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Oculocutaneous Albinism

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 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 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 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 antagonist HTR2A Acute Agitation 0,21652

DB00247 antagonist HTR2A 0,21652

DB00321 antagonist HTR2A Acute Depression 0,21652

DB00334 antagonist HTR2A Acute Agitation 0,21652

DB00363 antagonist HTR2A Suicidal Behaviour 0,21652

DB00370 antagonist HTR2A Depressive illness 0,21652

DB00408 antagonist HTR2A Acute Agitation 0,21652

DB00434 antagonist HTR2A Allergic Reactions 0,21652

Acute Intermittent DB00477 antagonist HTR2A 0,21652 Porphyria (AIP)

Acute Depressive DB00540 antagonist HTR2A 0,21652 Episode

DB00589 HTR2A 0,21652

DB00656 antagonist HTR2A Dependence 0,21652

DB00696 agonist HTR2A Cluster Headache 0,21652

DB00734 antagonist HTR2A Acute Mania 0,21652

DB00805 Minaprine antagonist HTR2A 0,21652

DB00924 antagonist HTR2A 0,21652 CBA

DB00933 antagonist HTR2A 0,21652

Anorexia Nervosa DB01151 antagonist HTR2A 0,21652 (AN)

Acute Depressive DB01224 antagonist HTR2A 0,21652 Episode

DB01238 antagonist HTR2A Agitation 0,21652

DB01242 antagonist HTR2A Depression 0,21652

DB01267 antagonist HTR2A Delusional Parasitosis 0,21652

DB01621 antagonist HTR2A 0,21652

DB01623 Thiothixene antagonist HTR2A 0,21652

DB04908 antagonist HTR2A 0,21652

DB04946 antagonist HTR2A 0,21652

DB05316 inverse agonist HTR2A 0,21652

Mixed manic DB06016 antagonist HTR2A 0,21652 depressive episode

Mixed manic DB06216 antagonist HTR2A 0,21652 depressive episode

Acute Depressive DB08815 antagonist HTR2A 0,21652 Episode

DB09016 antagonist HTR2A 0,21652

Major Depressive DB09128 antagonist HTR2A 0,21652 Disorder (MDD)

DB09167 antagonist HTR2A 0,21652

DB09195 antagonist HTR2A 0,21652

Aripiprazole DB14185 antagonist HTR2A 0,21652 lauroxil

DB00247 Methysergide antagonist HTR2B 0,10284

DB00508 antagonist HTR2B 0,10284

DB00805 Minaprine antagonist HTR2B 0,10284 CBA

DB01242 Clomipramine antagonist HTR2B Depression 0,10284

Mixed manic DB06016 Cariprazine antagonist HTR2B 0,10284 depressive episode

DB00356 Chlorzoxazone KCNMA1 Pain 0,05466

Bendroflumethiazi DB00436 inducer KCNMA1 0,05466 de

Hydrochlorothiazi Acidosis, Renal DB00999 inhibitor KCNMA1 0,05466 de Tubular

DB01003 Cromoglicic acid inhibitor KCNMA1 Asthma 0,05466

Irritable Bowel DB09089 Trimebutine inhibitor KCNMA1 0,05466 Syndrome (IBS)

DB11157 Anthralin antagonist KRT2 0,04583

DB00831 antagonist CALY Agitation 0,01786

Erythrityl DB01613 agonist NPR2 0,01763 tetranitrate

DB01202 Levetiracetam agonist SV2A Epilepsies 0,01646

DB05541 Brivaracetam unknown SV2A 0,01646

DB00909 Zonisamide inhibitor SCN1B 0,01432

Hypercalcemia of DB00720 Clodronic acid inhibitor SLC25A4 0,01355 Malignancy

Atopic Dermatitis DB00091 Ciclosporin inhibitor PPP3R2 0,0084 (AD)

