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Article: Rhinovirus infection of airway epithelial cells uncovers the non-ciliated subset as a likely driver of genetic susceptibility to childhood-onset asthma.

Djeddi, Sarah / Fernandez-Salinas, Daniela / Huang, George X / Aguiar, Vitor R C / Mohanty, Chitrasen / Kendziorski, Christina / Gazal, Steven / Boyce, Joshua / Ober, Carole / Gern, James / Barrett, Nora / Gutierrez-Arcelus, Maria

medRxiv : the preprint server for health sciences

2024

Abstract: Asthma is a complex disease caused by genetic and environmental factors. Epidemiological studies have shown that in children, wheezing during rhinovirus infection (a cause of the common cold) is associated with asthma development during childhood. This ... ...

Abstract	Asthma is a complex disease caused by genetic and environmental factors. Epidemiological studies have shown that in children, wheezing during rhinovirus infection (a cause of the common cold) is associated with asthma development during childhood. This has led scientists to hypothesize there could be a causal relationship between rhinovirus infection and asthma or that RV-induced wheezing identifies individuals at increased risk for asthma development. However, not all children who wheeze when they have a cold develop asthma. Genome-wide association studies (GWAS) have identified hundreds of genetic variants contributing to asthma susceptibility, with the vast majority of likely causal variants being non-coding. Integrative analyses with transcriptomic and epigenomic datasets have indicated that T cells drive asthma risk, which has been supported by mouse studies. However, the datasets ascertained in these integrative analyses lack airway epithelial cells. Furthermore, large-scale transcriptomic T cell studies have not identified the regulatory effects of most non-coding risk variants in asthma GWAS, indicating there could be additional cell types harboring these "missing regulatory effects". Given that airway epithelial cells are the first line of defense against rhinovirus, we hypothesized they could be mediators of genetic susceptibility to asthma. Here we integrate GWAS data with transcriptomic datasets of airway epithelial cells subject to stimuli that could induce activation states relevant to asthma. We demonstrate that epithelial cultures infected with rhinovirus significantly upregulate childhood-onset asthma-associated genes. We show that this upregulation occurs specifically in non-ciliated epithelial cells. This enrichment for genes in asthma risk loci, or 'asthma heritability enrichment' is also significant for epithelial genes upregulated with influenza infection, but not with SARS-CoV-2 infection or cytokine activation. Additionally, cells from patients with asthma showed a stronger heritability enrichment compared to cells from healthy individuals. Overall, our results suggest that rhinovirus infection is an environmental factor that interacts with genetic risk factors through non-ciliated airway epithelial cells to drive childhood-onset asthma.
Language	English
Publishing date	2024-02-06
Publishing country	United States
Document type	Preprint
DOI	10.1101/2024.02.02.24302068
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Article: Functional genomics implicates natural killer cells in the pathogenesis of ankylosing spondylitis.

Chiñas, Marcos / Fernandez-Salinas, Daniela / Aguiar, Vitor R C / Nieto-Caballero, Victor E / Lefton, Micah / Nigrovic, Peter A / Ermann, Joerg / Gutierrez-Arcelus, Maria

medRxiv : the preprint server for health sciences

2024

Abstract: Objective: Multiple lines of evidence indicate that ankylosing spondylitis (AS) is a lymphocyte-driven disease. However, which lymphocyte populations are critical in AS pathogenesis is not known. In this study, we aimed to identify the key cell types ... ...

