The Pharmacogenomics Journal Impact Factor & Information

Publisher: Nature Publishing Group

Journal description

The Pharmacogenomics Journal is dedicated to the publication of original research and reviews on pharmacogenomics and its clinical applications. Topics covered include: identification of novel genomic targets for drug development, clinical applications of genomic science, potential benefits of pharmacogenomics, effects of genetic variability on drug toxicity and efficacy, pharmacokinetic variation and drug toxicity, pharmacodynamic variation and drug efficacy plus, the integration of new developments in the genome project and proteomics into clinical medicine, pharmacology, and therapeutics.

Current impact factor: 4.23

Impact Factor Rankings

2015 Impact Factor Available summer 2016
2014 Impact Factor 4.229
2013 Impact Factor 5.513
2012 Impact Factor 5.134
2011 Impact Factor 4.536
2010 Impact Factor 4.306
2009 Impact Factor 4.398
2008 Impact Factor 5.435
2007 Impact Factor 4.968
2006 Impact Factor 3.957
2005 Impact Factor 3.989

Impact factor over time

Impact factor

Additional details

5-year impact 4.11
Cited half-life 5.30
Immediacy index 1.06
Eigenfactor 0.01
Article influence 1.21
Website Pharmacogenomics Journal, The website
Other titles Pharmacogenomics journal (Online)
ISSN 1470-269X
OCLC 49965587
Material type Document, Periodical, Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

Nature Publishing Group

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author cannot archive a post-print version
  • Restrictions
    • 6 months embargo
  • Conditions
    • Authors retain copyright
    • Published source must be acknowledged and DOI cited
    • Must link to publisher version
    • Publisher's version/PDF cannot be used
    • On author's personal website and institutional repository
    • If funding agency rules apply, authors may post authors version to their relevant funding body's archive, 6 months after publication
    • This policy is an exception to the default policies of 'Nature Publishing Group'
  • Classification