DB00270 Isradipine inhibitor CACNA1C 0,00805

DB00308 Ibutilide activator CACNA1C Atrial Fibrillation (AF) 0,00805

DB00343 Diltiazem blocker CACNA1C Anal Fissures 0,00805

DB00381 Amlodipine inhibitor CACNA1C Anginal Pain 0,00805

DB00393 Nimodipine inhibitor CACNA1C 0,00805

DB00401 Nisoldipine inhibitor CACNA1C 0,00805

DB00568 inhibitor CACNA1C 0,00805 CBA

Chronic Stable Angina DB00622 Nicardipine inhibitor CACNA1C 0,00805 Pectoris

DB00661 inhibitor CACNA1C Atrial Fibrillation (AF) 0,00805

DB00825 Levomenthol antagonist CACNA1C Coughing 0,00805

DB01023 Felodipine inhibitor CACNA1C 0,00805

DB01054 Nitrendipine inhibitor CACNA1C 0,00805

Chronic Stable Angina DB01115 Nifedipine inhibitor CACNA1C 0,00805 Pectoris

DB01373 Calcium CACNA1C 0,00805

DB06712 Nilvadipine inhibitor CACNA1C 0,00805

Irritable Bowel DB09089 Trimebutine inhibitor CACNA1C 0,00805 Syndrome (IBS)

DB09236 Lacidipine antagonist CACNA1C 0,00805

DB09238 blocker CACNA1C 0,00805

DB12278 Propiverine antagonist CACNA1C Micturition urgency 0,00805

DB00247 Methysergide antagonist HTR2C 0,00765

DB00434 Cyproheptadine antagonist HTR2C Allergic Reactions 0,00765

DB00589 Lisuride agonist HTR2C 0,00765

DB00656 Trazodone agonist HTR2C Alcohol Dependence 0,00765

DB00805 Minaprine antagonist HTR2C 0,00765

DB01242 Clomipramine antagonist HTR2C Depression 0,00765

DB01267 Paliperidone antagonist HTR2C Delusional Parasitosis 0,00765

DB06594 antagonist HTR2C 0,00765

DB09195 Lorpiprazole antagonist HTR2C 0,00765

DB00255 Diethylstilbestrol agonist ESR2 0,00651

Conjugated DB00286 agonist ESR2 Atrophic Vaginitis 0,00651 estrogens

DB00481 Raloxifene agonist ESR2 Breast Cancer 0,00651 CBA

Invasive Nos

antagonist,agon DB00675 Tamoxifen ESR2 Breast Cancer 0,00651 ist

DB00783 Estradiol agonist ESR2 Atrophic Vaginitis 0,00651

DB01196 Estramustine other/unknown ESR2 0,00651

DB06202 Lasofoxifene agonist ESR2 0,00651

Moderate DB13952 Estradiol acetate agonist ESR2 Menopausal 0,00651 Vasomotor Symptoms

