Integrated epigenomic exposure signature discovery

Jared Schuetter; Angela Minard-Smith; Brandon Hill; Jennifer L. Beare; Alexandria Vornholt; Thomas W. Burke; Vel Murugan; Anthony K. Smith; Thiruppavai Chandrasekaran; Hiba J. Shamma; Sarah C. Kahaian; Keegan L. Fillinger; Mary Anne S Amper; Wan Sze Cheng; Yongchao Ge; Mary Catherine George; Kristy Guevara; Nora Lovette-Okwara; Avinash Mahajan; Nada Marjanovic; Natalia Mendelev; Vance G. Fowler; Micah T. McClain; Clare M. Miller; Sagie Mofsowitz; Venugopalan D. Nair; German Nudelman; Thomas G. Evans; Flora Castellino; Irene Ramos; Stas Rirak; Frederique Ruf-Zamojski; Nitish Seenarine; Alessandra Soares-Shanoski; Sindhu Vangeti; Mital Vasoya; Xuechen Yu; Elena Zaslavsky; Lishomwa C. Ndhlovu; Michael J. Corley; Scott Bowler; Steven G. Deeks; Andrew G. Letizia; Stuart C. Sealfon; Christopher W. Woods; Rachel R. Spurbeck

doi:10.1080/17501911.2024.2375187

Integrated epigenomic exposure signature discovery

Jared Schuetter, Angela Minard-Smith, Brandon Hill, Jennifer L. Beare, Alexandria Vornholt, Thomas W. Burke, Vel Murugan, Anthony K. Smith, Thiruppavai Chandrasekaran, Hiba J. Shamma, Sarah C. Kahaian, Keegan L. Fillinger, Mary Anne S Amper, Wan Sze Cheng, Yongchao Ge, Mary Catherine George, Kristy Guevara, Nora Lovette-Okwara, Avinash Mahajan, Nada MarjanovicNatalia Mendelev, Vance G. Fowler, Micah T. McClain, Clare M. Miller, Sagie Mofsowitz, Venugopalan D. Nair, German Nudelman, Thomas G. Evans, Flora Castellino, Irene Ramos, Stas Rirak, Frederique Ruf-Zamojski, Nitish Seenarine, Alessandra Soares-Shanoski, Sindhu Vangeti, Mital Vasoya, Xuechen Yu, Elena Zaslavsky, Lishomwa C. Ndhlovu, Michael J. Corley, Scott Bowler, Steven G. Deeks, Andrew G. Letizia, Stuart C. Sealfon, Christopher W. Woods, Rachel R. Spurbeck

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

Aim: The epigenome influences gene regulation and phenotypes in response to exposures. Epigenome assessment can determine exposure history aiding in diagnosis. Materials & methods: Here we developed and implemented a machine learning algorithm, the exposure signature discovery algorithm (ESDA), to identify the most important features present in multiple epigenomic and transcriptomic datasets to produce an integrated exposure signature (ES). Results: Signatures were developed for seven exposures including Staphylococcus aureus, human immunodeficiency virus, SARS-CoV-2, influenza A (H3N2) virus and Bacillus anthracis vaccinations. ESs differed in the assays and features selected and predictive value. Conclusion: Integrated ESs can potentially be utilized for diagnosis or forensic attribution. The ESDA identifies the most distinguishing features enabling diagnostic panel development for future precision health deployment.

Original language	English
Journal	Epigenomics
DOIs	https://doi.org/10.1080/17501911.2024.2375187
State	Accepted/In press - 2024

Keywords

diagnostics
epigenomics
exposure health
infection
machine learning
multi-omics
transcriptomics

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10.1080/17501911.2024.2375187

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Schuetter, J., Minard-Smith, A., Hill, B., Beare, J. L., Vornholt, A., Burke, T. W., Murugan, V., Smith, A. K., Chandrasekaran, T., Shamma, H. J., Kahaian, S. C., Fillinger, K. L., S Amper, M. A., Cheng, W. S., Ge, Y., George, M. C., Guevara, K., Lovette-Okwara, N., Mahajan, A., ... Spurbeck, R. R. (Accepted/In press). Integrated epigenomic exposure signature discovery. Epigenomics. https://doi.org/10.1080/17501911.2024.2375187

