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Oculocutaneous Albinism CBA HoliRD REPORT: Oculocutaneous Albinism Marina Esteban Medina María Peña-Chilet Carlos Loucera Joaquín Dopazo Clinical Bioinformatics Area - FPS Sevilla, January 27, 2020 Collaborators: Dr.Luis Montoliu’s group - U756 CIBERER Research team at National Centre of Biotechnology (CNB-CSIC), Campus Cantoblanco, Madrid. CBA Objectives and methodology: The Holistic Rare Disease project (HoliRD) aims to build Diseases Maps for as many Rare Diseases as possible and to model them to systematize research in drug repurposing. In order to achieve this purpose several databases such as ORPHANET, OMIM, HPO, PubMed, KEGG, STRING, as well as the literature is used to collect all the up-to-date knowledge of the diseases under study and defining a Disease Map that contains the functional relationships among the known disease genes, as well as the functional consequences of their activity. Then, a mechanistic model that accounts for the activity of such map is used. The HiPathia algorithm, which has successfully proven to predict cell activities related to cancer hallmarks (Hidalgo et al., Oncotarget 2017; 8:5160-5178; Hidalgo et al., Biol Direct. 2018;13:16) as well as the effect of protein inhibitions on cell survival (Cubuk et al., Cancer Res. 2018; 78:6059-6072) is used to simulate the activity of the disease map. Finally, machine learning algorithms are used to find other proteins, already target of drugs with another indication, which display a potential causal effect on the activity of the previously defined disease map. The drugs that target these proteins are potential candidates for repurposing. Schematic representation of the method used. Examples of the use of this approach can be found in Esteban-Medina et al., BMC Bioinformatics. 2019, 20(1):370. CBA Report This report describes the results of the different steps of the HoliRD approach applied to Oculocutaneous Albinism. Identification of genes highly related to the rare disease (RD) under study in Orphanet/OMIM A total of 7 genes annotated as Oculocutaneous Albinism (ALB) were found in the Orphanet / OMIM database. ALB highly related genes Disease ID Entrez ID Gene Symbol OMIM:203200 4948 OCA2 ORPHA:370097 283652 SLC24A5 ORPHA:79433 7306 TYRP1 ORPHA:79435 51151 SLC45A2 OMIM:615179 83938 LRMDA ORPHA:79434 7299 TYR ORPHA:79432 4157 MC1R CBA Identification of highly related HPO to the RD under study: A total of 13 HPO codes associated to ALB with specificity >=7 were selected. ALB highly related HPOs HPO ID HPO term Specificity level HP:0000483 Astigmatism 10 HP:0000486 Strabismus 7 HP:0000613 Photophobia 9 HP:0000639 Nystagmus 7 HP:0000992 Cutaneous photosensitivity 7 HP:0002227 White eyelashes 15 HP:0002671 Basal cell carcinoma 8 HP:0006739 Squamous cell carcinoma of the skin 9 HP:0007513 Generalized hypopigmentation 8 HP:0007730 Iris hypopigmentation 9 HP:0007750 Hypoplasia of the fovea 15 HP:0008499 High hypermetropia 7 HP:0011364 White hair 9 CBA Identification of genes that shared at least RD-HPO codes Genes with >= 4 ALB-HPO codes Gene symbol Entrez Gene symbol Entrez Gene symbol Entrez RERE 473 MYO5A 4644 AP3B1 8546 CACNA1F 778 NDN 4692 HERC2 8924 LYST 1130 GPR143 4935 AP3D1 8943 CNGA3 1261 OCA2 4948 RECQL4 9401 DDB2 1643 PCYT1A 5130 MKRN3-AS1 10108 ERCC2 2068 PDE6C 5146 HPS5 11234 ERCC3 2071 PDE6H 5149 ATF6 22926 ERCC4 2072 PITX2 5308 PMPCA 23203 ERCC5 2073 PITX3 5309 CRB1 23418 ERCC6 2074 RPGR 6103 NPAP1 23742 FOXE3 2301 SKI 6497 SLC45A2 51151 GABRD 2563 SNRPN 6638 MAGEL2 54551 GJA1 2697 TYR 7299 CNGB3 54714 GNAT2 2780 TYRP1 7306 PRDM16 63976 GTF2E2 2961 CLRN1 7401 HPS6 79803 HARS 3035 BEST1 7439 CEP78 84131 IPW 3653 XPC 7508 HPS4 89781 KRAS 3845 MKRN3 7681 MPLKIP 136647 CBA MC1R 4157 RNF113A 7737 PWAR1 145624 MITF 4286 KCNAB2 8514 KCNV2 169522 SNORD115-1 338433 SLC6A19 340024 SLC24A5 283652 BLOC1S3 388552 GTF2H5 404672 PWRN1 791114 10003341 SNORD116-1 3 Genes with >= 6 ALB-HPO codes Gene Symbol Entrez Gene Symbol Entrez CACNA1F 778 ERCC5 2073 LYST 1130 MC1R 4157 ERCC2 2068 MITF 4286 ERCC3 2071 GPR143 4935 ERCC4 2072 OCA2 4948 SLC45A2 51151 TYR 7299 BLOC1S3 388552 CBA Genes with >= 8 ALB-HPO codes Gene Symbol Entrez MC1R 4157 OCA2 4948 TYR 7299 SLC45A2 51151 In order to maintain the specificity and not over expand the Disease Map of action only genes with >=6 ALB-HPO codes were selected. Location of the selected disease related genes in KEGG pathways to define the Disease Map of action. After locating the RD associated genes within KEGG pathways, a total of 17 circuits belonging to 8 KEGG pathways were found as part of the disease map. KEGG pathway KEGG-pathway code MAPK signaling pathway hsa04010 cGMP-PKG signaling pathway hsa04022 cAMP signaling pathway hsa04024 Serotonergic synapse hsa04726 GABAergic synapse hsa04727 Insulin secretion hsa04911 