Rare Genetic Variants in Cellular Transporters, Metabolic Enzymes, and Nuclear Receptors Can Be Important Determinants of Interindividual Differences in Drug Response

Total Page:16

File Type:pdf, Size:1020Kb

Rare Genetic Variants in Cellular Transporters, Metabolic Enzymes, and Nuclear Receptors Can Be Important Determinants of Interindividual Differences in Drug Response ORIGINAL RESEARCH ARTICLE © American College of Medical Genetics and Genomics Rare genetic variants in cellular transporters, metabolic enzymes, and nuclear receptors can be important determinants of interindividual differences in drug response Mikael Kozyra, Medical student1, Magnus Ingelman-Sundberg, PhD1 and Volker M. Lauschke, PhD1 Purpose: In this study we characterized the genetic variability of respectively. Additionally, by analyzing variation patterns across 146 clinically relevant genes influencing drug pharmacokinetics in these populations, we pinpointed potential priority genes for popula- African and European subpopulations, which are key determinants tion-adjusted genetic profiling strategies. Furthermore, we estimated, for interindividual variations in drug efficacy and adverse drug based on our variant frequency analyses, that approximately 30–40% reactions. of functional variability in pharmacogenes can be attributed to rare variants. Methods: By integrating data from the 1000 Genomes Project (n = 1,092 individuals) and the Exome Sequencing Project (ESP; n = 6,503 Conclusions: Our results indicate that these clinically important individuals), single-nucleotide variants (SNVs) were identified and genes are genetically highly variable and differ considerably between analyzed regarding frequency, functional consequences, and ethnic populations. Furthermore, the large extent of rare variants empha- diversity. sizes the need for sequencing-based approaches and effective func- Results: In total, we found 12,152 SNVs in exons, 312 of which were tionality predictions to allow for true personalized medicine. novel. The majority of variants were rare (minor allele frequency Genet Med advance online publication 21 April 2016 (MAF) <1%; 92.9%) and nonsynonymous (56.2%). We calculated that individuals of European and African descent harbor, on aver- Key Words: drug development; genetic variation; personalized age, 100.8 and 121.4 variants across the 146 pharmacogenes ­studied, medicine; pharmacogenes; rare variants INTRODUCTION the European Medicines Agency4 to optimize drug treatment. The development of next-generation sequencing platforms and These studies also uncovered a vast repertoire of genetic vari- the mapping of the human genome have transformed the field ants with profound impact on drug metabolism, some of which of pharmacogenetics into pharmacogenomics, thus expanding have been successfully translated in clinical practice.5 its scope from a candidate-driven approach to genome-wide Much research has been focused on the cytochrome P450 studies of associations. The vast amount of genetic information (CYP) superfamily of genes because these are major contribu- opens new possibilities to describe and categorize the extent of tors to drug metabolism, primarily in the liver. The impact of genetic polymorphisms in the human genome at the popula- this variation on drug response and ADRs is extensive; recently, tion level. a comprehensive overview of the genetic variability within the Interindividual differences in drug pharmacokinetics (PK) CYP super gene family with important implications for person- and pharmacodynamics (PD) can cause the loss of treatment alized medicine was published.6 Yet, a plethora of other genes efficacy or give rise to adverse drug reactions (ADRs) with neg- such as other phase I enzymes, phase II conjugation enzymes, ative consequences for patients. In addition, ADRs can be as transporters, cytochrome reductases, and nuclear receptors, costly for society when they occur with the initial treatment for hereafter jointly termed “pharmacogenes,” also impact PK and symptoms.1 They are the prime cause of drug withdrawal from PD directly or indirectly and can cause ADRs.7 the market, resulting in significant costs for the pharmaceutical Genes encoding transporter proteins belong primarily to industry that have been calculated as approximately US$2.6 