@article{41ce2b810010430390e9afaceb77b86f,

title = "Integrated epigenomic exposure signature discovery",

abstract = "Aim: The epigenome influences gene regulation and phenotypes in response to exposures. Epigenome assessment can determine exposure history aiding in diagnosis. Materials & methods: Here we developed and implemented a machine learning algorithm, the exposure signature discovery algorithm (ESDA), to identify the most important features present in multiple epigenomic and transcriptomic datasets to produce an integrated exposure signature (ES). Results: Signatures were developed for seven exposures including Staphylococcus aureus, human immunodeficiency virus, SARS-CoV-2, influenza A (H3N2) virus and Bacillus anthracis vaccinations. ESs differed in the assays and features selected and predictive value. Conclusion: Integrated ESs can potentially be utilized for diagnosis or forensic attribution. The ESDA identifies the most distinguishing features enabling diagnostic panel development for future precision health deployment.",

keywords = "diagnostics, epigenomics, exposure health, infection, machine learning, multi-omics, transcriptomics",

author = "Jared Schuetter and Angela Minard-Smith and Brandon Hill and Beare, {Jennifer L.} and Alexandria Vornholt and Burke, {Thomas W.} and Vel Murugan and Smith, {Anthony K.} and Thiruppavai Chandrasekaran and Shamma, {Hiba J.} and Kahaian, {Sarah C.} and Fillinger, {Keegan L.} and {S Amper}, {Mary Anne} and Cheng, {Wan Sze} and Yongchao Ge and George, {Mary Catherine} and Kristy Guevara and Nora Lovette-Okwara and Avinash Mahajan and Nada Marjanovic and Natalia Mendelev and Fowler, {Vance G.} and McClain, {Micah T.} and Miller, {Clare M.} and Sagie Mofsowitz and Nair, {Venugopalan D.} and German Nudelman and Evans, {Thomas G.} and Flora Castellino and Irene Ramos and Stas Rirak and Frederique Ruf-Zamojski and Nitish Seenarine and Alessandra Soares-Shanoski and Sindhu Vangeti and Mital Vasoya and Xuechen Yu and Elena Zaslavsky and Ndhlovu, {Lishomwa C.} and Corley, {Michael J.} and Scott Bowler and Deeks, {Steven G.} and Letizia, {Andrew G.} and Sealfon, {Stuart C.} and Woods, {Christopher W.} and Spurbeck, {Rachel R.}",

note = "Publisher Copyright: {\textcopyright} 2024 Battelle Memorial Institute. Published by Informa UK Limited, trading as Taylor & Francis Group.",

year = "2024",

doi = "10.1080/17501911.2024.2375187",

language = "English",

journal = "Epigenomics",

issn = "1750-1911",

publisher = "Taylor and Francis Ltd.",

}

Schuetter, J, Minard-Smith, A, Hill, B, Beare, JL, Vornholt, A, Burke, TW, Murugan, V, Smith, AK, Chandrasekaran, T, Shamma, HJ, Kahaian, SC, Fillinger, KL, S Amper, MA, Cheng, WS, Ge, Y, George, MC, Guevara, K, Lovette-Okwara, N, Mahajan, A, Marjanovic, N, Mendelev, N, Fowler, VG, McClain, MT, Miller, CM, Mofsowitz, S, Nair, VD, Nudelman, G, Evans, TG, Castellino, F, Ramos, I, Rirak, S, Ruf-Zamojski, F, Seenarine, N, Soares-Shanoski, A, Vangeti, S, Vasoya, M, Yu, X, Zaslavsky, E, Ndhlovu, LC, Corley, MJ, Bowler, S, Deeks, SG, Letizia, AG, Sealfon, SC, Woods, CW & Spurbeck, RR 2024, 'Integrated epigenomic exposure signature discovery', Epigenomics. https://doi.org/10.1080/17501911.2024.2375187

TY - JOUR

T1 - Integrated epigenomic exposure signature discovery

AU - Schuetter, Jared

AU - Minard-Smith, Angela

AU - Hill, Brandon

AU - Beare, Jennifer L.

