Mapping exposome derived phenotypes into SNOMED codes

Christopher Hawthorne; Luis Marco Ruiz; Guillermo Lopez Campos

doi:10.3233/SHTI230351

Mapping exposome derived phenotypes into SNOMED codes

Christopher Hawthorne, Luis Marco Ruiz, Guillermo Lopez Campos

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Abstract

Human phenotypes define the healthy or diseased status of an individual and they arise from the complex interactions between environmental and genetic factors. The whole set of human exposures constitute the human exposome. These exposures have multiple sources including physical and socioeconomic factors. In this manuscript we have used text mining techniques to retrieve 1295 and 1903 Human Phenotype Ontology terms associated with these exposome factors and we have subsequently mapped 83% and 90% of the HPO terms respectively) into SNOMED as a clinically actionable code. We have developed a proof-of-concept approach to facilitate the integration of exposomic and clinical data.

Original language	English
Title of host publication	Proceedings of MIE 2023: Caring is Sharing – Exploiting the Value in Data for Health and Innovation
Editors	M. Hägglund
Publisher	IOS Press
Pages	1073-1074
Number of pages	2
Volume	302
ISBN (Electronic)	9781643683898
ISBN (Print)	9781643683881
DOIs	https://doi.org/10.3233/SHTI230351
Publication status	Published - 18 May 2023
Event	The 33rd Medical Informatics Europe Conference, MIE2023 - Gothenburg, Sweden Duration: 22 May 2023 → 25 May 2023

Publication series

Name	Studies in Health Technology and Informatics
Publisher	IOS Press
Volume	302
ISSN (Print)	0926-9630
ISSN (Electronic)	1879-8365

Conference

Conference	The 33rd Medical Informatics Europe Conference, MIE2023
Country/Territory	Sweden
City	Gothenburg
Period	22/05/2023 → 25/05/2023

Keywords

Bioinformatics
SNOMED-CT
Systematized Nomenclature of Medicine
Phenotype
Humans
Exposome
Human Phenotype Ontology
precision medicine

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.3233/SHTI230351Licence: CC BY-NC

Mapping exposome derived phenotypes into SNOMED codes
Copyright 2023 European Federation for Medical Informatics (EFMI) and IOS Press. This is an open access Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits use, distribution and reproduction for non-commercial purposes, provided the author and source are cited.
Final published version, 117 KBLicence: CC BY-NC

Investigation and development of novel exposome informatics methodologies and solutions for the analysis and integration of phenome, genome and exposome data
Hawthorne, C. (Author), Lopez Campos, G. (Supervisor), Simpson, D. (Supervisor) & Devereux, B. (Supervisor), Dec 2023
Student thesis: Doctoral Thesis › Doctor of Philosophy

Cite this

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title = "Mapping exposome derived phenotypes into SNOMED codes",

abstract = "Human phenotypes define the healthy or diseased status of an individual and they arise from the complex interactions between environmental and genetic factors. The whole set of human exposures constitute the human exposome. These exposures have multiple sources including physical and socioeconomic factors. In this manuscript we have used text mining techniques to retrieve 1295 and 1903 Human Phenotype Ontology terms associated with these exposome factors and we have subsequently mapped 83% and 90% of the HPO terms respectively) into SNOMED as a clinically actionable code. We have developed a proof-of-concept approach to facilitate the integration of exposomic and clinical data.",

keywords = "Bioinformatics, SNOMED-CT, Systematized Nomenclature of Medicine, Phenotype, Humans, Exposome, Human Phenotype Ontology, precision medicine",

author = "Christopher Hawthorne and {Marco Ruiz}, Luis and {Lopez Campos}, Guillermo",

year = "2023",

month = may,

day = "18",

doi = "10.3233/SHTI230351",

language = "English",

isbn = "9781643683881",

volume = "302",

series = "Studies in Health Technology and Informatics",

publisher = "IOS Press",

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editor = "H{\"a}gglund, {M. }",

booktitle = "Proceedings of MIE 2023: Caring is Sharing – Exploiting the Value in Data for Health and Innovation",

address = "Netherlands",

note = "The 33rd Medical Informatics Europe Conference, MIE2023 ; Conference date: 22-05-2023 Through 25-05-2023",

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Hawthorne, C, Marco Ruiz, L & Lopez Campos, G 2023, Mapping exposome derived phenotypes into SNOMED codes. in M Hägglund (ed.), Proceedings of MIE 2023: Caring is Sharing – Exploiting the Value in Data for Health and Innovation. vol. 302, Studies in Health Technology and Informatics, vol. 302, IOS Press, pp. 1073-1074, The 33rd Medical Informatics Europe Conference, MIE2023, Gothenburg, Sweden, 22/05/2023. https://doi.org/10.3233/SHTI230351

Mapping exposome derived phenotypes into SNOMED codes. / Hawthorne, Christopher; Marco Ruiz, Luis; Lopez Campos, Guillermo.
Proceedings of MIE 2023: Caring is Sharing – Exploiting the Value in Data for Health and Innovation. ed. / M. Hägglund. Vol. 302 IOS Press, 2023. p. 1073-1074 (Studies in Health Technology and Informatics; Vol. 302).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - Mapping exposome derived phenotypes into SNOMED codes

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AU - Marco Ruiz, Luis

AU - Lopez Campos, Guillermo

PY - 2023/5/18

Y1 - 2023/5/18

N2 - Human phenotypes define the healthy or diseased status of an individual and they arise from the complex interactions between environmental and genetic factors. The whole set of human exposures constitute the human exposome. These exposures have multiple sources including physical and socioeconomic factors. In this manuscript we have used text mining techniques to retrieve 1295 and 1903 Human Phenotype Ontology terms associated with these exposome factors and we have subsequently mapped 83% and 90% of the HPO terms respectively) into SNOMED as a clinically actionable code. We have developed a proof-of-concept approach to facilitate the integration of exposomic and clinical data.

AB - Human phenotypes define the healthy or diseased status of an individual and they arise from the complex interactions between environmental and genetic factors. The whole set of human exposures constitute the human exposome. These exposures have multiple sources including physical and socioeconomic factors. In this manuscript we have used text mining techniques to retrieve 1295 and 1903 Human Phenotype Ontology terms associated with these exposome factors and we have subsequently mapped 83% and 90% of the HPO terms respectively) into SNOMED as a clinically actionable code. We have developed a proof-of-concept approach to facilitate the integration of exposomic and clinical data.

KW - Bioinformatics

KW - SNOMED-CT

KW - Systematized Nomenclature of Medicine

KW - Phenotype

KW - Humans

KW - Exposome

KW - Human Phenotype Ontology

KW - precision medicine

U2 - 10.3233/SHTI230351

DO - 10.3233/SHTI230351

M3 - Conference contribution

C2 - 37203585

SN - 9781643683881

VL - 302

T3 - Studies in Health Technology and Informatics

SP - 1073

EP - 1074

BT - Proceedings of MIE 2023: Caring is Sharing – Exploiting the Value in Data for Health and Innovation

A2 - Hägglund, M.

PB - IOS Press

T2 - The 33rd Medical Informatics Europe Conference, MIE2023

Y2 - 22 May 2023 through 25 May 2023

ER -

Mapping exposome derived phenotypes into SNOMED codes

Abstract

Publication series

Conference

Keywords

UN SDGs

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Student theses

Investigation and development of novel exposome informatics methodologies and solutions for the analysis and integration of phenome, genome and exposome data

Cite this