bil- two large gene families: the ATP-binding cassette (ABC) super- lion per new drug.2 In recent decades, much research has aimed family, whose members export substances out of cells, and to identify the genetic basis for interindividual differences in the solute carrier (SLC) superfamily, which mostly mediate drug response and toxicity; in particular, this work has resulted molecule influx. They can translocate a vast variety of com- in a series of genomic drug labels by the Food and Drug pounds like xenobiotics and drugs, thereby impacting PD and Administration (FDA)3 (http://www.fda.gov/drugs/sciencere- PK.8 Transporters of the ABC family are important in cancer search/researchareas/pharmacogenetics/ucm083378.htm) and therapy because they can confer resistance to chemotherapy by 1Section of Pharmacogenetics, Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden. Correspondence: Volker M. Lauschke ([email protected]) Submitted 26 November 2015; accepted 2 February 2016; advance online publication 21 April 2016. doi:10.1038/gim.2016.33 20 Volume 19 | Number 1 | January 2017 | GEnEticS in mEdicinE Genetic variability in pharmacogenes | KOZYRA et al ORIGINAL RESEARCH ARTICLE extruding chemotherapeutic drugs; thus, they are associated ucm083378.htm), a comprehensive overview of the inventory with poor prognosis.9 of genetic variation on a population level is still lacking. Here, The SLC transporter family contains more than 300 genes we present an extensive data set of human polymorphisms with selectivity to structurally diverse compounds whose vari- within important pharmacogenes based on two population ants impact drug PK. One such example is given by genetic sequencing projects: the ESP of the National Heart, Lung, and polymorphisms in SLCO1B1, a gene encoding the cellular Blood Institute22 and the 1000 Genomes Project.23 We provide transporter OATP1B1 that mediates influx of a wide variety of an overview and classification of variants across populations pharmaceutical substances like various statins, bosentan, and and assess the contribution of rare variants to overall functional troglitazone.10 The single-nucleotide variant (SNV) rs4149056 variability. Furthermore, the data presented here deliver new in SLCO1B1 (SLCO1B1*5) has been shown to profoundly influ- insights into genetic variants that potentially affect drug effi- ence statin uptake, resulting in lower inhibition of HMG-CoA cacy and can thus incentivize the adoption of this knowledge and increased blood cholesterol levels.11 Furthermore, the into clinical practice. rs4363657 variant, which is in almost complete linkage dis- equilibrium with rs4149056, showed a strong association with MATERIAL AND METHODS statin-induced myopathy.12 Inversely, treatment efficacy of the Data collection and filtration antidiabetes drug repaglinide is increased in variant carriers A list of important pharmacogenes was collected from http:// because hepatic uptake primes the compound for biotransfor- www.pharmaadme.org and expanded with genes from the liter- mation into inactive metabolites.13 ature that could play a role in the PK or PD. Data on each of the In addition to transporters, phase II enzymes constitute an 146 genes were collected from ESP database (http://www.nhlbi. important class of pharmacogenes that are responsible for nih.gov/) release ESP6500SI-V222 and from 1000 Genomes the detoxification and inactivation of drugs, mostly by trans- Project release 20130502 (http://www.ncbi.nlm.nih.gov/varia- fer of chemical moieties that render the drug, toxin, or hor- tion/tools/1000genomes).23 Information regarding variants was mone more hydrophilic and facilitate excretion. Major phase retrieved from NCBI dbSNP release 134 (http://www.nlm.nih. II pathways include conjugation with glucuronides by UDP- gov/SNP/), Ensembl variation (http://www.ensembl.org/info/ glucuronosyltransferases (UGTs), the addition of glutathione genome/variation/index.html), and UCSC genome browser by glutathione-S-transferases (GSTs), and sulfonation cata- (http://genome.ucsc.edu/). Variation rates were calculated as lyzed by sulfotransferases (SULTs). UGTs contribute to the bio- follows: transformation of drugs and other exogenous substances, such SUMM()AF ×+nnSUMM()AF × as tobacco smoke carcinogens as well as environmental