheng Wang, Xin-Ying Ma, Feng-Li Jiang, Bo Song, Xiao-Xiao Xu, An-Gao PLoS One Research Article BACKGROUND: High Resolution Melting Analysis (HRMA) is becoming the preferred method for mutation detection. However, its accuracy in the individual clinical diagnostic setting is variable. To assess the diagnostic accuracy of HRMA for human mutations in comparison to DNA sequencing in different routine clinical settings, we have conducted a meta-analysis of published reports. METHODOLOGY/PRINCIPAL FINDINGS: Out of 195 publications obtained from the initial search criteria, thirty-four studies assessing the accuracy of HRMA were included in the meta-analysis. We found that HRMA was a highly sensitive test for detecting disease-associated mutations in humans. Overall, the summary sensitivity was 97.5% (95% confidence interval (CI): 96.8–98.5; I(2) = 27.0%). Subgroup analysis showed even higher sensitivity for non-HR-1 instruments (sensitivity 98.7% (95%CI: 97.7–99.3; I(2) = 0.0%)) and an eligible sample size subgroup (sensitivity 99.3% (95%CI: 98.1–99.8; I(2) = 0.0%)). HRMA specificity showed considerable heterogeneity between studies. Sensitivity of the techniques was influenced by sample size and instrument type but by not sample source or dye type. CONCLUSIONS/SIGNIFICANCE: These findings show that HRMA is a highly sensitive, simple and low-cost test to detect human disease-associated mutations, especially for samples with mutations of low incidence. The burden on DNA sequencing could be significantly reduced by the implementation of HRMA, but it should be recognized that its sensitivity varies according to the number of samples with/without mutations, and positive results require DNA sequencing for confirmation. Public Library of Science 2011-12-14 /pmc/articles/PMC3237421/ /pubmed/22194806 http://dx.doi.org/10.1371/journal.pone.0028078 Text en Li et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Li, Bing-Sheng
Wang, Xin-Ying
Ma, Feng-Li
Jiang, Bo
Song, Xiao-Xiao
Xu, An-Gao
Is High Resolution Melting Analysis (HRMA) Accurate for Detection of Human Disease-Associated Mutations? A Meta Analysis
title Is High Resolution Melting Analysis (HRMA) Accurate for Detection of Human Disease-Associated Mutations? A Meta Analysis
title_full Is High Resolution Melting Analysis (HRMA) Accurate for Detection of Human Disease-Associated Mutations? A Meta Analysis
title_fullStr Is High Resolution Melting Analysis (HRMA) Accurate for Detection of Human Disease-Associated Mutations? A Meta Analysis
title_full_unstemmed Is High Resolution Melting Analysis (HRMA) Accurate for Detection of Human Disease-Associated Mutations? A Meta Analysis
title_short Is High Resolution Melting Analysis (HRMA) Accurate for Detection of Human Disease-Associated Mutations? A Meta Analysis
title_sort is high resolution melting analysis (hrma) accurate for detection of human disease-associated mutations? a meta analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3237421/
https://www.ncbi.nlm.nih.gov/pubmed/22194806
http://dx.doi.org/10.1371/journal.pone.0028078
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