Identification of Isobutyryl-Coa Dehydrogenase and Its Deficiency
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Genes Investigated
BabyNEXTTM EXTENDED Investigated genes and associated diseases Gene Disease OMIM OMIM Condition RUSP gene Disease ABCC8 Familial hyperinsulinism 600509 256450 Metabolic disorder - ABCC8-related Inborn error of amino acid metabolism ABCD1 Adrenoleukodystrophy 300371 300100 Miscellaneous RUSP multisystem (C) * diseases ABCD4 Methylmalonic aciduria and 603214 614857 Metabolic disorder - homocystinuria, cblJ type Inborn error of amino acid metabolism ACAD8 Isobutyryl-CoA 604773 611283 Metabolic Disorder - RUSP dehydrogenase deficiency Inborn error of (S) ** organic acid metabolism ACAD9 acyl-CoA dehydrogenase-9 611103 611126 Metabolic Disorder - (ACAD9) deficiency Inborn error of fatty acid metabolism ACADM Acyl-CoA dehydrogenase, 607008 201450 Metabolic Disorder - RUSP medium chain, deficiency of Inborn error of fatty (C) acid metabolism ACADS Acyl-CoA dehydrogenase, 606885 201470 Metabolic Disorder - RUSP short-chain, deficiency of Inborn error of fatty (S) acid metabolism ACADSB 2-methylbutyrylglycinuria 600301 610006 Metabolic Disorder - RUSP Inborn error of (S) organic acid metabolism ACADVL very long-chain acyl-CoA 609575 201475 Metabolic Disorder - RUSP dehydrogenase deficiency Inborn error of fatty (C) acid metabolism ACAT1 Alpha-methylacetoacetic 607809 203750 Metabolic Disorder - RUSP aciduria Inborn error of (C) organic acid metabolism ACSF3 Combined malonic and 614245 614265 Metabolic Disorder - methylmalonic aciduria Inborn error of organic acid metabolism 1 ADA Severe combined 608958 102700 Primary RUSP immunodeficiency due -
CDH12 Cadherin 12, Type 2 N-Cadherin 2 RPL5 Ribosomal
5 6 6 5 . 4 2 1 1 1 2 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 A A A A A A A A A A A A A A A A A A A A C C C C C C C C C C C C C C C C C C C C R R R R R R R R R R R R R R R R R R R R B , B B B B B B B B B B B B B B B B B B B , 9 , , , , 4 , , 3 0 , , , , , , , , 6 2 , , 5 , 0 8 6 4 , 7 5 7 0 2 8 9 1 3 3 3 1 1 7 5 0 4 1 4 0 7 1 0 2 0 6 7 8 0 2 5 7 8 0 3 8 5 4 9 0 1 0 8 8 3 5 6 7 4 7 9 5 2 1 1 8 2 2 1 7 9 6 2 1 7 1 1 0 4 5 3 5 8 9 1 0 0 4 2 5 0 8 1 4 1 6 9 0 0 6 3 6 9 1 0 9 0 3 8 1 3 5 6 3 6 0 4 2 6 1 0 1 2 1 9 9 7 9 5 7 1 5 8 9 8 8 2 1 9 9 1 1 1 9 6 9 8 9 7 8 4 5 8 8 6 4 8 1 1 2 8 6 2 7 9 8 3 5 4 3 2 1 7 9 5 3 1 3 2 1 2 9 5 1 1 1 1 1 1 5 9 5 3 2 6 3 4 1 3 1 1 4 1 4 1 7 1 3 4 3 2 7 6 4 2 7 2 1 2 1 5 1 6 3 5 6 1 3 6 4 7 1 6 5 1 1 4 1 6 1 7 6 4 7 e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m -
Dietary Amylose:Amylopectin Ratio Influences the Expression of Amino Acid Transporters and Enzyme Activities for Amino Acid Meta
Downloaded from British Journal of Nutrition, page 1 of 11 doi:10.1017/S0007114521002087 https://www.cambridge.org/core © The Author(s), 2021. Published by Cambridge University Press on behalf of The Nutrition Society. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. Dietary amylose:amylopectin ratio influences the expression of amino acid transporters and enzyme activities for amino acid metabolism in the gastrointestinal tract of goats . IP address: 170.106.202.226 Xiaokang Lv1,2, Chuanshe Zhou1,2*, Tao Ran3, Jinzhen Jiao1, Yong Liu1, Zhiliang Tan1, Shaoxun Tang1, Jinhe Kang1, Jingjing Xie1, Liang Chen1, Ao Ren4, Qixiang Xv1,2 and Zhiwei Kong1 1CAS Key Laboratory of Agro-ecological Processes in Subtropical Region, National Engineering Laboratory