and VR = EA EA AA AA +× dietary pollutants.14 Kinetics of these detoxification processes ()nnEA AA 100 influence exposure to toxic or carcinogenic substances and thus where SUM(MAF) is the aggregated minor allele frequen- can modify the susceptibility to exposure-induced diseases cies and n is the allele sample size for European Americans such as cancer.14 Furthermore, genetic variants can influence or African Americans, respectively. All chromosome files the susceptibility to drug-induced toxicity, as exemplified by were obtained from http://ftp.1000genomes.ebi.ac.uk/vol1/ ADRs seen upon treatment with irinotecan.15 GSTs catalyze the ftp/phase1/analysis_results/supporting/accessible_genome_ transfer of reduced glutathione to unipolar compounds such as masks/ and analyzed using UGENE (http://ugene.unipro.ru). halogenonitrobenzenes, quinones, and unsaturated carbonyls.16 Gene coordinates were obtained from GeneCards (version Genetic variants in GSTs affect the metabolism of busulfan and 3.12.396 26 May 2015). cyclophosphamide, two compounds with narrow therapeutic ranges used in conditioning prior to hematopoietic stem cell Quality assessment of sequencing methods transplantations.17 Sulfonation of drugs, environmental chemi- The suitability of short-read sequencing technologies
Recommended publications
  • Supplementary Data
    Figure 2S 4 7 A - C 080125 CSCs 080418 CSCs - + IFN-a 48 h + IFN-a 48 h + IFN-a 72 h 6 + IFN-a 72 h 3 5 MRFI 4 2 3 2 1 1 0 0 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 7 B 13 080125 FBS - D 080418 FBS - + IFN-a 48 h 12 + IFN-a 48 h + IFN-a 72 h + IFN-a 72 h 6 080125 FBS 11 10 5 9 8 4 7 6 3 MRFI 5 4 2 3 2 1 1 0 0 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 Molecule Molecule FIGURE 4S FIGURE 5S Panel A Panel B FIGURE 6S A B C D Supplemental Results Table 1S. Modulation by IFN-α of APM in GBM CSC and FBS tumor cell lines. Molecule * Cell line IFN-α‡ HLA β2-m# HLA LMP TAP1 TAP2 class II A A HC§ 2 7 10 080125 CSCs - 1∞ (1) 3 (65) 2 (91) 1 (2) 6 (47) 2 (61) 1 (3) 1 (2) 1 (3) + 2 (81) 11 (80) 13 (99) 1 (3) 8 (88) 4 (91) 1 (2) 1 (3) 2 (68) 080125 FBS - 2 (81) 4 (63) 4 (83) 1 (3) 6 (80) 3 (67) 2 (86) 1 (3) 2 (75) + 2 (99) 14 (90) 7 (97) 5 (75) 7 (100) 6 (98) 2 (90) 1 (4) 3 (87) 080418 CSCs - 2 (51) 1 (1) 1 (3) 2 (47) 2 (83) 2 (54) 1 (4) 1 (2) 1 (3) + 2 (81) 3 (76) 5 (75) 2 (50) 2 (83) 3 (71) 1 (3) 2 (87) 1 (2) 080418 FBS - 1 (3) 3 (70) 2 (88) 1 (4) 3 (87) 2 (76) 1 (3) 1 (3) 1 (2) + 2 (78) 7 (98) 5 (99) 2 (94) 5 (100) 3 (100) 1 (4) 2 (100) 1 (2) 070104 CSCs - 1 (2) 1 (3) 1 (3) 2 (78) 1 (3) 1 (2) 1 (3) 1 (3) 1 (2) + 2 (98) 8 (100) 10 (88) 4 (89) 3 (98) 3 (94) 1 (4) 2 (86) 2 (79) * expression of APM molecules was evaluated by intracellular staining and cytofluorimetric analysis; ‡ cells were treatead or not (+/-) for 72 h with 1000 IU/ml of IFN-α; # β-2 microglobulin; § β-2 microglobulin-free HLA-A heavy chain; ∞ values are indicated as ratio between the mean of fluorescence intensity of cells stained with the selected mAb and that of the negative control; bold values indicate significant MRFI (≥ 2).
    [Show full text]
  • Screening and Identification of Key Biomarkers in Clear Cell Renal Cell Carcinoma Based on Bioinformatics Analysis
    bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Screening and identification of key biomarkers in clear cell renal cell carcinoma based on bioinformatics analysis Basavaraj Vastrad1, Chanabasayya Vastrad*2 , Iranna Kotturshetti 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. 3. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka 562209, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Abstract Clear cell renal cell carcinoma (ccRCC) is one of the most common types of malignancy of the urinary system. The pathogenesis and effective diagnosis of ccRCC have become popular topics for research in the previous decade. In the current study, an integrated bioinformatics analysis was performed to identify core genes associated in ccRCC. An expression dataset (GSE105261) was downloaded from the Gene Expression Omnibus database, and included 26 ccRCC and 9 normal kideny samples. Assessment of the microarray dataset led to the recognition of differentially expressed genes (DEGs), which was subsequently used for pathway and gene ontology (GO) enrichment analysis.