Melanogenesis hsa04916 Oxytocin signaling pathway hsa04921 HiPathia is a signal propagation algorithm that considers pathways as collections of circuits defined as sub-pathways or sequences of proteins connecting signal receptor proteins to effector proteins. HiPathia uses expression values genes as proxies of the level of activation of the corresponding protein in the circuit. Taking into account the inferred protein activity and the interactions between the proteins (activation or inhibition) defined in the pathway, the level of activity of a circuit is estimated using a signal propagation algorithm. Ultimately, effector proteins are annotated with a cellular function. CBA In order to enable a better visualization of the RD Map the HiPathia viewer has been used. The circuits that define the RD Map are marked in RED (please ignore the color legend). The pathways that contain these circuits are highlighted in the right window with a red arrow. The only purpose of this report is to represent the components (genes and interaction) and functions of the circuits that compose the RD Map. Click to access the RD Map Report Hipathia uses KEGG pathway for the graphical representation of the circuits. The original pathways can also be visualized in the KEGG repository https://www.genome.jp/kegg/pathway.html Select prefix: hsa (Organism) Enter keywords: e.g. FoxOsignalingpathway (any HiPathia pathway) Prediction of relevance of gene targets from approved drugs extracted from DRUGBANK database (release 5.1.4) The HoliRD approach takes the mechanistic model of the disease map as the proxy for the molecular basis of the disease outcome. Then, a Multi-Output Random Forest (MORF) regressor, a machine learning algorithm that predicts the circuit activities across the whole disease map, is trained on GTEx gene expression data to find proteins (which are targets for drugs with indications for other diseases) that correctly predict the behavior of the disease map. The drugs targeting the best predictor proteins are candidate for drug repurposing. The relevance score accounts for the accuracy of the prediction contributed by each individual protein. Relevance are absolute values and do not account for the direction of the prediction, that is, if the interaction is an activation or an inhibition. CBA From a total of 683 targets for approved drugs (AT) in the DRUGBANK database (release 5.1.4) the machine learning algorithm selected the 25 most relevant ones (top AT). Entrez Gene Symbol Relevance score Entrez Gene Symbol Relevance score 7299 TYR 0.2811105738 2100 ESR2 0.0065114645 3356 HTR2A 0.216515967 3757 KCNH2 0.0059683608 3357 HTR2B 0.1028354357 4137 MAPT 0.005070877 3778 KCNMA1 0.0546554091 776 CACNA1D 0.0049331 3849 KRT2 0.0458333973 6335 SCN9A 0.0043507735 50632 CALY 0.0178556769 2562 GABRB3 0.0036459506 4882 NPR2 0.0176289214 3274 HRH2 0.0035269408 9900 SV2A 0.0164550149 777 CACNA1E 0.0034067533 6324 SCN1B 0.0143180942 6262 RYR2 0.0032688947 291 SLC25A4 0.0135524337 6785 ELOVL4 0.0031980558 5535 PPP3R2 0.0084035268 6261 RYR1 0.0029505544 775 CACNA1C 0.0080491854 774 CACNA1B 0.0029303435 3358 HTR2C 0.007654728 Relevance plot depicting the 25 most relevant gene targets. CBA Drugs from DRUGBANK db (release 5.1.4) that target top AT. And the list of drugs that target the 25 most relevant genes follows: You can click on the hyperlink of the Drug ID to see more detailed information about the drug in DrugBank DB. Relevance Drug ID Drug Name Drug Effect Target Associated condition score DB00548 Azelaic acid inhibitor TYR Acne Vulgaris 0,28111 DB09526 Hydroquinone inhibitor TYR Melasma 0,28111 DB11217 Arbutin inhibitor TYR 0,28111 DB00246 Ziprasidone antagonist HTR2A Acute Agitation 0,21652 DB00247 Methysergide antagonist HTR2A 0,21652 DB00321 Amitriptyline antagonist HTR2A Acute Depression 0,21652 DB00334 Olanzapine antagonist HTR2A Acute Agitation 0,21652 DB00363 Clozapine antagonist HTR2A Suicidal Behaviour 0,21652 DB00370 Mirtazapine antagonist HTR2A Depressive illness 0,21652 DB00408 Loxapine antagonist HTR2A Acute Agitation 0,21652 DB00434 Cyproheptadine antagonist HTR2A Allergic Reactions 0,21652 Acute Intermittent DB00477 Chlorpromazine antagonist HTR2A 0,21652 Porphyria (AIP) Acute Depressive DB00540 Nortriptyline antagonist HTR2A 0,21652 Episode DB00589 Lisuride agonist HTR2A 0,21652 DB00656 Trazodone antagonist HTR2A Alcohol Dependence 0,21652 DB00696 Ergotamine agonist HTR2A Cluster Headache 0,21652 DB00734 Risperidone antagonist HTR2A Acute Mania 0,21652 DB00805 Minaprine antagonist HTR2A 0,21652 DB00924 Cyclobenzaprine antagonist HTR2A 0,21652 CBA DB00933 Mesoridazine antagonist HTR2A 0,21652 Anorexia Nervosa DB01151 Desipramine antagonist HTR2A 0,21652 (AN) Acute Depressive DB01224 Quetiapine antagonist HTR2A 0,21652 Episode DB01238
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