for Pollution Control and Waste Utilization in Livestock and Poultry Production, Hunan Provincial Key Laboratory of Animal Nutrition & Physiology , on and Metabolism, Institute of Subtropical Agriculture, the Chinese Academy of Sciences, Changsha 410125, People’s Republic of 28 Sep 2021 at 13:00:40 China 2University of Chinese Academy of Sciences, Beijing 100049, People’s Republic of China 3College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730020, People’s Republic of China 4Department of Animal Science and Technology, University of Hunan Agricultural University, Changsha 410128, People’s Republic of China , subject to the Cambridge Core terms of use, available at (Submitted 12 March 2021 – Final revision received 25 May 2021 – Accepted 8 June 2021) Abstract This study was designed to investigate the effects of dietary starch structure on muscle protein synthesis and gastrointestinal amino acid (AA) transport and metabolism of goats. -
Supplementary Materials
Supplementary Materials COMPARATIVE ANALYSIS OF THE TRANSCRIPTOME, PROTEOME AND miRNA PROFILE OF KUPFFER CELLS AND MONOCYTES Andrey Elchaninov1,3*, Anastasiya Lokhonina1,3, Maria Nikitina2, Polina Vishnyakova1,3, Andrey Makarov1, Irina Arutyunyan1, Anastasiya Poltavets1, Evgeniya Kananykhina2, Sergey Kovalchuk4, Evgeny Karpulevich5,6, Galina Bolshakova2, Gennady Sukhikh1, Timur Fatkhudinov2,3 1 Laboratory of Regenerative Medicine, National Medical Research Center for Obstetrics, Gynecology and Perinatology Named after Academician V.I. Kulakov of Ministry of Healthcare of Russian Federation, Moscow, Russia 2 Laboratory of Growth and Development, Scientific Research Institute of Human Morphology, Moscow, Russia 3 Histology Department, Medical Institute, Peoples' Friendship University of Russia, Moscow, Russia 4 Laboratory of Bioinformatic methods for Combinatorial Chemistry and Biology, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry of the Russian Academy of Sciences, Moscow, Russia 5 Information Systems Department, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow, Russia 6 Genome Engineering Laboratory, Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russia Figure S1. Flow cytometry analysis of unsorted blood sample. Representative forward, side scattering and histogram are shown. The proportions of negative cells were determined in relation to the isotype controls. The percentages of positive cells are indicated. The blue curve corresponds to the isotype control. Figure S2. Flow cytometry analysis of unsorted liver stromal cells. Representative forward, side scattering and histogram are shown. The proportions of negative cells were determined in relation to the isotype controls. The percentages of positive cells are indicated. The blue curve corresponds to the isotype control. Figure S3. MiRNAs expression analysis in monocytes and Kupffer cells. Full-length of heatmaps are presented. -
Term Description FDR Matching Proteins in the Network Metabolic Pathways 2.40E-81 AADAT,AASS,ABAT,ACAA2, ACADL, ACADM, ACADS, AC
