AIMS: Admixture in the population of the island of Puerto Rico is of general interest with regards to pharmacogenetics to develop comprehensive strategies for personalized healthcare in Latin Americans. This research was aimed at determining the frequencies of SNPs in key physiological, pharmacological and biochemical genes to infer population structure and ancestry in the Puerto Rican population. MATERIALS & METHODS: A noninterventional, cross-sectional, retrospective study design was implemented following a controlled, stratified-by-region, random sampling protocol. The sample was based on birthrates in each region of the island of Puerto Rico, according to the 2004 National Birth Registry. Genomic DNA samples from 100 newborns were obtained from the Puerto Rico Newborn Screening Program in dried-blood spot cards. Genotyping using a physiogenomic array was performed for 332 SNPs from 196 cardiometabolic and neuroendocrine genes. Population structure was examined using a Bayesian clustering approach as well as by allelic dissimilarity as a measure of allele sharing. RESULTS: The Puerto Rican sample was found to be broadly heterogeneous. We observed three main clusters in the population, which we hypothesize to reflect the historical admixture in the Puerto Rican population from Amerindian, African and European ancestors. We present evidence for this interpretation by comparing allele frequencies for the three clusters with those for the same SNPs available from the International HapMap project for Asian, African and European populations. CONCLUSION: Our results demonstrate that population analysis can be performed with a physiogenomic array of cardiometabolic and neuroendocrine genes to facilitate the translation of genome diversity into personalized medicine.
AIMS: Admixture in the population of the island of Puerto Rico is of general interest with regards to pharmacogenetics to develop comprehensive strategies for personalized healthcare in Latin Americans. This research was aimed at determining the frequencies of SNPs in key physiological, pharmacological and biochemical genes to infer population structure and ancestry in the Puerto Rican population. MATERIALS & METHODS: A noninterventional, cross-sectional, retrospective study design was implemented following a controlled, stratified-by-region, random sampling protocol. The sample was based on birthrates in each region of the island of Puerto Rico, according to the 2004 National Birth Registry. Genomic DNA samples from 100 newborns were obtained from the Puerto Rico Newborn Screening Program in dried-blood spot cards. Genotyping using a physiogenomic array was performed for 332 SNPs from 196 cardiometabolic and neuroendocrine genes. Population structure was examined using a Bayesian clustering approach as well as by allelic dissimilarity as a measure of allele sharing. RESULTS: The Puerto Rican sample was found to be broadly heterogeneous. We observed three main clusters in the population, which we hypothesize to reflect the historical admixture in the Puerto Rican population from Amerindian, African and European ancestors. We present evidence for this interpretation by comparing allele frequencies for the three clusters with those for the same SNPs available from the International HapMap project for Asian, African and European populations. CONCLUSION: Our results demonstrate that population analysis can be performed with a physiogenomic array of cardiometabolic and neuroendocrine genes to facilitate the translation of genome diversity into personalized medicine.
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