    [Show full text]
  • Small Cell Ovarian Carcinoma: Genomic Stability and Responsiveness to Therapeutics
    Gamwell et al. Orphanet Journal of Rare Diseases 2013, 8:33 http://www.ojrd.com/content/8/1/33 RESEARCH Open Access Small cell ovarian carcinoma: genomic stability and responsiveness to therapeutics Lisa F Gamwell1,2, Karen Gambaro3, Maria Merziotis2, Colleen Crane2, Suzanna L Arcand4, Valerie Bourada1,2, Christopher Davis2, Jeremy A Squire6, David G Huntsman7,8, Patricia N Tonin3,4,5 and Barbara C Vanderhyden1,2* Abstract Background: The biology of small cell ovarian carcinoma of the hypercalcemic type (SCCOHT), which is a rare and aggressive form of ovarian cancer, is poorly understood. Tumourigenicity, in vitro growth characteristics, genetic and genomic anomalies, and sensitivity to standard and novel chemotherapeutic treatments were investigated in the unique SCCOHT cell line, BIN-67, to provide further insight in the biology of this rare type of ovarian cancer. Method: The tumourigenic potential of BIN-67 cells was determined and the tumours formed in a xenograft model was compared to human SCCOHT. DNA sequencing, spectral karyotyping and high density SNP array analysis was performed. The sensitivity of the BIN-67 cells to standard chemotherapeutic agents and to vesicular stomatitis virus (VSV) and the JX-594 vaccinia virus was tested. Results: BIN-67 cells were capable of forming spheroids in hanging drop cultures. When xenografted into immunodeficient mice, BIN-67 cells developed into tumours that reflected the hypercalcemia and histology of human SCCOHT, notably intense expression of WT-1 and vimentin, and lack of expression of inhibin. Somatic mutations in TP53 and the most common activating mutations in KRAS and BRAF were not found in BIN-67 cells by DNA sequencing.
    [Show full text]
  • Epigenetic Interplay Between Mouse Endogenous
    Rebollo et al. Genome Biology 2012, 13:R89 http://genomebiology.com/2012/13/10/R89 RESEARCH Open Access Epigenetic interplay between mouse endogenous retroviruses and host genes Rita Rebollo1,2†, Katharine Miceli-Royer1,2†, Ying Zhang1,2, Sharareh Farivar1,2, Liane Gagnier1,2 and Dixie L Mager1,2* Abstract Background: Transposable elements are often the targets of repressive epigenetic modifications such as DNA methylation that, in theory, have the potential to spread toward nearby genes and induce epigenetic silencing. To better understand the role of DNA methylation in the relationship between transposable elements and genes, we assessed the methylation state of mouse endogenous retroviruses (ERVs) located near genes. Results: We found that ERVs of the ETn/MusD family show decreased DNA methylation when near transcription start sites in tissues where the nearby gene is expressed. ERVs belonging to the IAP family, however, are generally heavily methylated, regardless of the genomic environment and the tissue studied. Furthermore, we found full- length ETn and IAP copies that display differential DNA methylation between their two long terminal repeats (LTRs), suggesting that the environment surrounding gene promoters can prevent methylation of the nearby LTR. Spreading from methylated ERV copies to nearby genes was rarely observed, with the regions between the ERVs and genes apparently acting as a boundary, enriched in H3K4me3 and CTCF, which possibly protects the unmethylated gene promoter. Furthermore, the flanking regions of unmethylated ERV copies harbor H3K4me3, consistent with spreading of euchromatin from the host gene toward ERV insertions. Conclusions: We have shown that spreading of DNA methylation from ERV copies toward active gene promoters is rare.
    [Show full text]
  • Iron Depletion Reduces Abce1 Transcripts While Inducing The
    Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 22 October 2019 doi:10.20944/preprints201910.0252.v1 1 Research Article 2 Iron depletion Reduces Abce1 Transcripts While 3 Inducing the Mitophagy Factors Pink1 and Parkin 4 Jana Key 1,2, Nesli Ece Sen 1, Aleksandar Arsovic 1, Stella Krämer 1, Robert Hülse 1, Suzana 5 Gispert-Sanchez 1 and Georg Auburger 1,* 6 1 Experimental Neurology, Goethe University Medical School, 60590 Frankfurt am Main; 7 2 Faculty of Biosciences, Goethe-University Frankfurt am Main, Germany 8 * Correspondence: [email protected] 9 10 Abstract: Lifespan extension was recently achieved in Caenorhabditis elegans nematodes by 11 mitochondrial stress and mitophagy, triggered via iron depletion. Conversely in man, deficient 12 mitophagy due to Pink1/Parkin mutations triggers iron accumulation in patient brain and limits 13 survival. We now aimed to identify murine fibroblast factors, which adapt their mRNA expression 14 to acute iron manipulation, relate to mitochondrial dysfunction and may influence survival. After 15 iron depletion, expression of the plasma membrane receptor Tfrc with its activator Ireb2, the 16 mitochondrial membrane transporter Abcb10, the heme-release factor Pgrmc1, the heme- 17 degradation enzyme Hmox1, the heme-binding cholesterol metabolizer Cyp46a1, as well as the 18 mitophagy regulators Pink1 and Parkin showed a negative correlation to iron levels. After iron 19 overload, these factors did not change expression. Conversely, a positive correlation of mRNA levels 20 with both conditions of iron availability was observed for the endosomal factors Slc11a2 and Steap2, 21 as well as for the iron-sulfur-cluster (ISC)-containing factors Ppat, Bdh2 and Nthl1.