Term description FDR Matching proteins in the network Metabolic pathways 2.40e-81 AADAT,AASS,ABAT,ACAA2, ACADL, ACADM, ACADS, ACADSB, ACADVL, ACAT1, ACO2, ACOT1, ACOT2, ACOX1, ACSL5, ACSL6, ACSM1, ACSM3, ACSM5, ACSS2, ACSS3, AGMAT, AGXT2, AK4, ALAS1, ALDH1B1, ALDH2, ALDH4A1, ALDH5A1, ALDH6A1, ALDOB, AMACR, AMT, APRT, ARG1, ATP5A1, ATP5B, ATP5C1, ATP5E, ATP5F1, ATP5H, ATP5J, ATP5L, ATP5O, AUH, BCKDHA, BDH1, CHDH, COX4I1, COX7C, CPS1, CS, CYCS, CYP1A2, CYP27A1, DBT, DHRS4, DLAT, DLD, DLST, DMGDH, ECHS1, EHHADH, ENO1, EPHX2, FAHD1, FASN, FDPS, FECH, FH, GBE1, GCDH, GLDC, GLS, GLS2, GLUD1, GOT2, GPAM, GPI, GPT2, H6PD, HADH, HADHA, HADHB, HIBADH, HIBCH, HMGCL, HMGCS2, HSD17B10, HSD17B12, IDH1, IDH2, IDH3A, IDH3G, IVD, MCCC1, MCCC2, MCEE, MDH2, ME1, ME3, MECR, MLYCD, MMAB, MPST, MT-ATP8, MTHFD1L, MUT, NDUFA10, NDUFA12, NDUFA13, NDUFA2, NDUFA5, NDUFA7, NDUFA9, NDUFAB1, NDUFB11, NDUFB3, NDUFS1, NDUFS2, NDUFS3, NDUFS6, NDUFS7, NDUFS8, NDUFV1, NDUFV2, NDUFV3, NNT, OAT, OGDH, OTC, OXSM, PC, PCCA, PCCB, PDHA1, PDHB, PDHX, PRODH2, PYCR2, PYGL, SARDH, SDHA, SDHB, SHMT2, SLC27A5, SUCLA2, SUCLG1, SUCLG2, TST, UGP2, UQCRC2, UQCRFS1, UQCRQ Carbon metabolism 4.12e-43 ACADM, ACADS, ACAT1, ACO2, ACSS2, ALDH6A1, ALDOB, AMT, CAT, CPS1, CS, DLAT, DLD, DLST, ECHS1, EHHADH, ENO1, FH, GLDC, GLUD1, GOT2, GPI, GPT2, H6PD, HADHA, HIBCH, IDH1, IDH2, IDH3A, IDH3G, MCEE, MDH2, ME1, ME2, ME3, MUT, OGDH, PC, PCCA, PCCB, PDHA1, PDHB, SDHA, SDHB, SHMT2, SUCLA2, SUCLG1, SUCLG2 Valine, leucine, and isoleucine degradation 1.44e-33 ABAT, ACAA2, ACADM, ACADS, ACADSB, ACAT1, ACSF3, -
Chain Acyl-Coa Dehydrogenase (Mcad) Deficiency
EXPLORING THERAPEUTIC APPROACHES FOR TREATMENT OF MEDIUM- CHAIN ACYL-COA DEHYDROGENASE (MCAD) DEFICIENCY by Heejung Kang BS, Sungkyunkwan University, South Korea, 2003 MS, Sungkyunkwan University, South Korea, 2005 MS, University of Minnesota, 2008 Submitted to the Graduate Faculty of Graduate School of Public Health in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Pittsburgh 2014 UNIVERSITY OF PITTSBURGH GRADUATE SCHOOL OF PUBLIC HEALTH This dissertation was presented by Heejung Kang It was defended on April 15, 2014 and approved by Dissertation Advisor: Jerry Vockley, M.D. Ph.D., Professor, Pediatrics, School of Medicine, University of Pittsburgh Committee Chair: Robert Ferrell, Ph.D., Professor, Human Genetics, Graduate School of Public Health, University of Pittsburgh David Finegold, Ph.D., Professor, Pediatrics, School of Medicine, University of Pittsburgh Al-Walid A. Mohsen, Ph.D., Research Associate Professor of Pediatrics School of Medicine, University of Pittsburgh Zsolt Urban, Ph.D., Associate Professor, Human Genetics, Graduate School of Public Health, University of Pittsburgh ii Copyright © by Heejung Kang 2014 iii Jerry Vockley, MD, PhD EXPLORING THERAPEUTIC APPROACHES FOR TREATMENT OF MEDIUM- CHAIN ACYL-COA DEHYDROGENASE (MCAD) DEFICIENCY Heejung Kang, PhD University of Pittsburgh, 2014 ABSTRACT Medium chain acyl-CoA dehydrogenase deficiency (MCADD) is a common biochemical genetic disorder in the US. Nearly 90% of alleles from MCADD patients contain a common mutation in the ACADM (c.985A>G). The change replaces a lysine with a glutamate (K304E), causing improper folding. The K304E protein can fold to a mature form and is then stable and active when expressed in a prokaryotic system with molecular chaperonins. -
Common Genetic Variants in the Vitamin D Pathway Including Genome-Wide Associated Variants Are Not Associated with Breast Cancer Risk Among Chinese Women