DB13953 Estradiol benzoate agonist ESR2 0,00651

Estradiol DB13954 agonist ESR2 Estrogen Deficiency 0,00651 cypionate

Estradiol DB13955 agonist ESR2 0,00651 dienanthate

DB13956 Estradiol valerate agonist ESR2 Estrogen Deficiency 0,00651

Symptomatic Atrial DB00204 Dofetilide inhibitor KCNH2 0,00597 flutter

DB00308 Ibutilide inhibitor KCNH2 Atrial Fibrillation (AF) 0,00597

DB00489 inhibitor KCNH2 Atrial Fibrillation (AF) 0,00597

DB01100 inhibitor KCNH2 Delusional Parasitosis 0,00597

DB01118 Amiodarone inhibitor KCNH2 Atrial Fibrillation (AF) 0,00597

DB01182 inhibitor KCNH2 Atrial Fibrillation (AF) 0,00597

DB01218 Halofantrine inhibitor KCNH2 0,00597

Advanced Cervical DB01229 Paclitaxel MAPT 0,00507 Cancer

DB01248 Docetaxel MAPT Esophageal Cancers 0,00507

DB00270 Isradipine inhibitor CACNA1D 0,00493

DB00393 Nimodipine inhibitor CACNA1D 0,00493

DB00401 Nisoldipine inhibitor CACNA1D 0,00493 CBA

DB00568 Cinnarizine inhibitor CACNA1D 0,00493

Chronic Stable Angina DB00622 Nicardipine inhibitor CACNA1D 0,00493 Pectoris

DB00661 Verapamil inhibitor CACNA1D Atrial Fibrillation (AF) 0,00493

DB01023 Felodipine inhibitor CACNA1D 0,00493

DB01054 Nitrendipine inhibitor CACNA1D 0,00493

Chronic Stable Angina DB01115 Nifedipine inhibitor CACNA1D 0,00493 Pectoris

Postherpetic DB00281 Lidocaine inhibitor SCN9A 0,00435 Neuralgia

DB00909 Zonisamide inhibitor SCN9A 0,00435

DB00231 Temazepam potentiator GABRB3 0,00365

DB00592 agonist GABRB3 0,00365

DB00690 Flurazepam potentiator GABRB3 0,00365

DB00818 Propofol potentiator GABRB3 0,00365

Alcohol Withdrawal DB00829 potentiator GABRB3 0,00365 Syndrome(AWS)

Alcohol Withdrawal DB00842 potentiator GABRB3 0,00365 Syndrome(AWS)

DB00897 Triazolam potentiator GABRB3 0,00365

DB01215 Estazolam potentiator GABRB3 0,00365

DB01558 potentiator GABRB3 Acute Anxiety 0,00365

DB01559 potentiator GABRB3 0,00365

DB01588 potentiator GABRB3 0,00365

DB01589 Quazepam potentiator GABRB3 0,00365

DB01595 Nitrazepam potentiator GABRB3 Insomnia 0,00365

DB06716 Fospropofol potentiator GABRB3 0,00365

DB00272 agonist HRH2 0,00353 CBA

Gastro-esophageal DB00501 antagonist HRH2 0,00353 Reflux Disease (GERD)

Bacterial Infection DB00585 antagonist HRH2 Due to Helicobacter 0,00353 Pylori (H. Pylori)

DB00751 antagonist HRH2 0,00353

Ankylosing Spondylitis DB00863 antagonist HRH2 0,00353 (AS)

Bacterial Infection DB00927 antagonist HRH2 Due to Helicobacter 0,00353 Pylori (H. Pylori)

DB00940 Methantheline antagonist HRH2 0,00353

DB01142 antagonist HRH2 Anxiety 0,00353

DB05381 agonist HRH2 0,00353

Acute Bipolar DB00555 Lamotrigine inhibitor CACNA1E 0,00341 Depression

DB09085 Tetracaine modulator RYR2 0,00327

Omega-3-carboxyl DB09568 potentiator ELOVL4 0,0032 ic acids

Malignant DB01219 Dantrolene antagonist RYR1 0,00295 Hyperthermia

DB09085 Tetracaine modulator RYR1 0,00295

DB00996 inhibitor CACNA1B Partial-Onset Seizures 0,00293

DB01202 Levetiracetam inhibitor CACNA1B Epilepsies 0,00293 CBA

Location of top AT in HiPathia circuits and selection of those circuits shared with the Disease Map. A total of 14/17 circuits containing top AT are shown.

Disease Map circuits with top AT

HiPathia pathway: Effector gene HiPathia pathway: Effector gene MAPK signaling pathway: ATF4* cAMP signaling pathway: CACNA1C

MAPK signaling pathway: FOS Serotonergic synapse: CACNA1C

MAPK signaling pathway: MAPT GABAergic synapse: CACNA1A*

MAPK signaling pathway: STMN1 Insulin secretion: CACNA1C

MAPK signaling pathway: PLA2G4B Melanogenesis: TYR*

MAPK signaling pathway: MYC Melanogenesis: TYR

cGMP-PKG signaling pathway: CACNA1C Oxytocin signaling pathway: CACNG3

Matrix correlation of the expression of top AT with the activity of the circuits that compose the RD Map.

In order to understand the nature of the interaction (activation or inhibition) between the most relevant targets and the circuits of the disease map a correlation plot was derived. The plot represents the correlation between the expression level of the most relevant targets and the activity levels of the circuits in the disease map inferred by HiPathia across the GTEx data set. Additionally, the top of the figure represents the effect (pharmacological action) of the drugs.

Hint: a drug with an inhibitory effect in a given target will potentially produce an inhibitory effect in circuits positively correlated (and, it is likely that activation in circuits negatively correlated with the target.)

Click to access and download the Correlation Matrix

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