    [Show full text]
  • A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
    Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated.
    [Show full text]
  • ABCC12 Monoclonal Antibody, Clone M9II-3
    ABCC12 monoclonal antibody, Gene Symbol: ABCC12 clone M9II-3 Gene Alias: MGC27071, MRP9 Catalog Number: MAB6675 Gene Summary: This gene is a member of the superfamily of ATP-binding cassette (ABC) transporters Regulatory Status: For research use only (RUO) and the encoded protein contains two ATP-binding domains and 12 transmembrane regions. ABC proteins Product Description: Rat monoclonal antibody raised transport various molecules across extra- and against partial recombinant ABCC12. intracellular membranes. ABC genes are divided into Clone Name: M9II-3 seven distinct subfamilies: ABC1, MDR/TAP, MRP, ALD, OABP, GCN20, and White. This gene is a member of Immunogen: Recombinant protein corresponding to the MRP subfamily which is involved in multi-drug amino acids 690-734 of human ABCC12. resistance. This gene and another subfamily member are arranged head-to-tail on chromosome 16q12.1. Host: Rat Increased expression of this gene is associated with breast cancer. [provided by RefSeq] Reactivity: Human References: Applications: ICC, IHC-Fr, WB 1. Multidrug resistance-associated protein 9 (ABCC12) is (See our web site product page for detailed applications present in mouse and boar sperm. Ono N, Van der information) Heijden I, Scheffer GL, Van de Wetering K, Van Deemter E, De Haas M, Boerke A, Gadella BM, De Rooij Protocols: See our web site at DG, Neefjes JJ, Groothuis TA, Oomen L, Brocks L, http://www.abnova.com/support/protocols.asp or product Ishikawa T, Borst P. Ono N, Van der Heijden I, Scheffer page for detailed protocols GL, Van de Wetering K, Van Deemter E, De Haas M, Boerke A, Gadella BM, De Rooij DG, Neefjes JJ, Specificity: M9II-3 reacts with an internal epitope of Groothuis TA, Oomen L, Brocks L, Ishikawa T, Borst P.
    [Show full text]
  • Protein Identities in Evs Isolated from U87-MG GBM Cells As Determined by NG LC-MS/MS
    Protein identities in EVs isolated from U87-MG GBM cells as determined by NG LC-MS/MS. No. Accession Description Σ Coverage Σ# Proteins Σ# Unique Peptides Σ# Peptides Σ# PSMs # AAs MW [kDa] calc. pI 1 A8MS94 Putative golgin subfamily A member 2-like protein 5 OS=Homo sapiens PE=5 SV=2 - [GG2L5_HUMAN] 100 1 1 7 88 110 12,03704523 5,681152344 2 P60660 Myosin light polypeptide 6 OS=Homo sapiens GN=MYL6 PE=1 SV=2 - [MYL6_HUMAN] 100 3 5 17 173 151 16,91913397 4,652832031 3 Q6ZYL4 General transcription factor IIH subunit 5 OS=Homo sapiens GN=GTF2H5 PE=1 SV=1 - [TF2H5_HUMAN] 98,59 1 1 4 13 71 8,048185945 4,652832031 4 P60709 Actin, cytoplasmic 1 OS=Homo sapiens GN=ACTB PE=1 SV=1 - [ACTB_HUMAN] 97,6 5 5 35 917 375 41,70973209 5,478027344 5 P13489 Ribonuclease