Author Manuscript Published OnlineFirst on August 9, 2011; DOI: 10.1158/1055-9965.EPI-11-0704 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Null Results in Brief Common genetic variants in the vitamin D pathway including genome-wide associated variants are not associated with breast cancer risk among Chinese women Tsogzolmaa Dorjgochoo1, Ryan Delahanty1, Wei Lu2, Jirong Long1, Qiuyin Cai1, Ying Zheng2, Kai Gu2, Yu-Tang Gao3, Wei Zheng1, Xiao Ou Shu1 1Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA 2Shanghai Center for Disease Control and Prevention, Shanghai, China 3Department of Epidemiology, Shanghai Cancer Institute, Shanghai, China Running title: Vitamin D pathway gene polymorphisms and breast cancer risk Keywords: breast cancer, risk, polymorphisms, vitamin D pathway genes, 25(OH)D, GWAS. Financial Support: This research was supported by USPHS grants R01CA064277, R01CA090899, and R01CA124558. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute or the National Institutes of Health. Sample preparation and genotyping assays, using Affymetrix arrays, were conducted at the Survey and Biospecimen Shared Resource and the Vanderbilt Microarray Shared Resource, respectively, which are supported in part by the Vanderbilt-Ingram Cancer Center (P30CA68485). Corresponding author: Xiao Ou Shu Professor of Medicine Vanderbilt Epidemiology Center Vanderbilt Ingram-Cancer Center Vanderbilt University 2525 West End Avenue, 6th Floor Nashville, TN 37203, USA Tel: 615-936-0713 Fax: 615-936-8291 Email: [email protected] Conflicts of Interest: No potential conflicts of interest. -
Development of a Targeted Second-Tier Genetic Test For
Development of a Targeted Second-Tier Genetic Test for Conditions Examined during Newborn Screening 1Lonna Mollison, 1Chelsea Gustafson, 1Edgar A Rivera-Munoz, 1Alicia Brandt, 1Daniela DeCristo, 1Falecia Metcalf, 2Cynthia Powell, 1Jonathan Berg 1Department of Genetics, 2Department of Pediatrics and Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina Introduction Figure 1. Library HEAT-Seq and SureSelectXT Comparison • Approximately four million children are born annually in the United States, preparation workflows for Agilent’s SureSelectXT most undergo state mandated newborn screening and Roche’s HEAT-Seq. A. B. C. • In 2006 the American College of Medical Genetics and Genomics (ACMG) • Time requirement for developed a recommended uniform screening panel (RUSP) to minimize SureSelectXT was about 32 hours, and variability between states for HEAT-Seq about 8 • Most RUSP conditions are detected by tandem mass spectrometry hours. • Recommended DNA • Through the use of genetic sequencing it is possible to detect the underlying input amount for genetic cause of RUSP conditions SureSelectXT was • Here we propose a step-wise approach to enhance traditional newborn about 3000ng, and for HEAT-Seq was about D. screening and integrate genetic screening into population health using cost- 250ng. effective, targeted sequencing to examine current RUSP conditions • Cost per sample for Figure 4. (A-C) The percent of bases at varying read depths for SureSelectXT HEAT-Seq and SureSelect when normalized to 5M reads (A), 50M (including all human reads (B) and 200M reads (C) for each of the 8 samples. (D) The exon baits) was about percent of targeted bases in all samples sequenced at 30 fold Core Condition Associated Gene(s) ACMG Code $333, and for HEAT- coverage were estimated normalizing the data to various values Maple Syrup Urine Disease BCKDHA, BCKDHB, DBT MSUD Seq (including MIPs) of sequenced reads. -
Establishment and Characterisation of a New Breast Cancer Xenograft Obtained from a Woman Carrying a Germline BRCA2 Mutation
