Omics feature selection with the extended SIS R package: identification of a body mass index epigenetic multimarker in the Strong Heart Study

[EN] The statistical analysis of omics data poses a great computational challenge given its ultra-high dimensional nature and frequent between-features correlation. In this work, we extended the Iterative Sure Independence Screening (ISIS) algorithm by pairing ISIS with elastic-net (Enet) and two ve...

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Authors: Domingo-Relloso, Arce, Feng, Yang, Rodríguez-Hernández, Zulema, Haack, Karin, Cole, Shelley A., Navas-Acien, Ana, Tellez-Plaza, Maria, Bermudez, Jose D.
Format: article
Publication Date:2024
Country:España
Institution:Universitat Politècnica de València (UPV)
Repository:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Language:English
OAI Identifier:oai:riunet.upv.es:10251/220571
Online Access:https://riunet.upv.es/handle/10251/220571
Access Level:Open access
Keyword:DNA methylation
Feature selection
Sure independence screening
Dimensionality reduction
Omics data
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network_name_str España
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dc.title.none.fl_str_mv Omics feature selection with the extended SIS R package: identification of a body mass index epigenetic multimarker in the Strong Heart Study
title Omics feature selection with the extended SIS R package: identification of a body mass index epigenetic multimarker in the Strong Heart Study
spellingShingle Omics feature selection with the extended SIS R package: identification of a body mass index epigenetic multimarker in the Strong Heart Study
Domingo-Relloso, Arce
DNA methylation
Feature selection
Sure independence screening
Dimensionality reduction
Omics data
title_short Omics feature selection with the extended SIS R package: identification of a body mass index epigenetic multimarker in the Strong Heart Study
title_full Omics feature selection with the extended SIS R package: identification of a body mass index epigenetic multimarker in the Strong Heart Study
title_fullStr Omics feature selection with the extended SIS R package: identification of a body mass index epigenetic multimarker in the Strong Heart Study
title_full_unstemmed Omics feature selection with the extended SIS R package: identification of a body mass index epigenetic multimarker in the Strong Heart Study
title_sort Omics feature selection with the extended SIS R package: identification of a body mass index epigenetic multimarker in the Strong Heart Study
dc.creator.none.fl_str_mv Domingo-Relloso, Arce
Feng, Yang
Rodríguez-Hernández, Zulema
Haack, Karin
Cole, Shelley A.
Navas-Acien, Ana
Tellez-Plaza, Maria
Bermudez, Jose D.
author Domingo-Relloso, Arce
author_facet Domingo-Relloso, Arce
Feng, Yang
Rodríguez-Hernández, Zulema
Haack, Karin
Cole, Shelley A.
Navas-Acien, Ana
Tellez-Plaza, Maria
Bermudez, Jose D.
author_role author
author2 Feng, Yang
Rodríguez-Hernández, Zulema
Haack, Karin
Cole, Shelley A.
Navas-Acien, Ana
Tellez-Plaza, Maria
Bermudez, Jose D.
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Instituto de Salud Carlos III
Agencia Estatal de Investigación
National Heart, Lung, and Blood Institute, EEUU
National Institute of Environmental Health Sciences
Fundació Bancària Caixa d'Estalvis i Pensions de Barcelona
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv DNA methylation
Feature selection
Sure independence screening
Dimensionality reduction
Omics data
topic DNA methylation
Feature selection
Sure independence screening
Dimensionality reduction
Omics data
description [EN] The statistical analysis of omics data poses a great computational challenge given its ultra-high dimensional nature and frequent between-features correlation. In this work, we extended the Iterative Sure Independence Screening (ISIS) algorithm by pairing ISIS with elastic-net (Enet) and two versions of adaptive Enet (AEnet and MSAEnet) to efficiently improve feature selection and effect estimation in omics research. We subsequently used genome-wide human blood DNA methylation data from American Indians of the Strong Heart Study (N=2,235 participants), measured in 1989-1991, to compare the performance (predictive accuracy, coefficient estimation and computational efficiency) of SIS-paired regularization methods to Bayesian shrinkage and traditional linear regression to identify epigenomic multi-marker of body mass index. ISIS-AEnet outperformed the other methods in prediction. In biological pathway enrichment analysis of genes annotated to BMI-related differentially methylated positions, ISIS-AEnet captured most of the enriched pathways in common for at least two of all the evaluated methods. ISIS-AEnet can favor biological discovery because it identifies the most robust biological pathways while achieving an optimal balance between bias and efficient feature selection. In the extended SIS R package, we also implemented ISIS paired with Cox and logistic regression for time-to-event and binary endpoints, respectively, and bootstrap confidence intervals for the estimated regression coefficients.
