16 research outputs found

    Comprehensive assessment of cytochromes P450 and transporter genetics with endoxifen concentration during tamoxifen treatment

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    Objectives Tamoxifen bioactivation to endoxifen is mediated primarily by CYP2D6; however, considerable variability remains unexplained. Our aim was to perform a comprehensive assessment of the effect of genetic variation in tamoxifen-relevant enzymes and transporters on steady-state endoxifen concentrations. Patients and methods Comprehensive genotyping of CYP enzymes and transporters was performed using the iPLEX ADME PGx Pro Panel in 302 tamoxifen-treated breast cancer patients. Predicted activity phenotype for 19 enzymes and transporters were analyzed for univariate association with endoxifen concentration, and then adjusted for CYP2D6 and clinical covariates. Results In univariate analysis, higher activity of CYP2C8 (regression β=0.22, P=0.020) and CYP2C9 (β=0.20, P=0.04), lower body weight (β=-0.014, P<0.0001), and endoxifen measurement during winter (each β< -0.39, P=0.002) were associated with higher endoxifen concentrations. After adjustment for the CYP2D6 diplotype, weight, and season, CYP2C9 remained significantly associated with higher concentrations (P=0.02), but only increased the overall model R2 by 1.3%. Conclusion Our results further support a minor contribution of CYP2C9 genetic variability toward steadystate endoxifen concentrations. Integration of clinician and genetic variables into individualized tamoxifen dosing algorithms would marginally improve their accuracy and potentially enhance tamoxifen treatment outcomes

    Patients' Understanding of How Genotype Variation Affects Benefits of Tamoxifen Therapy for Breast Cancer

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    CYP2D6 is a critical enzyme in the metabolism of tamoxifen and potentially a key determinant in breast cancer outcomes. Our study examined patients' beliefs about how CYP2D6 genotype would affect their prognoses

    Whole genome sequence association analysis of fasting glucose and fasting insulin levels in diverse cohorts from the NHLBI TOPMed program

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    The genetic determinants of fasting glucose (FG) and fasting insulin (FI) have been studied mostly through genome arrays, resulting in over 100 associated variants. We extended this work with high-coverage whole genome sequencing analyses from fifteen cohorts in NHLBI’s Trans-Omics for Precision Medicine (TOPMed) program. Over 23,000 non-diabetic individuals from five race-ethnicities/populations (African, Asian, European, Hispanic and Samoan) were included. Eight variants were significantly associated with FG or FI across previously identified regions MTNR1B, G6PC2, GCK, GCKR and FOXA2. We additionally characterize suggestive associations with FG or FI near previously identified SLC30A8, TCF7L2, and ADCY5 regions as well as APOB, PTPRT, and ROBO1. Functional annotation resources including the Diabetes Epigenome Atlas were compiled for each signal (chromatin states, annotation principal components, and others) to elucidate variant-to-function hypotheses. We provide a catalog of nucleotide-resolution genomic variation spanning intergenic and intronic regions creating a foundation for future sequencing-based investigations of glycemic traits

    Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

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    Funding Information: GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file : Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services. Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe

    Challenges to Developing Proteomic-Based Breast Cancer Diagnostics

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    Over the past decade, multiple genetic and histological approaches have accelerated development of new breast cancer diagnostics and treatment paradigms. Multiple distinct genetic subtypes of breast cancers have been defined, and this has progressively led toward more personalized medicine in regard to treatment options. There still remains a deficiency in the development of molecular diagnostic assays that can be used for breast cancer detection and pretherapy clinical decisions. In particular, the type of cancer-specific biomarker typified by a serum or tissue-derived protein. Progress in this regard has been minimal, especially in comparison to the rapid advancements in genetic and histological assays for breast cancers. In this review, some potential reasons for this large gap in developing protein biomarkers will be discussed, as well as new strategies for improving these approaches. Improvements in the study design of protein biomarker discovery strategies in relation to the genetic subtypes and histology of breast cancers is also emphasized. The current successes in use of genetic and histological assays for breast cancer diagnostics are summarized, and in that context, the current limitations of the types of breast cancer-related clinical samples available for protein biomarker assay development are discussed. Based on these limitations, research strategies emphasizing identification of glycoprotein biomarkers in blood and MALDI mass spectrometry imaging of tissues are described

    Genetic transformation of Drosophila willistoni using piggyBac transposon and GFP

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    Studies were carried out on the use of piggyBac transposable element as vector and the green fluorescent protein (EGFP) from the jellyfish, Aquorea victoria, as a genetic marker for the transformation of Drosophila willistoni. Preblastoderm embryos of D. willistoni white mutant were microinjected with a plasmid containing the EGFP marker and the piggyBac ITRs, together with a helper plasmid containing the piggyBac transposase placed under the control of the D. melanogaster hsp70 promoter. G0 adults transformants were recovered at a frequency of approximately 67%. Expression of EGFP in larvae, pupae and adults was observed up to the third generation, suggesting that this transposon was not stable in D. willistoni. Transformed individuals displayed high levels of EGFP expression during larvae and adult stages in the eye, abdomen, thorax and legs, suggesting a wide expression pattern in this species than reported to other species of Drosophilidae.<br>Descrevemos neste trabalho a transformação genética de Drosophila willistoni empregando o elemento transponível piggyBac como vetor e o gene EGFP (green fluorescent protein ) retirado da água-viva Aquorea victoria, como marcador de transformação. Embriões de D. willistoni em estágio pré-blastoderme, mutantes para o gene white, foram microinjetados com plasmídio contendo o marcador EGFP e as regiões ITRs do transposon piggyBac concomitantemente com um plasmídio auxiliar possuindo o gene da transposase de piggyBac sobre o controle do promotor do gene hsp70 de Drosophila melanogaster. Adultos transformantes Go foram gerados em uma taxa de 67%. A expressão de GFP em larvas, pupas e adultos foi observada somente até a terceira geração, sugerindo que este transposon não é estável em D. willistoni. Os indivíduos transformados exigem um alto nível de expressão de EGFP durante os estágios de larva e, também em adultos o gene marcador é expresso nos olhos, abdome, tórax e patas, mostrando um padrão de expressão mais amplo nesta espécie do que o registrado para outros drosofilídeos
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