Publications in this journal

  • The Pharmacogenomics Journal 11/2015;
  • [Show abstract] [Hide abstract]
    ABSTRACT: Lipid-lowering therapy has shown a high degree of variability in clinical response and there is evidence that the variability in drug response between individuals is due to genetic factors. Thirteen single nucleotide polymorphisms (SNPs) within the ESR1 gene were evaluated with basal lipid and lipoprotein levels, as well as response to lipid-lowering therapy, in 495 hypercholesterolemic individuals of European descent receiving simvastatin or atorvastatin. Significant associations were detected between rs4870061 (P=0.040, corrected P-value (PC)=0.440), rs1801132 (P=0.002, PC=0.022) and the SNP rs3020314 (P=0.013, PC=0.143) with triglyceride (TG) baseline levels. The rs4870061 was also associated with high-density lipoprotein cholesterol (HDL-C) baseline levels (P=0.045, PC=0.495). Regarding statin efficacy, rs2234693 C/C was associated with greater HDL-C increase (P=0.037; PC=0.407) and rs3798577 T allele was associated with greater total cholesterol (TC) reduction (P=0.019; PC=0.209) and greater TG reduction (P=0.026; PC=0.286). These associations suggest that ESR1 polymorphisms are in part responsible for the TC, HDL-C and TG variation levels and this effect may be sex-specific.The Pharmacogenomics Journal advance online publication, 25 August 2015; doi:10.1038/tpj.2015.60.
    The Pharmacogenomics Journal 08/2015; DOI:10.1038/tpj.2015.60
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    ABSTRACT: Osteosarcoma patients are commonly treated with high doses of methotrexate (MTX). MTX is an analog of folate, which is essential for DNA synthesis. Genetic polymorphism at single nucleotide can be indicative to the prognostic outcome in patients. Germ-line variants in candidate genes, coding for enzymes active in the metabolism of MTX, were studied in 62 osteosarcoma patients. Patients harboring the GG genotype in reduced folate carrier 1 (RFC1) rs1051266 had significantly better survival in comparison with patients having the AA genotype (P=0.046). These patients also had a lower frequency of metastasis (15%, P=0.029). Also patients homozygous for the G allele of rs1053129 in the dihydrofolate reductase (DHFR) gene were more likely to have a metastasis (45%, P= 0.005), and the methylenetetetrahydrofolate reductase (MTHFR) 677C allele was associated with higher degree of liver toxicity (88%, P=0.007). The study suggests that germ-line variants in the MTX metabolic pathway are associated with survival and side effects in patients treated with MTX.The Pharmacogenomics Journal advance online publication, 17 March 2015; doi:10.1038/tpj.2015.11.
    The Pharmacogenomics Journal 03/2015; 15(5). DOI:10.1038/tpj.2015.11
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    ABSTRACT: Oxaliplatin-based chemotherapy exerts its effects through generating DNA damage. Hence, genetic variants in DNA repair pathways could modulate treatment response. We used a prospective cohort of 623 colorectal cancer patients with stage II-IV disease treated with adjuvant/palliative chemotherapy to comprehensively investigate 1727 genetic variants in the DNA repair pathways as potential predictive markers for oxaliplatin treatment. Single nucleotide polymorphisms (SNP) associations with overall survival and recurrence-free survival were assessed using a Cox regression model. Pathway analysis was performed using the gamma method. Patients carrying variant alleles of rs3783819 (MNAT1) and rs1043953 (XPC) experienced a longer overall survival after treatment with oxaliplatin than patients who did not carry the variant allele, while the opposite association was found in patients who were not treated with oxaliplatin (false discovery rate-adjusted P-values for heterogeneity 0.0047 and 0.0237, respectively). The nucleotide excision repair (NER) pathway was found to be most likely associated with overall survival in patients who received oxaliplatin (P-value=0.002). Our data show that genetic variants in the NER pathway are potentially predictive of treatment response to oxaliplatin.The Pharmacogenomics Journal advance online publication, 17 March 2015; doi:10.1038/tpj.2015.8.
    The Pharmacogenomics Journal 03/2015; 15(6). DOI:10.1038/tpj.2015.8
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    ABSTRACT: The objective of this study was to determine the effect of the CYP3A5 and ATP binding cassette subfamily B member 1 (ABCB1) single-nucleotide polymorphisms on the disposition of sunitinib and SU12662, on clinical response, and on the manifestation of toxicities in Asian metastatic renal cell carcinoma patients. At week 4 of each treatment cycle, toxicities and plasma steady-state levels were assessed. Clinical response was assessed after two cycles. Genotyping was performed by using the PCR restriction fragment length polymorphism method. The CC genotype for ABCB1 was associated with a higher sunitinib exposure (76.81 vs 56.55 ng ml(-1), P=0.03), higher risk of all-grade rash (RR 3.00, 95% CI 1.17-7.67) and mucositis (RR 1.60, 95% CI 1.10-2.34) and disease progression than compared with the CT/TT genotype. There was a lack of association observed between the CYP3A5 polymorphism and exposure, response and toxicities. The polymorphism of ABCB1 (C3435T) has an important role in the manifestation of toxicities and drug exposure, but not polymorphism of CYP3A5.The Pharmacogenomics Journal advance online publication, 17 March 2015; doi:10.1038/tpj.2015.13.
    The Pharmacogenomics Journal 03/2015; DOI:10.1038/tpj.2015.13
  • X Liu · J Sun · H Yu · H Chen · J Wang · H Zou · D Lu · J Xu · S L Zheng ·
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    ABSTRACT: Multiple HLA-B alleles (haplotypes) are associated with drug-induced adverse responses and disease risks but are difficult to be directly genotyped. The goal of this study is to identify single nucleotide polymorphisms (SNPs) that are able to tag HLA-B alleles in the Chinese Han population. Twelve HLA-B alleles that are associated with drug adverse responses and disease risks were identified. They were sequenced initially in 880 Chinese Han subjects where high-density SNPs within the HLA-B gene were available. Performances of these SNPs to tag the HLA-B alleles were assessed primarily by sensitivity and specificity. Two HLA-B alleles can be reliably tagged by SNPs at 100% sensitivity and >95% specificity. For example, HLA-B*15:02 can be tagged by the 'C' allele of rs10484555, and HLA-B*58:01 can be tagged by the 'T' allele of rs9262570. These results were confirmed in 500 additional Chinese Han subjects. If confirmed in independent studies, these tag SNPs could be used as a reliable, simple and cost-effective alternative for genotyping a subset of HLA-B alleles.The Pharmacogenomics Journal advance online publication, 10 March 2015; doi:10.1038/tpj.2015.7.
    The Pharmacogenomics Journal 03/2015; 15(5). DOI:10.1038/tpj.2015.7
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    ABSTRACT: Statistical imputation of classical human leukocyte antigen (HLA) alleles is becoming an indispensable tool for fine-mappings of disease association signals from case-control genome-wide association studies. However, most currently available HLA imputation tools are based on European reference populations and are not suitable for direct application to non-European populations. Among the HLA imputation tools, The HIBAG R package is a flexible HLA imputation tool that is equipped with a wide range of population-based classifiers; moreover, HIBAG R enables individual researchers to build custom classifiers. Here, two data sets, each comprising data from healthy Japanese individuals of difference sample sizes, were used to build custom classifiers. HLA imputation accuracy in five HLA classes (HLA-A, HLA-B, HLA-DRB1, HLA-DQB1 and HLA-DPB1) increased from the 82.5-98.8% obtained with the original HIBAG references to 95.2-99.5% with our custom classifiers. A call threshold (CT) of 0.4 is recommended for our Japanese classifiers; in contrast, HIBAG references recommend a CT of 0.5. Finally, our classifiers could be used to identify the risk haplotypes for Japanese narcolepsy with cataplexy, HLA-DRB1*15:01 and HLA-DQB1*06:02, with 100% and 99.7% accuracy, respectively; therefore, these classifiers can be used to supplement the current lack of HLA genotyping data in widely available genome-wide association study data sets.The Pharmacogenomics Journal advance online publication, 24 February 2015; doi:10.1038/tpj.2015.4.
    The Pharmacogenomics Journal 02/2015; 15(6). DOI:10.1038/tpj.2015.4