Integration of microarray data and literature mining identifies a sex bias in DPP4+CD4+ T cells in HIV-1 infection

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Integration of microarray data and literature mining identifies a sex bias in DPP4+CD4+ T cells in HIV-1 infection. / Stubbe, Hans Christian; Dahlke, Christine; Rotheneder, Katharina; Stirner, Renate; Roider, Julia; Conca, Raffaele; Seybold, Ulrich; Bogner, Johannes; Addo, Marylyn Martina; Draenert, Rika.

in: PLOS ONE, Jahrgang 15, Nr. 9, 2020, S. e0239399.

Publikationen: SCORING: Beitrag in Fachzeitschrift/ZeitungSCORING: ZeitschriftenaufsatzForschungBegutachtung

Harvard

Stubbe, HC, Dahlke, C, Rotheneder, K, Stirner, R, Roider, J, Conca, R, Seybold, U, Bogner, J, Addo, MM & Draenert, R 2020, 'Integration of microarray data and literature mining identifies a sex bias in DPP4+CD4+ T cells in HIV-1 infection', PLOS ONE, Jg. 15, Nr. 9, S. e0239399. https://doi.org/10.1371/journal.pone.0239399

APA

Stubbe, H. C., Dahlke, C., Rotheneder, K., Stirner, R., Roider, J., Conca, R., Seybold, U., Bogner, J., Addo, M. M., & Draenert, R. (2020). Integration of microarray data and literature mining identifies a sex bias in DPP4+CD4+ T cells in HIV-1 infection. PLOS ONE, 15(9), e0239399. https://doi.org/10.1371/journal.pone.0239399

Vancouver

Bibtex

@article{fd572ee272dd4ecba310c5d38fbd869b,
title = "Integration of microarray data and literature mining identifies a sex bias in DPP4+CD4+ T cells in HIV-1 infection",
abstract = "HIV-1 infection exhibits a significant sex bias. This study aimed at identifying and examining lymphocyte associated sex differences in HIV-1 pathogenesis using a data-driven approach. To select targets for investigating sex differences in lymphocytes, data of microarray experiments and literature mining were integrated. Data from three large-scale microarray experiments were obtained from NCBI/GEO and screened for sex differences in gene expression. Literature mining was employed to identify sex biased genes in the microarray data, which were relevant to HIV-1 pathogenesis and lymphocyte biology. Sex differences in gene expression of selected genes were investigated by RT-qPCR and flowcytometry in healthy individuals and persons living with HIV-1. A significant and consistent sex bias was identified in 31 genes, the majority of which were related to immunity and expressed at higher levels in women. Using literature mining, three genes (DPP4, FCGR1A and SOCS3) were selected for analysis by qPCR because of their relevance to HIV, as well as, B and T cell biology. DPP4 exhibited the most significant sex bias in mRNA expression (p = 0.00029). Therefore, its expression was further analyzed on B and T cells using flowcytometry. In HIV-1 infected controllers and healthy individuals, frequencies of CD4+DPP4+ T cells were higher in women compared to men (p = 0.037 and p = 0.027). In women, CD4 T cell counts correlated with a predominant decreased in DPP4+CD4+ T cells (p = 0.0032). Sex differences in DPP4 expression abrogated in progressive HIV-1 infection. In conclusion, we found sex differences in the pathobiology of T cells in HIV-1 infection using a data-driven approach. Our results indicate that DPP4 expression on CD4+ T cells might contribute to the immunological sex differences observed in chronic HIV‑1 infection.",
author = "Stubbe, {Hans Christian} and Christine Dahlke and Katharina Rotheneder and Renate Stirner and Julia Roider and Raffaele Conca and Ulrich Seybold and Johannes Bogner and Addo, {Marylyn Martina} and Rika Draenert",
year = "2020",
doi = "10.1371/journal.pone.0239399",
language = "English",
volume = "15",
pages = "e0239399",
journal = "PLOS ONE",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "9",

}

RIS

TY - JOUR

T1 - Integration of microarray data and literature mining identifies a sex bias in DPP4+CD4+ T cells in HIV-1 infection

