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Evaluating NAT2PRED for inferring the individual acetylation status from unphased genotype data.

Sabbagh A, Darlu P, Vidaud M - BMC Med. Genet. (2009)

Bottom Line: The ability of NAT2PRED to classify individuals according to their acetylation status (slow, intermediate and rapid acetylators) was evaluated in a worldwide dataset composed of 56 population samples (8,489 individuals) from four continental regions.NAT2PRED correctly identified slow acetylators with a sensitivity above 99% for all populations outside sub-Saharan Africa.Nevertheless, NAT2PRED showed a poor ability to distinguish between intermediate and rapid acetylators, with a classification error rate reaching up to 10% in the non-African samples.

View Article: PubMed Central - HTML - PubMed

Affiliation: INSERM UMR745, Faculty of Pharmacy, University of Paris Descartes, Paris, France. audrey.sabbagh@parisdescartes.fr

ABSTRACT

Background: Genetically determined differences in N-acetylation capacity have proved to be important determinants of both the effectiveness of therapeutic response and the development of adverse drug reactions and toxicity during drug treatment. NAT2PRED is a web-server that allows a fast determination of NAT2 acetylation phenotype from genotype data without taking the extra step of reconstructing haplotypes for each individual (publicly available at http://nat2pred.rit.albany.edu). However, the classification accuracy of NAT2PRED needs to be assessed before its application can be advocated at a large scale.

Methods: The ability of NAT2PRED to classify individuals according to their acetylation status (slow, intermediate and rapid acetylators) was evaluated in a worldwide dataset composed of 56 population samples (8,489 individuals) from four continental regions.

Results: NAT2PRED correctly identified slow acetylators with a sensitivity above 99% for all populations outside sub-Saharan Africa. Nevertheless, NAT2PRED showed a poor ability to distinguish between intermediate and rapid acetylators, with a classification error rate reaching up to 10% in the non-African samples.

Conclusion: NAT2PRED is an excellent tool to infer the individual acetylation status from NAT2 genotype data when the main interest is to distinguish slow acetylators from the others. This should facilitate the determination of the individual acetylation status in routine clinical practice and lead to better monitoring of risks associated with cancer and adverse drug reactions.

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Classification error rates of NAT2PRED in the 56 worldwide samples. The classification accuracy of NAT2PRED was evaluated using either three phenotypic classes (slow, intermediate and rapid acetylators; hatched area) or two phenotypic classes (slow and other acetylators; black area) for the acetylation status. Single populations are reported on the left side of the plot, with sample sizes (number of individuals) in brackets. Geographic areas are indicated on the right side, as follows: SSAFRICA, sub-Saharan Africa; EUROPE/NORTH AFRICA, Europe and North Africa; CSASIA, Central and South Asia; EAST ASIA, East Asia; AME, America. The assignment of populations to one of the five world regions was based on the origin of the population, in effect ignoring the past 1,000 years of known human migration (e.g., people of European descent in the United States were assigned to Europe).
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Figure 1: Classification error rates of NAT2PRED in the 56 worldwide samples. The classification accuracy of NAT2PRED was evaluated using either three phenotypic classes (slow, intermediate and rapid acetylators; hatched area) or two phenotypic classes (slow and other acetylators; black area) for the acetylation status. Single populations are reported on the left side of the plot, with sample sizes (number of individuals) in brackets. Geographic areas are indicated on the right side, as follows: SSAFRICA, sub-Saharan Africa; EUROPE/NORTH AFRICA, Europe and North Africa; CSASIA, Central and South Asia; EAST ASIA, East Asia; AME, America. The assignment of populations to one of the five world regions was based on the origin of the population, in effect ignoring the past 1,000 years of known human migration (e.g., people of European descent in the United States were assigned to Europe).

Mentions: The classification error rates of NAT2PRED in each sample for both classification issues (two or three acetylation phenotypes) are shown in Figure 1 (see Additional File 1 for the exact numbers). The performance of this tool in each of the five world regions investigated is summarized in Table 1. NAT2PRED performed poorly in almost all sub-Saharan African samples investigated, except in the two Ethiopian samples where it correctly classified 100% of subjects into rapid, intermediate and slow acetylators. Such a poor performance is not surprising in view of the omission by the supervised learning classifier implemented in NAT2PRED of the functional SNP 191G>A which, although monomorphic in most worldwide populations, occurs at an appreciable frequency in many sub-Saharan African populations (up to 23%) and accounts for a sizeable portion of the slow acetylators encountered in these populations [11,12]. By contrast, NAT2PRED achieved a high classification accuracy in all the other world regions. In particular, individuals with a slow acetylation phenotype were correctly identified as slow acetylators with a sensitivity above 99% for all populations outside sub-Saharan Africa. Conversely, NAT2PRED showed a poor ability to distinguish between intermediate and rapid acetylators, with a classification error rate reaching up to 10% in the non-African samples.