publishDate 2024
dc.date.none.fl_str_mv 2024
2024-05-05
dc.type.none.fl_str_mv journal article
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dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/220571
url https://riunet.upv.es/handle/10251/220571
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Agencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020 PID2019-108973RB-C21 ESTUDIO DE ALEATORIZACION MENDELIANA DEL SELENIO Y FACTORES RELACIONADOS CON LA DIABETES: UN ENFOQUE INTEGRADOR
Instituto de Salud Carlos III https://doi.org/10.13039/501100004587 PI15%2F00071
National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 75N92019D00027
National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 75N92019D00028
National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 75N92019D00029
National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 75N92019D00030
National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 R01HL109315
National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 R01HL109284
National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 U01HL65521
National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 U01HL41642
National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 U01HL41652
National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 U01HL41654
National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 U01HL65520
National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 R01HL090863
National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 R01HL109301
National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 R01HL109282
National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 R01HL109319
Fundació Bancària Caixa d'Estalvis i Pensions de Barcelona Fundació Bancària Caixa d'Estalvis i Pensions de Barcelona LCF%2FBQ%2FDR19%2F11740016
NIEHS NIEHS P30ES009089
NIEHS NIEHS R01ES021367
NIEHS NIEHS R01ES025216
NIEHS NIEHS P42ES033719
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reserva de todos los derechos
http://rightsstatements.org/vocab/InC/1.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reserva de todos los derechos
http://rightsstatements.org/vocab/InC/1.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Oxford University Press
publisher.none.fl_str_mv Oxford University Press
dc.source.none.fl_str_mv reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
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spelling Omics feature selection with the extended SIS R package: identification of a body mass index epigenetic multimarker in the Strong Heart StudyDomingo-Relloso, ArceFeng, YangRodríguez-Hernández, ZulemaHaack, KarinCole, Shelley A.Navas-Acien, AnaTellez-Plaza, MariaBermudez, Jose D.DNA methylationFeature selectionSure independence screeningDimensionality reductionOmics data[EN] The statistical analysis of omics data poses a great computational challenge given its ultra-high dimensional nature and frequent between-features correlation. In this work, we extended the Iterative Sure Independence Screening (ISIS) algorithm by pairing ISIS with elastic-net (Enet) and two versions of adaptive Enet (AEnet and MSAEnet) to efficiently improve feature selection and effect estimation in omics research. We subsequently used genome-wide human blood DNA methylation data from American Indians of the Strong Heart Study (N=2,235 participants), measured in 1989-1991, to compare the performance (predictive accuracy, coefficient estimation and computational efficiency) of SIS-paired regularization methods to Bayesian shrinkage and traditional linear regression to identify epigenomic multi-marker of body mass index. ISIS-AEnet outperformed the other methods in prediction. In biological pathway enrichment analysis of genes annotated to BMI-related differentially methylated positions, ISIS-AEnet captured most of the enriched pathways in common for at least two of all the evaluated methods. ISIS-AEnet can favor biological discovery because it identifies the most robust biological pathways while achieving an optimal balance between bias and efficient feature selection. In the extended SIS R package, we also implemented ISIS paired with Cox and logistic regression for time-to-event and binary endpoints, respectively, and bootstrap confidence intervals for the estimated regression coefficients.The Strong Heart Study is funded by grants from the National Heart, Lung, and Blood Institute (NHLBI) (contracts 75N92019D00027, 75N92019D00028, 75N92019D00029, and 75N92019D00030) and previous NHLBI grants (R01HL090863, R01HL109315, R01HL109301, R01HL109284, R01HL109282, and R01HL109319) and cooperative agreements (U01HL41642, U01HL41652, U01HL41654, U01HL65520, and U01HL65521) and by the National Institute of Environmental Health Sciences (grants R01ES021367, R01ES025216, P42ES033719, and P30ES009089). A.D.-R. was supported by a fellowship from the "la Caixa" Foundation (ID100010434; fellowship code LCF/BQ/DR19/11740016). M.T.-P. was supported by Strategic Action for Research in Health Sciences (grant PI15/00071), an initiative from the Instituto de Salud Carlos III and the Spanish Ministry of Science and Innovation and co funded by the European Funds for Regional Development, the Third AstraZeneca Award for Spanish Young Researchers, and the State Agency for Research (grant PID2019-108973RB-C21).Oxford University PressInstituto de Salud Carlos IIIAgencia Estatal de InvestigaciónNational Heart, Lung, and Blood Institute, EEUUNational Institute of Environmental Health SciencesFundació Bancària Caixa d'Estalvis i Pensions de BarcelonaRepositorio Institucional de la Universitat Politècnica de València Riunet20242024-05-05journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfapplication/pdfhttps://riunet.upv.es/handle/10251/220571reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)InglésengAgencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020 PID2019-108973RB-C21 ESTUDIO DE ALEATORIZACION MENDELIANA DEL SELENIO Y FACTORES RELACIONADOS CON LA DIABETES: UN ENFOQUE INTEGRADORInstituto de Salud Carlos III https://doi.org/10.13039/501100004587 PI15%2F00071National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 75N92019D00027National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 75N92019D00028National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 75N92019D00029National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 75N92019D00030National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 R01HL109315National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 R01HL109284National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 U01HL65521National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 U01HL41642National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 U01HL41652National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 U01HL41654National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 U01HL65520National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 R01HL090863National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 R01HL109301National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 R01HL109282National Heart, Lung, and Blood Institute, EEUU https://doi.org/10.13039/100000050 R01HL109319Fundació Bancària Caixa d'Estalvis i Pensions de Barcelona Fundació Bancària Caixa d'Estalvis i Pensions de Barcelona LCF%2FBQ%2FDR19%2F11740016NIEHS NIEHS P30ES009089NIEHS NIEHS R01ES021367NIEHS NIEHS R01ES025216NIEHS NIEHS P42ES033719open accesshttp://purl.org/coar/access_right/c_abf2Reserva de todos los derechoshttp://rightsstatements.org/vocab/InC/1.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/2205712026-06-13T07:49:27Z
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