BACKGROUND: For genetic polymorphisms known to alter drug effect or safety, regulatory authorities can tap into population genomic databases and other sources of allele and genotype distribution data to make a more informed decision about the anticipated impact of such variants on the main ethnic groups in a country's population. OBJECTIVE: The aim of this short communication is to describe how the Singapore Health Sciences Authority (HSA) made use of allele and genotype distributions in the main ethnic groups in Singapore (Chinese, Malay, Indian) and population genetic tools to compare with North American Caucasians and Japanese. METHODS: Published papers and publicly accessible genomic databases were searched up to August 2009 to obtain allele and genotype frequencies for UGT1A1*6 and *28, two common variants of UGT1A1, a gene that encodes for a key enzyme in the pathway of irinotecan metabolism. These variants are associated with greater risk of serious toxicity. RESULTS: In Singapore, the combined prevalence of three high-risk genotypes, UGT1A1*6/*6, *6/*28 and *28/*28, is 9.7% in Chinese, 5.0% in Malays and 18.7% in Indians, compared with 11.5% in North American Caucasians and 8.1% in Japanese. Indians are at an elevated risk of irinotecan-induced neutropenia associated with UGT1A1*28 compared with Chinese and Japanese, and at an even higher risk compared with North American Caucasians. On the other hand, Chinese and Japanese are at an elevated risk of irinotecan-induced neutropenia associated with UGT1A1*6 relative to Indians in Singapore or North American Caucasians. Population genotype data were the basis for the HSA to request revision of the package insert from manufacturers of irinotecan products. Moreover, the data provided the impetus for the HSA to publicize the availability of UGT1A1 genetic testing at the National Cancer Centre. CONCLUSION: With the growing volume of genomic data and pharmacogenomic associations, a regulatory authority is now able to more readily utilize population genetic information and tools to supplement evaluations of drug products pertinent to the country's ethnic demography.
BACKGROUND: For genetic polymorphisms known to alter drug effect or safety, regulatory authorities can tap into population genomic databases and other sources of allele and genotype distribution data to make a more informed decision about the anticipated impact of such variants on the main ethnic groups in a country's population. OBJECTIVE: The aim of this short communication is to describe how the Singapore Health Sciences Authority (HSA) made use of allele and genotype distributions in the main ethnic groups in Singapore (Chinese, Malay, Indian) and population genetic tools to compare with North American Caucasians and Japanese. METHODS: Published papers and publicly accessible genomic databases were searched up to August 2009 to obtain allele and genotype frequencies for UGT1A1*6 and *28, two common variants of UGT1A1, a gene that encodes for a key enzyme in the pathway of irinotecan metabolism. These variants are associated with greater risk of serious toxicity. RESULTS: In Singapore, the combined prevalence of three high-risk genotypes, UGT1A1*6/*6, *6/*28 and *28/*28, is 9.7% in Chinese, 5.0% in Malays and 18.7% in Indians, compared with 11.5% in North American Caucasians and 8.1% in Japanese. Indians are at an elevated risk of irinotecan-induced neutropenia associated with UGT1A1*28 compared with Chinese and Japanese, and at an even higher risk compared with North American Caucasians. On the other hand, Chinese and Japanese are at an elevated risk of irinotecan-induced neutropenia associated with UGT1A1*6 relative to Indians in Singapore or North American Caucasians. Population genotype data were the basis for the HSA to request revision of the package insert from manufacturers of irinotecan products. Moreover, the data provided the impetus for the HSA to publicize the availability of UGT1A1 genetic testing at the National Cancer Centre. CONCLUSION: With the growing volume of genomic data and pharmacogenomic associations, a regulatory authority is now able to more readily utilize population genetic information and tools to supplement evaluations of drug products pertinent to the country's ethnic demography.
Authors: Roshni P Ramchandani; Yaning Wang; Brian P Booth; Amna Ibrahim; John R Johnson; Atiqur Rahman; Mehul Mehta; Federico Innocenti; Mark J Ratain; Jogarao V S Gobburu Journal: J Clin Pharmacol Date: 2007-01 Impact factor: 3.126
Authors: Yik-Ying Teo; Xueling Sim; Rick T H Ong; Adrian K S Tan; Jieming Chen; Erwin Tantoso; Kerrin S Small; Chee-Seng Ku; Edmund J D Lee; Mark Seielstad; Kee-Seng Chia Journal: Genome Res Date: 2009-08-21 Impact factor: 9.043
Authors: Jessica M van der Bol; Ron H J Mathijssen; Geert-Jan M Creemers; André S Th Planting; Walter J Loos; Erik A C Wiemer; Lena E Friberg; Jaap Verweij; Alex Sparreboom; Floris A de Jong Journal: Clin Cancer Res Date: 2010-01-12 Impact factor: 12.531
Authors: A Ruzzo; F Graziano; F Loupakis; D Santini; V Catalano; R Bisonni; R Ficarelli; A Fontana; F Andreoni; A Falcone; E Canestrari; G Tonini; D Mari; P Lippe; F Pizzagalli; G Schiavon; P Alessandroni; L Giustini; P Maltese; E Testa; E T Menichetti; M Magnani Journal: Pharmacogenomics J Date: 2007-06-05 Impact factor: 3.550