Evaluating NAT2PRED for inferring the individual acetylation status from unphased genotype data.

Sabbagh A, Darlu P, Vidaud M - BMC Med. Genet. (2009)

Classification error rates of NAT2PRED in the 56 worldwide samples. The classification accuracy of NAT2PRED was evaluated using either three phenotypic classes (slow, intermediate and rapid acetylators; hatched area) or two phenotypic classes (slow and other acetylators; black area) for the acetylation status. Single populations are reported on the left side of the plot, with sample sizes (number of individuals) in brackets. Geographic areas are indicated on the right side, as follows: SSAFRICA, sub-Saharan Africa; EUROPE/NORTH AFRICA, Europe and North Africa; CSASIA, Central and South Asia; EAST ASIA, East Asia; AME, America. The assignment of populations to one of the five world regions was based on the origin of the population, in effect ignoring the past 1,000 years of known human migration (e.g., people of European descent in the United States were assigned to Europe).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2806877&req=5

Figure 1: Classification error rates of NAT2PRED in the 56 worldwide samples. The classification accuracy of NAT2PRED was evaluated using either three phenotypic classes (slow, intermediate and rapid acetylators; hatched area) or two phenotypic classes (slow and other acetylators; black area) for the acetylation status. Single populations are reported on the left side of the plot, with sample sizes (number of individuals) in brackets. Geographic areas are indicated on the right side, as follows: SSAFRICA, sub-Saharan Africa; EUROPE/NORTH AFRICA, Europe and North Africa; CSASIA, Central and South Asia; EAST ASIA, East Asia; AME, America. The assignment of populations to one of the five world regions was based on the origin of the population, in effect ignoring the past 1,000 years of known human migration (e.g., people of European descent in the United States were assigned to Europe).
Mentions: The classification error rates of NAT2PRED in each sample for both classification issues (two or three acetylation phenotypes) are shown in Figure 1 (see Additional File 1 for the exact numbers). The performance of this tool in each of the five world regions investigated is summarized in Table 1. NAT2PRED performed poorly in almost all sub-Saharan African samples investigated, except in the two Ethiopian samples where it correctly classified 100% of subjects into rapid, intermediate and slow acetylators. Such a poor performance is not surprising in view of the omission by the supervised learning classifier implemented in NAT2PRED of the functional SNP 191G>A which, although monomorphic in most worldwide populations, occurs at an appreciable frequency in many sub-Saharan African populations (up to 23%) and accounts for a sizeable portion of the slow acetylators encountered in these populations [11,12]. By contrast, NAT2PRED achieved a high classification accuracy in all the other world regions. In particular, individuals with a slow acetylation phenotype were correctly identified as slow acetylators with a sensitivity above 99% for all populations outside sub-Saharan Africa. Conversely, NAT2PRED showed a poor ability to distinguish between intermediate and rapid acetylators, with a classification error rate reaching up to 10% in the non-African samples.

Bottom Line: The ability of NAT2PRED to classify individuals according to their acetylation status (slow, intermediate and rapid acetylators) was evaluated in a worldwide dataset composed of 56 population samples (8,489 individuals) from four continental regions.NAT2PRED correctly identified slow acetylators with a sensitivity above 99% for all populations outside sub-Saharan Africa.Nevertheless, NAT2PRED showed a poor ability to distinguish between intermediate and rapid acetylators, with a classification error rate reaching up to 10% in the non-African samples.

View Article: PubMed Central - HTML - PubMed

Affiliation: INSERM UMR745, Faculty of Pharmacy, University of Paris Descartes, Paris, France. audrey.sabbagh@parisdescartes.fr

ABSTRACT

Background: Genetically determined differences in N-acetylation capacity have proved to be important determinants of both the effectiveness of therapeutic response and the development of adverse drug reactions and toxicity during drug treatment. NAT2PRED is a web-server that allows a fast determination of NAT2 acetylation phenotype from genotype data without taking the extra step of reconstructing haplotypes for each individual (publicly available at http://nat2pred.rit.albany.edu). However, the classification accuracy of NAT2PRED needs to be assessed before its application can be advocated at a large scale.

Methods: The ability of NAT2PRED to classify individuals according to their acetylation status (slow, intermediate and rapid acetylators) was evaluated in a worldwide dataset composed of 56 population samples (8,489 individuals) from four continental regions.

Results: NAT2PRED correctly identified slow acetylators with a sensitivity above 99% for all populations outside sub-Saharan Africa. Nevertheless, NAT2PRED showed a poor ability to distinguish between intermediate and rapid acetylators, with a classification error rate reaching up to 10% in the non-African samples.

Conclusion: NAT2PRED is an excellent tool to infer the individual acetylation status from NAT2 genotype data when the main interest is to distinguish slow acetylators from the others. This should facilitate the determination of the individual acetylation status in routine clinical practice and lead to better monitoring of risks associated with cancer and adverse drug reactions.

Show MeSH
Related in: MedlinePlus