Abstract	Objective: Multiple lines of evidence indicate that ankylosing spondylitis (AS) is a lymphocyte-driven disease. However, which lymphocyte populations are critical in AS pathogenesis is not known. In this study, we aimed to identify the key cell types mediating the genetic risk in AS using an unbiased functional genomics approach. Methods: We integrated genome-wide association study (GWAS) data with epigenomic and transcriptomic datasets of human immune cells. To quantify enrichment of cell type-specific open chromatin or gene expression in AS risk loci, we used three published methods that have successfully identified relevant cell types in other diseases. We performed co-localization analyses between GWAS risk loci and genetic variants associated with gene expression (eQTL) to find putative target genes. Results: Natural killer (NK) cell-specific open chromatin regions are significantly enriched in heritability for AS, compared to other immune cell types such as T cells, B cells, and monocytes. This finding was consistent between two AS GWAS. Using RNA-seq data, we validated that genes in AS risk loci are enriched in NK cell-specific gene expression. Using the human Space-Time Gut Cell Atlas, we also found significant upregulation of AS-associated genes predominantly in NK cells. Co-localization analysis revealed four AS risk loci affecting regulation of candidate target genes in NK cells: two known loci, Conclusion: Our findings suggest that NK cells may play a crucial role in AS development and highlight four putative target genes for functional follow-up in NK cells.
Language	English
Publishing date	2024-05-09
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.09.21.23295912
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Article ; Online: HLApers: HLA Typing and Quantification of Expression with Personalized Index.

Aguiar, Vitor R C / Masotti, Cibele / Camargo, Anamaria A / Meyer, Diogo

Methods in molecular biology (Clifton, N.J.)

2020 Volume 2120, Page(s) 101–112

Abstract: The plethora of RNA-seq data which have been generated in the recent years constitutes an attractive resource to investigate HLA variation and its relationship with normal and disease phenotypes, such as cancer. However, next generation sequencing (NGS) ... ...

Abstract	The plethora of RNA-seq data which have been generated in the recent years constitutes an attractive resource to investigate HLA variation and its relationship with normal and disease phenotypes, such as cancer. However, next generation sequencing (NGS) brings new challenges to HLA analysis because of the mapping bias introduced by aligning short reads originated from polymorphic genes to a single reference genome. Here we describe HLApers, a pipeline which adapts widely used tools for analysis of standard RNA-seq data to infer HLA genotypes and estimate expression. By generating reliable expression estimates for each HLA allele that an individual carries, HLApers allows a better understanding of the relationship between HLA alleles and phenotypes manifested by an individual.
MeSH term(s)	Alleles ; Gene Expression ; Gene Frequency ; Genotype ; HLA Antigens/genetics ; High-Throughput Nucleotide Sequencing ; Histocompatibility Testing/methods ; Humans ; Phenotype ; Sequence Analysis, RNA/methods
Chemical Substances	HLA Antigens
Language	English
Publishing date	2020-03-02
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ISSN	1940-6029
ISSN (online)	1940-6029
DOI	10.1007/978-1-0716-0327-7_7
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Article: High-throughput identification of functional regulatory SNPs in systemic lupus erythematosus.

Nigrovic, Peter A / Wang, Qiang / Kim, Taehyeung / Martinez-Bonet, Marta / Aguiar, Vitor R C / Sim, Sangwan / Cui, Jing / Sparks, Jeffrey A / Chen, Xiaoting / Todd, Marc / Wauford, Brian / Marion, Miranda C / Langefeld, Carl D / Weirauch, Matthew T / Gutierrez-Arcelus, Maria

bioRxiv : the preprint server for biology

2024

Abstract: Genome-wide association studies implicate multiple loci in risk for systemic lupus erythematosus (SLE), but few contain exonic variants, rendering systematic identification of non-coding variants essential to decoding SLE genetics. We utilized SNP-seq ... ...

Abstract	Genome-wide association studies implicate multiple loci in risk for systemic lupus erythematosus (SLE), but few contain exonic variants, rendering systematic identification of non-coding variants essential to decoding SLE genetics. We utilized SNP-seq and bioinformatic enrichment to interrogate 2180 single-nucleotide polymorphisms (SNPs) from 87 SLE risk loci for potential binding of transcription factors and related proteins from B cells. 52 SNPs that passed initial screening were tested by electrophoretic mobility shift and luciferase reporter assays. To validate the approach, we studied rs2297550 in detail, finding that the risk allele enhanced binding to the transcription factor Ikaros (IKZF1), thereby modulating expression of IKBKE. Correspondingly, primary cells from genotyped healthy donors bearing the risk allele expressed higher levels of the interferon / NF-κB regulator IKKϵ. Together, these findings define a set of likely functional non-coding lupus risk variants and identify a new regulatory pathway involving rs2297550, Ikaros, and IKKϵ implicated by human genetics in risk for SLE.
Language	English
Publishing date	2024-04-12
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.08.16.553538
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Article ; Online: Comparison between qPCR and RNA-seq reveals challenges of quantifying HLA expression.