British Journal of Cancer (2010) 103, 1192 – 1200 & 2010 Cancer Research UK All rights reserved 0007 – 0920/10 www.bjcancer.com Establishment and characterisation of a new breast cancer xenograft obtained from a woman carrying a germline BRCA2 mutation 1 ´ 2 1 1 1 2 2,3 L de Plater , A Lauge , C Guyader , M-F Poupon , F Assayag , P de Cremoux , A Vincent-Salomon , 2,3,4 2 5 6 6 6 1,7 D Stoppa-Lyonnet , B Sigal-Zafrani , J-J Fontaine , R Brough , CJ Lord , A Ashworth , P Cottu , 1,7 *,1 D Decaudin and E Marangoni 1 Preclinical Investigation Unit, Institut Curie – Translational Research Department, Hoˆpital St Louis, Quadrilate`re historique, Porte 13, 1, Ave Claude 2 3 4 Vellefaux, Paris 75010, France; Department of Tumor Biology, Institut Curie, Paris, France; INSERM U830, Institut Curie, Paris, France; University Paris Translational Therapeutics 5 6 Descartes, Paris, France; National Veterinary School of Maisons Alfort, Maisons-Alfort, France; Gene Function Laboratory, The Breakthrough Breast 7 Cancer Research Centre, The Institute of Cancer Research, London SW3 6JB, UK; Department of Medical Oncology, Institut Curie, Paris, France BACKGROUND: The BRCA2 gene is responsible for a high number of hereditary breast and ovarian cancers, and studies of the BRCA2 biological functions are limited by the lack of models that resemble the patient’s tumour features. The aim of this study was to establish and characterise a new human breast carcinoma xenograft obtained from a woman carrying a germline BRCA2 mutation. METHODS: A transplantable xenograft was obtained by grafting a breast cancer sample into nude mice. -
Transcriptomic and Proteomic Analysis Reveals Mechanisms of Patulin- Induced Cell Toxicity in Human Embryonic Kidney Cells
Toxins 2020, 12, x; doi: FOR PEER REVIEW S1 of S12 Supplementary Materials: Transcriptomic and Proteomic Analysis Reveals Mechanisms of Patulin- Induced Cell Toxicity in Human Embryonic Kidney Cells Nianfa Han, Ruilin Luo, Jiayu Liu, Tianmin Guo, Jiayu Feng and Xiaoli Peng 100 Control 100 5 µM PAT for 10 h Genes mappled by all clean tags Genes mappled by all clean tags Genes mapped by unambigous 80 Genes mapped by unambigous 80 clean tags clean tags 60 60 40 40 20 20 0 Percentage genes of identified (%) 0 Percentage genes of identified (%) 0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35 Total tag of number (×100 K) Total tag of number (×100 K) Figure S1. Saturation evaluation of detected gene expression. When sequencing amount reaches 2 M or higher, the number of detected genes almost ceases to increase. Toxins 2020, 12, x; doi: FOR PEER REVIEW S2 of S12 Table S1. Statistics of categorization and abundance of digital gene expression (DGE) tags. Control 5 μM PAT for 10 h Total tags Distinct tags Total tags Distinct tags number % number % number % number % Total reads 3,479,005 100.00 335,487 100.00 3,732,185 100.00 359,859 100.00 Tags containing N 3309 0.10 2757 0.82 3328 0.09 2760 0.77 Only adaptors 32 0.00 27 0.01 91 0.00 86 0.02 Copy number < 2 193,285 5.56 193,285 57.61 210,396 5.64 210,396 58.47 clean reads 3,282,379 94.35 139,418 41.56 3,518,370 94.27 146,617 40.74 Copy number (2,5) 238,686 7.27 83,877 60.16 248,991 7.08 87,676 59.80 Copy number (6,10) 160,649 4.89 21,200 15.21 169,270 4.81 22,339 15.24 Copy number (11,20) 208,339 6.35 -
Advantages of Functional Analysis in Comparison of Different Chemometric Techniques for Selecting Obesity-Related Genes of Adipose Tissue from High-Fat Diet-Fed Mice