inhibitor OS=Homo sapiens GN=RNH1 PE=1 SV=2 - [RINI_HUMAN] 96,75 1 12 37 173 461 49,94108966 4,817871094 6 P09382 Galectin-1 OS=Homo sapiens GN=LGALS1 PE=1 SV=2 - [LEG1_HUMAN] 96,3 1 7 14 283 135 14,70620005 5,503417969 7 P60174 Triosephosphate isomerase OS=Homo sapiens GN=TPI1 PE=1 SV=3 - [TPIS_HUMAN] 95,1 3 16 25 375 286 30,77169764 5,922363281 8 P04406 Glyceraldehyde-3-phosphate dehydrogenase OS=Homo sapiens GN=GAPDH PE=1 SV=3 - [G3P_HUMAN] 94,63 2 13 31 509 335 36,03039959 8,455566406 9 Q15185 Prostaglandin E synthase 3 OS=Homo sapiens GN=PTGES3 PE=1 SV=1 - [TEBP_HUMAN] 93,13 1 5 12 74 160 18,68541938 4,538574219 10 P09417 Dihydropteridine reductase OS=Homo sapiens GN=QDPR PE=1 SV=2 - [DHPR_HUMAN] 93,03 1 1 17 69 244 25,77302971 7,371582031 11 P01911 HLA class II histocompatibility antigen,
    [Show full text]
  • Alternating Hypoglycemia and Hyperglycemia in a Toddler with a Homozygous P.R1419H ABCC8 Mutation: an Unusual Clinical Picture
    J Pediatr Endocr Met 2015; 28(3-4): 345–351 Patient report Open Access Shira Harel, Ana S.A. Cohen, Khalid Hussain, Sarah E. Flanagan, Kamilla Schlade-Bartusiak, Millan Patel, Jaques Courtade, Jenny B.W. Li, Clara Van Karnebeek, Harley Kurata, Sian Ellard, Jean-Pierre Chanoine and William T. Gibson* Alternating hypoglycemia and hyperglycemia in a toddler with a homozygous p.R1419H ABCC8 mutation: an unusual clinical picture Abstract Results: A 16-month-old girl of consanguineous descent manifested hypoglycemia. She had dysregulation of Background: Inheritance of two pathogenic ABCC8 alleles insulin secretion, with postprandial hyperglycemia fol- typically causes severe congenital hyperinsulinism. We lowed by hypoglycemia. Microarray revealed homozygo- describe a girl and her father, both homozygous for the sity for the regions encompassing KCNJ11 and ABCC8. Her same ABCC8 mutation, who presented with unusual father had developed diabetes at 28 years of age. Sequenc- phenotypes. ing of ABCC8 identified a homozygous missense mutation, Methods: Single nucleotide polymorphism microarray p.R1419H, in both individuals. Functional studies showed and Sanger sequencing were performed. Western blot, absence of working KATP channels. rubidium efflux, and patch clamp recordings interrogated Conclusion: This is the first description of a homozygous the expression and activity of the mutant protein. p.R1419H mutation. Our findings highlight that homozy- gous loss-of-function mutations of ABCC8 do not neces- sarily translate into early-onset severe hyperinsulinemia. *Corresponding author: William T. Gibson, Child and Family Research Institute, Department of Medical Genetics, British Keywords: ABCC8; diabetes; hyperglycemia; hyperinsu- Columbia Children’s Hospital, 950 West 28th Avenue, Vancouver, linism; hypoglycemia. BC, V5Z 4H4, Canada, Phone: +1-604-875-2000 ext.