Aguiar, Vitor R C / Castelli, Erick C / Single, Richard M / Bashirova, Arman / Ramsuran, Veron / Kulkarni, Smita / Augusto, Danillo G / Martin, Maureen P / Gutierrez-Arcelus, Maria / Carrington, Mary / Meyer, Diogo

Immunogenetics

2023 Volume 75, Issue 3, Page(s) 249–262

Abstract: Human leukocyte antigen (HLA) class I and II loci are essential elements of innate and acquired immunity. Their functions include antigen presentation to T cells leading to cellular and humoral immune responses, and modulation of NK cells. Their ... ...

Abstract	Human leukocyte antigen (HLA) class I and II loci are essential elements of innate and acquired immunity. Their functions include antigen presentation to T cells leading to cellular and humoral immune responses, and modulation of NK cells. Their exceptional influence on disease outcome has now been made clear by genome-wide association studies. The exons encoding the peptide-binding groove have been the main focus for determining HLA effects on disease susceptibility/pathogenesis. However, HLA expression levels have also been implicated in disease outcome, adding another dimension to the extreme diversity of HLA that impacts variability in immune responses across individuals. To estimate HLA expression, immunogenetic studies traditionally rely on quantitative PCR (qPCR). Adoption of alternative high-throughput technologies such as RNA-seq has been hampered by technical issues due to the extreme polymorphism at HLA genes. Recently, however, multiple bioinformatic methods have been developed to accurately estimate HLA expression from RNA-seq data. This opens an exciting opportunity to quantify HLA expression in large datasets but also brings questions on whether RNA-seq results are comparable to those by qPCR. In this study, we analyze three classes of expression data for HLA class I genes for a matched set of individuals: (a) RNA-seq, (b) qPCR, and (c) cell surface HLA-C expression. We observed a moderate correlation between expression estimates from qPCR and RNA-seq for HLA-A, -B, and -C (0.2 ≤ rho ≤ 0.53). We discuss technical and biological factors which need to be accounted for when comparing quantifications for different molecular phenotypes or using different techniques.
MeSH term(s)	Humans ; RNA-Seq ; Genome-Wide Association Study ; Histocompatibility Antigens Class I/genetics ; HLA-C Antigens/genetics ; Polymerase Chain Reaction
Chemical Substances	Histocompatibility Antigens Class I ; HLA-C Antigens
Language	English
Publishing date	2023-01-28
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural
ZDB-ID	186560-2
ISSN	1432-1211 ; 0093-7711
ISSN (online)	1432-1211
ISSN	0093-7711
DOI	10.1007/s00251-023-01296-7
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Article: An immunogenetic view of COVID-19.

Aguiar, Vitor R C / Augusto, Danillo G / Castelli, Erick C / Hollenbach, Jill A / Meyer, Diogo / Nunes, Kelly / Petzl-Erler, Maria Luiza

Genetics and molecular biology

2021 Volume 44, Issue 1 Suppl 1, Page(s) e20210036

Abstract: Meeting the challenges brought by the COVID-19 pandemic requires an interdisciplinary approach. In this context, integrating knowledge of immune function with an understanding of how genetic variation influences the nature of immunity is a key challenge. ...

Abstract	Meeting the challenges brought by the COVID-19 pandemic requires an interdisciplinary approach. In this context, integrating knowledge of immune function with an understanding of how genetic variation influences the nature of immunity is a key challenge. Immunogenetics can help explain the heterogeneity of susceptibility and protection to the viral infection and disease progression. Here, we review the knowledge developed so far, discussing fundamental genes for triggering the innate and adaptive immune responses associated with a viral infection, especially with the SARS-CoV-2 mechanisms. We emphasize the role of the HLA and KIR genes, discussing what has been uncovered about their role in COVID-19 and addressing methodological challenges of studying these genes. Finally, we comment on questions that arise when studying admixed populations, highlighting the case of Brazil. We argue that the interplay between immunology and an understanding of genetic associations can provide an important contribution to our knowledge of COVID-19.
Language	English
Publishing date	2021-08-25
Publishing country	Brazil
Document type	Journal Article
ZDB-ID	1445712-x
ISSN	1678-4685 ; 1415-4757
ISSN (online)	1678-4685
ISSN	1415-4757
DOI	10.1590/1678-4685-GMB-2021-0036
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Article ; Online: Expression estimation and eQTL mapping for HLA genes with a personalized pipeline.

