Systematic Pharmacogenomics Analysis of a Malay Whole Genome: Proof of Concept for Personalized Medicine
Background:With a higher throughput and lower cost in sequencing, second generation sequencing technology has immense potential for translation into clinical practice and in the realization of pharmacogenomics based patient care. The systematic analysis of whole genome sequences to assess patient to...
Main Authors: | , , , , , , , , , , , , , , , , |
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Format: | Article |
Language: | English |
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Online Access: | View Fulltext in Publisher View in Scopus |
LEADER | 04712nam a2200877Ia 4500 | ||
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001 | 10.1371-journal.pone.0071554 | ||
008 | 220112s2013 CNT 000 0 und d | ||
020 | |a 19326203 (ISSN) | ||
245 | 1 | 0 | |a Systematic Pharmacogenomics Analysis of a Malay Whole Genome: Proof of Concept for Personalized Medicine |
856 | |z View Fulltext in Publisher |u https://doi.org/10.1371/journal.pone.0071554 | ||
856 | |z View in Scopus |u https://www.scopus.com/inward/record.uri?eid=2-s2.0-84882970247&doi=10.1371%2fjournal.pone.0071554&partnerID=40&md5=4d8919f0ff3d059a571a19587cee73b7 | ||
520 | 3 | |a Background:With a higher throughput and lower cost in sequencing, second generation sequencing technology has immense potential for translation into clinical practice and in the realization of pharmacogenomics based patient care. The systematic analysis of whole genome sequences to assess patient to patient variability in pharmacokinetics and pharmacodynamics responses towards drugs would be the next step in future medicine in line with the vision of personalizing medicine.Methods:Genomic DNA obtained from a 55 years old, self-declared healthy, anonymous male of Malay descent was sequenced. The subject's mother died of lung cancer and the father had a history of schizophrenia and deceased at the age of 65 years old. A systematic, intuitive computational workflow/pipeline integrating custom algorithm in tandem with large datasets of variant annotations and gene functions for genetic variations with pharmacogenomics impact was developed. A comprehensive pathway map of drug transport, metabolism and action was used as a template to map non-synonymous variations with potential functional consequences.Principal Findings:Over 3 million known variations and 100,898 novel variations in the Malay genome were identified. Further in-depth pharmacogenetics analysis revealed a total of 607 unique variants in 563 proteins, with the eventual identification of 4 drug transport genes, 2 drug metabolizing enzyme genes and 33 target genes harboring deleterious SNVs involved in pharmacological pathways, which could have a potential role in clinical settings.Conclusions:The current study successfully unravels the potential of personal genome sequencing in understanding the functionally relevant variations with potential influence on drug transport, metabolism and differential therapeutic outcomes. These will be essential for realizing personalized medicine through the use of comprehensive computational pipeline for systematic data mining and analysis. © 2013 Salleh et al. | |
650 | 0 | 4 | |a adult |
650 | 0 | 4 | |a article |
650 | 0 | 4 | |a Asian Continental Ancestry Group |
650 | 0 | 4 | |a Biological Markers |
650 | 0 | 4 | |a Chromosome Mapping |
650 | 0 | 4 | |a Computational Biology |
650 | 0 | 4 | |a controlled study |
650 | 0 | 4 | |a disease marker |
650 | 0 | 4 | |a drug response |
650 | 0 | 4 | |a ethnic group |
650 | 0 | 4 | |a family history |
650 | 0 | 4 | |a Female |
650 | 0 | 4 | |a gene frequency |
650 | 0 | 4 | |a gene function |
650 | 0 | 4 | |a gene identification |
650 | 0 | 4 | |a gene mapping |
650 | 0 | 4 | |a genetic association |
650 | 0 | 4 | |a genetic marker |
650 | 0 | 4 | |a Genetic Predisposition to Disease |
650 | 0 | 4 | |a genetic variability |
650 | 0 | 4 | |a genome analysis |
650 | 0 | 4 | |a Genome, Human |
650 | 0 | 4 | |a Genome-Wide Association Study |
650 | 0 | 4 | |a genomic DNA |
650 | 0 | 4 | |a Genomics |
650 | 0 | 4 | |a High-Throughput Nucleotide Sequencing |
650 | 0 | 4 | |a human |
650 | 0 | 4 | |a Humans |
650 | 0 | 4 | |a Individualized Medicine |
650 | 0 | 4 | |a Malay |
650 | 0 | 4 | |a Malaysia |
650 | 0 | 4 | |a male |
650 | 0 | 4 | |a Male |
650 | 0 | 4 | |a Middle Aged |
650 | 0 | 4 | |a outcome assessment |
650 | 0 | 4 | |a patient assessment |
650 | 0 | 4 | |a personalized medicine |
650 | 0 | 4 | |a Pharmacogenetics |
650 | 0 | 4 | |a pharmacogenomics |
650 | 0 | 4 | |a Polymorphism, Single Nucleotide |
650 | 0 | 4 | |a Quantitative Trait Loci |
650 | 0 | 4 | |a Quantitative Trait, Heritable |
650 | 0 | 4 | |a sequence alignment |
650 | 0 | 4 | |a sequence analysis |
650 | 0 | 4 | |a signal transduction |
650 | 0 | 4 | |a single nucleotide polymorphism |
700 | 1 | 0 | |a Adam, A. |e author |
700 | 1 | 0 | |a Ahmed, A.Z. |e author |
700 | 1 | 0 | |a Hamzah, A.S. |e author |
700 | 1 | 0 | |a Hatta, F.H.M. |e author |
700 | 1 | 0 | |a Hoh, B.P. |e author |
700 | 1 | 0 | |a Ismail, M.I. |e author |
700 | 1 | 0 | |a Ismet, R.I. |e author |
700 | 1 | 0 | |a Janor, R.M. |e author |
700 | 1 | 0 | |a Joshi, K. |e author |
700 | 1 | 0 | |a Lee, L.S. |e author |
700 | 1 | 0 | |a Pasha, A. |e author |
700 | 1 | 0 | |a Patowary, A. |e author |
700 | 1 | 0 | |a Salleh, M.Z. |e author |
700 | 1 | 0 | |a Scaria, V. |e author |
700 | 1 | 0 | |a Sivasubbu, S. |e author |
700 | 1 | 0 | |a Teh, L.K. |e author |
700 | 1 | 0 | |a Yusoff, K. |e author |
773 | |t PLoS ONE |