    [Show full text]
  • The Concise Guide to Pharmacology 2019/20
    Edinburgh Research Explorer THE CONCISE GUIDE TO PHARMACOLOGY 2019/20 Citation for published version: Cgtp Collaborators 2019, 'THE CONCISE GUIDE TO PHARMACOLOGY 2019/20: Transporters', British Journal of Pharmacology, vol. 176 Suppl 1, pp. S397-S493. https://doi.org/10.1111/bph.14753 Digital Object Identifier (DOI): 10.1111/bph.14753 Link: Link to publication record in Edinburgh Research Explorer Document Version: Publisher's PDF, also known as Version of record Published In: British Journal of Pharmacology General rights Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) and / or other copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated with these rights. Take down policy The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer content complies with UK legislation. If you believe that the public display of this file breaches copyright please contact [email protected] providing details, and we will remove access to the work immediately and investigate your claim. Download date: 28. Sep. 2021 S.P.H. Alexander et al. The Concise Guide to PHARMACOLOGY 2019/20: Transporters. British Journal of Pharmacology (2019) 176, S397–S493 THE CONCISE GUIDE TO PHARMACOLOGY 2019/20: Transporters Stephen PH Alexander1 , Eamonn Kelly2, Alistair Mathie3 ,JohnAPeters4 , Emma L Veale3 , Jane F Armstrong5 , Elena Faccenda5 ,SimonDHarding5 ,AdamJPawson5 , Joanna L
    [Show full text]
  • Structures and Functions of Mitochondrial ABC Transporters
    ATP-binding cassette transporters: from mechanism to organism 943 Structures and functions of mitochondrial ABC transporters Theresia A. Schaedler*, Belinda Faust†, Chitra A. Shintre†, Elisabeth P. Carpenter†, Vasundara Srinivasan‡, Hendrik W. van Veen§ and Janneke Balk1 *Department of Biological Chemistry and Crop Protection, Rothamsted Research, West Common, Harpenden, AL5 2JQ, U.K. †Structural Genomics Consortium, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, OX3 7DQ, U.K. ‡LOEWE center for synthetic microbiology (SYNMIKRO) and Philipps University, D-35043 Marburg, Germany §Department of Pharmacology, University of Cambridge, Tennis Court Road, Cambridge, CB2 1PD, U.K. John Innes Centre and University of East Anglia, Colney Lane, Norwich, NR4 7UH, U.K. Abstract A small number of physiologically important ATP-binding cassette (ABC) transporters are found in mitochondria. Most are half transporters of the B group forming homodimers and their topology suggests they function as exporters. The results of mutant studies point towards involvement in iron cofactor biosynthesis. In particular, ABC subfamily B member 7 (ABCB7) and its homologues in yeast and plants are required for iron-sulfur (Fe-S) cluster biosynthesis outside of the mitochondria, whereas ABCB10 is involved in haem biosynthesis. They also play a role in preventing oxidative stress. Mutations in ABCB6 and ABCB7 have been linked to human disease. Recent crystal structures of yeast Atm1 and human ABCB10 have been key to identifying substrate-binding sites and transport mechanisms. Combined with in vitro and in vivo studies, progress is being made to find the physiological substrates of the different mitochondrial ABC transporters. Sequence analysis of mitochondrial ABC The ABCB7 group, which includes the ABC transporters transporters of the mitochondria Atm1 in yeast and ATM3 in Arabidopsis, Mitochondria of most eukaryote species harbour 2–4 can be found in virtually all eukaryotic species.
    [Show full text]
  • Taqman® Openarray® Pharmacogenomics (Pgx) Panel
    PRODUCT OVERVIEW TaqMan® OpenArray® Pharmacogenomics (PGx) Panel TaqMan® OpenArray® Pharmacogenomics (PGx) Panel Genotyping analysis of drug metabolism enzymes and associated transport proteins The TaqMan® OpenArray® Trusted TaqMan® performance samples, studies, and labs. Assays Pharmacogenomics (PGx) Panel is Each TaqMan® DME Genotyping were selected for optimal relevance a powerful tool to help researchers Assay contains two allele-specific to current pharmacogenomics study human genetic variation probes and a primer pair to detect studies and organized for a simplified in relation to drug action and its the specific SNP target. Both the workflow. potential application to medical probes and primers uniquely align ® ® treatment. within the genome, enabling the The TaqMan OpenArray PGx TaqMan® genotyping technology to Panel provides valuable data for ® ® The TaqMan OpenArray PGx provide superior specificity. It is this the study of drug interactions in Panel was developed for quick and specificity that allows these assays several research areas. Targeted easy screening of known high- to detect targets residing in highly genes relate to areas of study such value target genes associated with homologous gene families that may as cardiovascular (CYP2D6, CYP2C19, drug metabolism enzymes and include pseudogenes. TaqMan® Drug NAT1, NAT2), analgesics (CYP2C9, associated transport proteins. Metabolism Enzyme Genotyping CYP2D6), rheumatology (CYP2C9, The panel consists of 158 drug Assays were developed using a high TPMT), neurology (CYP2C19, CYP2D6), metabolism enzyme (DME) assays level of bioinformatics and wet-lab and musculoskeletal (CYP2C19). A derived from the PharmaADME stringency. All assays have passed total of 29 genes are covered across Core Marker Set (Table 1). The performance tests involving 180 158 unique assays.
    [Show full text]