Aguiar, Vitor R C / César, Jônatas / Delaneau, Olivier / Dermitzakis, Emmanouil T / Meyer, Diogo

PLoS genetics

2019 Volume 15, Issue 4, Page(s) e1008091

Abstract: The HLA (Human Leukocyte Antigens) genes are well-documented targets of balancing selection, and variation at these loci is associated with many disease phenotypes. Variation in expression levels also influences disease susceptibility and resistance, but ...

Abstract	The HLA (Human Leukocyte Antigens) genes are well-documented targets of balancing selection, and variation at these loci is associated with many disease phenotypes. Variation in expression levels also influences disease susceptibility and resistance, but little information exists about the regulation and population-level patterns of expression. This results from the difficulty in mapping short reads originated from these highly polymorphic loci, and in accounting for the existence of several paralogues. We developed a computational pipeline to accurately estimate expression for HLA genes based on RNA-seq, improving both locus-level and allele-level estimates. First, reads are aligned to all known HLA sequences in order to infer HLA genotypes, then quantification of expression is carried out using a personalized index. We use simulations to show that expression estimates obtained in this way are not biased due to divergence from the reference genome. We applied our pipeline to the GEUVADIS dataset, and compared the quantifications to those obtained with reference transcriptome. Although the personalized pipeline recovers more reads, we found that using the reference transcriptome produces estimates similar to the personalized pipeline (r ≥ 0.87) with the exception of HLA-DQA1. We describe the impact of the HLA-personalized approach on downstream analyses for nine classical HLA loci (HLA-A, HLA-C, HLA-B, HLA-DRA, HLA-DRB1, HLA-DQA1, HLA-DQB1, HLA-DPA1, HLA-DPB1). Although the influence of the HLA-personalized approach is modest for eQTL mapping, the p-values and the causality of the eQTLs obtained are better than when the reference transcriptome is used. We investigate how the eQTLs we identified explain variation in expression among lineages of HLA alleles. Finally, we discuss possible causes underlying differences between expression estimates obtained using RNA-seq, antibody-based approaches and qPCR.
MeSH term(s)	Alleles ; Chromosome Mapping ; Computational Biology/methods ; Gene Expression ; Gene Frequency ; Genotype ; HLA Antigens/genetics ; Haplotypes ; Humans ; Quantitative Trait Loci ; Transcriptome
Chemical Substances	HLA Antigens
Language	English
Publishing date	2019-04-22
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2186725-2
ISSN	1553-7404 ; 1553-7390
ISSN (online)	1553-7404
ISSN	1553-7390
DOI	10.1371/journal.pgen.1008091
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Article ; Online: Non-coding autoimmune risk variant defines role for ICOS in T peripheral helper cell development.

Kim, Taehyeung / Martínez-Bonet, Marta / Wang, Qiang / Hackert, Nicolaj / Sparks, Jeffrey A / Baglaenko, Yuriy / Koh, Byunghee / Darbousset, Roxane / Laza-Briviesca, Raquel / Chen, Xiaoting / Aguiar, Vitor R C / Chiu, Darren J / Westra, Harm-Jan / Gutierrez-Arcelus, Maria / Weirauch, Matthew T / Raychaudhuri, Soumya / Rao, Deepak A / Nigrovic, Peter A

Nature communications

2024 Volume 15, Issue 1, Page(s) 2150

Abstract: Fine-mapping and functional studies implicate rs117701653, a non-coding single nucleotide polymorphism in the CD28/CTLA4/ICOS locus, as a risk variant for rheumatoid arthritis and type 1 diabetes. Here, using DNA pulldown, mass spectrometry, genome ... ...