Biomedical Research and Therapy, 8(3):4277-4285 Open Access Full Text Article Original Research Advantages of functional analysis in comparison of different chemometric techniques for selecting obesity-related genes of adipose tissue from high-fat diet-fed mice Saravanan Dharmaraj*, Mahadeva Rao U. S. , Nordin Simbak ABSTRACT Introduction: Obesity is a lifestyle disease that is becoming prevalent nowadays and is associated with a surplus in energy balance related to lipid metabolism, inflammation and hypoxic condition, Use your smartphone to scan this resulting in maladaptive adipose tissue expansion. This study used the publicly available gene QR code and download this article dataset to identify a small subset of important genes for diagnostics or as potential targets for therapeutics. Methods: Chemometric analyses by principal component analysis (PCA), random forest (RF), and genetic algorithm (GA) were used to identify 50 genes that differentiate adipose samples from high-fat diet- and normal diet-fed mice. The first 30 important genes were studied for classifying the samples using six different classification techniques. Gene ontology (GO), pathway analysis, and protein-protein interaction studies on the 50 selected genes were subsequently done to identify important functional genes. Finally, gene regulatory effects by microRNA were assessed to confirm the genes' potential as targets for new therapeutic drugs. Results: The genes identified by RF are best for differentiating the samples, followed by PCA, with the least predictability shown by genes chosen by GA. However, PCA identified more genes with functional importance, such as the hub genes ATP5a1 and Apoa1. ATP5a1 is the main hub gene, whereas Apoa1 is involved in cholesterol metabolism. -
(12) Patent Application Publication (10) Pub. No.: US 2016/0002733 A1 Chu (43) Pub
US 2016.0002733A1 (19) United States (12) Patent Application Publication (10) Pub. No.: US 2016/0002733 A1 Chu (43) Pub. Date: Jan. 7, 2016 (54) ASSESSING RISK FORENCEPHALOPATHY Related U.S. Application Data INDUCED BYS-FLUOROURACL, OR (60) Provisional application No. 61/772,949, filed on Mar. CAPECTABINE 5, 2013. Publication Classification (71) Applicant: THE BOARD OF TRUSTEES OF THE LELAND STANFORD JUNOR (51) Int. C. UNIVERSITY, Palo Alto, CA (US) CI2O I/68 (2006.01) (52) U.S. C. (72) Inventor: Gilbert Chu, Stanford, CA (US) CPC ........ CI2O I/6886 (2013.01); C12O 2600/156 (2013.01); C12O 2600/106 (2013.01); C12O (21) Appl. No.: 14/769,961 2600/142 (2013.01) (22) PCT Fled: Feb. 26, 2014 (57) ABSTRACT Methods and systems are provided for determining Suscepti (86) PCT NO.: PCT/US14/18739 bility to 5-fluorouracil (5-FU) or capecitabine toxicity. Meth ods are provided for treating a human Subject based on a S371 (c)(1), determined susceptibility to 5-fluorouracil (5-FU) or capecit (2) Date: Aug. 24, 2015 abine toxicity. Patent Application Publication Jan. 7, 2016 Sheet 1 of 17 US 2016/0002733 A1 Figure 1A urea cycle pyrimidine synthesis -- - - - - - - - - - - - Glin / WPA H al-NAGS NH 3. NH3CPSIDcarbamoyl-P Glu->NAG->|CPS Ca rbamyl-Asp: carbamoyl-P OHO : P. Orotate ornithine citruline s --AlORNT - Y - - - OMPwY Ornithine citruline UDP am UMP as UTP RR urea { UDP in OSuccinat A. 5-FUTP arginine 8 gypsuccina e CUMP i. cycleRECTS-5-FdUMP4-5-FU dTMP Figure IB /a-ketoglutarate pyruvate Asp PD PC 4-acetyl-CoA Glu oxaloacetate malate isocitrate Krebs cycle NH3 fumarate a-ketoglutarate Glu succinate succinyl-CoA methylmalonyl-CoA r a fatty acid proponyi-UOE.