AU - Stubbe, Hans Christian

AU - Dahlke, Christine

AU - Rotheneder, Katharina

AU - Stirner, Renate

AU - Roider, Julia

AU - Conca, Raffaele

AU - Seybold, Ulrich

AU - Bogner, Johannes

AU - Addo, Marylyn Martina

AU - Draenert, Rika

PY - 2020

Y1 - 2020

N2 - HIV-1 infection exhibits a significant sex bias. This study aimed at identifying and examining lymphocyte associated sex differences in HIV-1 pathogenesis using a data-driven approach. To select targets for investigating sex differences in lymphocytes, data of microarray experiments and literature mining were integrated. Data from three large-scale microarray experiments were obtained from NCBI/GEO and screened for sex differences in gene expression. Literature mining was employed to identify sex biased genes in the microarray data, which were relevant to HIV-1 pathogenesis and lymphocyte biology. Sex differences in gene expression of selected genes were investigated by RT-qPCR and flowcytometry in healthy individuals and persons living with HIV-1. A significant and consistent sex bias was identified in 31 genes, the majority of which were related to immunity and expressed at higher levels in women. Using literature mining, three genes (DPP4, FCGR1A and SOCS3) were selected for analysis by qPCR because of their relevance to HIV, as well as, B and T cell biology. DPP4 exhibited the most significant sex bias in mRNA expression (p = 0.00029). Therefore, its expression was further analyzed on B and T cells using flowcytometry. In HIV-1 infected controllers and healthy individuals, frequencies of CD4+DPP4+ T cells were higher in women compared to men (p = 0.037 and p = 0.027). In women, CD4 T cell counts correlated with a predominant decreased in DPP4+CD4+ T cells (p = 0.0032). Sex differences in DPP4 expression abrogated in progressive HIV-1 infection. In conclusion, we found sex differences in the pathobiology of T cells in HIV-1 infection using a data-driven approach. Our results indicate that DPP4 expression on CD4+ T cells might contribute to the immunological sex differences observed in chronic HIV‑1 infection.

AB - HIV-1 infection exhibits a significant sex bias. This study aimed at identifying and examining lymphocyte associated sex differences in HIV-1 pathogenesis using a data-driven approach. To select targets for investigating sex differences in lymphocytes, data of microarray experiments and literature mining were integrated. Data from three large-scale microarray experiments were obtained from NCBI/GEO and screened for sex differences in gene expression. Literature mining was employed to identify sex biased genes in the microarray data, which were relevant to HIV-1 pathogenesis and lymphocyte biology. Sex differences in gene expression of selected genes were investigated by RT-qPCR and flowcytometry in healthy individuals and persons living with HIV-1. A significant and consistent sex bias was identified in 31 genes, the majority of which were related to immunity and expressed at higher levels in women. Using literature mining, three genes (DPP4, FCGR1A and SOCS3) were selected for analysis by qPCR because of their relevance to HIV, as well as, B and T cell biology. DPP4 exhibited the most significant sex bias in mRNA expression (p = 0.00029). Therefore, its expression was further analyzed on B and T cells using flowcytometry. In HIV-1 infected controllers and healthy individuals, frequencies of CD4+DPP4+ T cells were higher in women compared to men (p = 0.037 and p = 0.027). In women, CD4 T cell counts correlated with a predominant decreased in DPP4+CD4+ T cells (p = 0.0032). Sex differences in DPP4 expression abrogated in progressive HIV-1 infection. In conclusion, we found sex differences in the pathobiology of T cells in HIV-1 infection using a data-driven approach. Our results indicate that DPP4 expression on CD4+ T cells might contribute to the immunological sex differences observed in chronic HIV‑1 infection.

U2 - 10.1371/journal.pone.0239399

DO - 10.1371/journal.pone.0239399

M3 - SCORING: Journal article

C2 - 32946499

VL - 15

SP - e0239399

JO - PLOS ONE

JF - PLOS ONE

SN - 1932-6203

IS - 9

ER -