Abstract	Fine-mapping and functional studies implicate rs117701653, a non-coding single nucleotide polymorphism in the CD28/CTLA4/ICOS locus, as a risk variant for rheumatoid arthritis and type 1 diabetes. Here, using DNA pulldown, mass spectrometry, genome editing and eQTL analysis, we establish that the disease-associated risk allele is functional, reducing affinity for the inhibitory chromosomal regulator SMCHD1 to enhance expression of inducible T-cell costimulator (ICOS) in memory CD4
MeSH term(s)	Humans ; T-Lymphocytes/metabolism ; Arthritis, Rheumatoid ; Inducible T-Cell Co-Stimulator Protein/metabolism ; CD28 Antigens/metabolism ; Alleles ; T-Lymphocytes, Helper-Inducer ; Chromosomal Proteins, Non-Histone/metabolism
Chemical Substances	Inducible T-Cell Co-Stimulator Protein ; CD28 Antigens ; ICOS protein, human ; SMCHD1 protein, human ; Chromosomal Proteins, Non-Histone
Language	English
Publishing date	2024-03-09
Publishing country	England
Document type	Journal Article
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-024-46457-8
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Article ; Online: Assessing false paternity risk in simulated motherless cases from more than 20 000 real exclusion trios.

Aguiar, Vitor R C / de Castro, Amanda M / Pinto, Laélia M / Ferreira, Alessandro C S / Dos Santos, Eldamária V W / Louro, Iuri D

Transfusion

2020 Volume 61, Issue 3, Page(s) 678–681

Abstract: Background: When the mother's DNA profile is not available for paternity testing, there is a smaller probability that a locus will exclude an alleged father. This study aims to evaluate the risk of potential false paternity inclusions in motherless ... ...

Abstract	Background: When the mother's DNA profile is not available for paternity testing, there is a smaller probability that a locus will exclude an alleged father. This study aims to evaluate the risk of potential false paternity inclusions in motherless cases. Study design and methods: More than 20 000 duos were generated by removing the maternal genotypes from exclusion trios. After recalculating paternity in these duos, any found inclusions would be false. Results: The use of an appropriate number of loci, mutation model, and mutation rates to analyze motherless paternity cases was robust against false inclusions. A single potential false inclusion was observed in a case wherein kinship plays a role. This result highlights the importance of testing the mother when available and of obtaining information on family circumstances for the proper handling of cases involving related individuals. Conclusion: The guidelines we used here were sufficient to avoid false inclusions in a data set of more than 20 000 motherless cases.
MeSH term(s)	Alleles ; Computer Simulation ; Female ; Genetic Loci ; Genotype ; Humans ; Male ; Microsatellite Repeats ; Mothers ; Mutation ; Paternity ; Probability
Language	English
Publishing date	2020-10-21
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	208417-x
ISSN	1537-2995 ; 0041-1132
ISSN (online)	1537-2995
ISSN	0041-1132
DOI	10.1111/trf.16153
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Article: Mapping the dynamic genetic regulatory architecture of

Kang, Joyce B / Shen, Amber Z / Sakaue, Saori / Luo, Yang / Gurajala, Saisriram / Nathan, Aparna / Rumker, Laurie / Aguiar, Vitor R C / Valencia, Cristian / Lagattuta, Kaitlyn / Zhang, Fan / Jonsson, Anna Helena / Yazar, Seyhan / Alquicira-Hernandez, Jose / Khalili, Hamed / Ananthakrishnan, Ashwin N / Jagadeesh, Karthik / Dey, Kushal / Daly, Mark J /

Xavier, Ramnik J / Donlin, Laura T / Anolik, Jennifer H / Powell, Joseph E / Rao, Deepak A / Brenner, Michael B / Gutierrez-Arcelus, Maria / Raychaudhuri, Soumya

medRxiv : the preprint server for health sciences

2023

Abstract: The human leukocyte antigen (HLA) locus plays a critical role in complex traits spanning autoimmune and infectious diseases, transplantation, and cancer. While coding variation ... ...

Abstract	The human leukocyte antigen (HLA) locus plays a critical role in complex traits spanning autoimmune and infectious diseases, transplantation, and cancer. While coding variation in
Language	English
Publishing date	2023-03-20
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.03.14.23287257
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