AU - Vornholt, Alexandria

AU - Burke, Thomas W.

AU - Murugan, Vel

AU - Smith, Anthony K.

AU - Chandrasekaran, Thiruppavai

AU - Shamma, Hiba J.

AU - Kahaian, Sarah C.

AU - Fillinger, Keegan L.

AU - S Amper, Mary Anne

AU - Cheng, Wan Sze

AU - Ge, Yongchao

AU - George, Mary Catherine

AU - Guevara, Kristy

AU - Lovette-Okwara, Nora

AU - Mahajan, Avinash

AU - Marjanovic, Nada

AU - Mendelev, Natalia

AU - Fowler, Vance G.

AU - McClain, Micah T.

AU - Miller, Clare M.

AU - Mofsowitz, Sagie

AU - Nair, Venugopalan D.

AU - Nudelman, German

AU - Evans, Thomas G.

AU - Castellino, Flora

AU - Ramos, Irene

AU - Rirak, Stas

AU - Ruf-Zamojski, Frederique

AU - Seenarine, Nitish

AU - Soares-Shanoski, Alessandra

AU - Vangeti, Sindhu

AU - Vasoya, Mital

AU - Yu, Xuechen

AU - Zaslavsky, Elena

AU - Ndhlovu, Lishomwa C.

AU - Corley, Michael J.

AU - Bowler, Scott

AU - Deeks, Steven G.

AU - Letizia, Andrew G.

AU - Sealfon, Stuart C.

AU - Woods, Christopher W.

AU - Spurbeck, Rachel R.

PY - 2024

Y1 - 2024

N2 - Aim: The epigenome influences gene regulation and phenotypes in response to exposures. Epigenome assessment can determine exposure history aiding in diagnosis. Materials & methods: Here we developed and implemented a machine learning algorithm, the exposure signature discovery algorithm (ESDA), to identify the most important features present in multiple epigenomic and transcriptomic datasets to produce an integrated exposure signature (ES). Results: Signatures were developed for seven exposures including Staphylococcus aureus, human immunodeficiency virus, SARS-CoV-2, influenza A (H3N2) virus and Bacillus anthracis vaccinations. ESs differed in the assays and features selected and predictive value. Conclusion: Integrated ESs can potentially be utilized for diagnosis or forensic attribution. The ESDA identifies the most distinguishing features enabling diagnostic panel development for future precision health deployment.

AB - Aim: The epigenome influences gene regulation and phenotypes in response to exposures. Epigenome assessment can determine exposure history aiding in diagnosis. Materials & methods: Here we developed and implemented a machine learning algorithm, the exposure signature discovery algorithm (ESDA), to identify the most important features present in multiple epigenomic and transcriptomic datasets to produce an integrated exposure signature (ES). Results: Signatures were developed for seven exposures including Staphylococcus aureus, human immunodeficiency virus, SARS-CoV-2, influenza A (H3N2) virus and Bacillus anthracis vaccinations. ESs differed in the assays and features selected and predictive value. Conclusion: Integrated ESs can potentially be utilized for diagnosis or forensic attribution. The ESDA identifies the most distinguishing features enabling diagnostic panel development for future precision health deployment.

KW - diagnostics

KW - epigenomics

KW - exposure health

KW - infection

KW - machine learning

KW - multi-omics

KW - transcriptomics

UR - http://www.scopus.com/inward/record.url?scp=85203018679&partnerID=8YFLogxK

U2 - 10.1080/17501911.2024.2375187

DO - 10.1080/17501911.2024.2375187

M3 - Article

AN - SCOPUS:85203018679

SN - 1750-1911

JO - Epigenomics

JF - Epigenomics

ER -

Integrated epigenomic exposure signature discovery

Abstract

Keywords

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