Predicting functional variants in enhancer and promoter elements using RegulomeDB

Dong, Shengcheng; Boyle, Alan P.

doi:10.1002/humu.23791

Cited by 84 publications

(77 citation statements)

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“…The functional relevance of the lead GWAS loci for antibody response was assessed using in silico functional annotation analyses based on Combined Annotation Dependent Depletion (CADD) [ 22 ] scores and RegulomeDB 2.0 [ 23 ] and by leveraging external datasets, such as GTEx v8, DICE (Database of Immune Cell Expression) [ 24 ], and the Human Plasma Proteome Atlas [ 25 , 26 ].…”

Section: Methodsmentioning

confidence: 99%

The landscape of host genetic factors involved in immune response to common viral infections

et al. 2020

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Background Humans and viruses have co-evolved for millennia resulting in a complex host genetic architecture. Understanding the genetic mechanisms of immune response to viral infection provides insight into disease etiology and therapeutic opportunities. Methods We conducted a comprehensive study including genome-wide and transcriptome-wide association analyses to identify genetic loci associated with immunoglobulin G antibody response to 28 antigens for 16 viruses using serological data from 7924 European ancestry participants in the UK Biobank cohort. Results Signals in human leukocyte antigen (HLA) class II region dominated the landscape of viral antibody response, with 40 independent loci and 14 independent classical alleles, 7 of which exhibited pleiotropic effects across viral families. We identified specific amino acid (AA) residues that are associated with seroreactivity, the strongest associations presented in a range of AA positions within DRβ1 at positions 11, 13, 71, and 74 for Epstein-Barr virus (EBV), Varicella zoster virus (VZV), human herpesvirus 7, (HHV7), and Merkel cell polyomavirus (MCV). Genome-wide association analyses discovered 7 novel genetic loci outside the HLA associated with viral antibody response (P < 5.0 × 10−8), including FUT2 (19q13.33) for human polyomavirus BK (BKV), STING1 (5q31.2) for MCV, and CXCR5 (11q23.3) and TBKBP1 (17q21.32) for HHV7. Transcriptome-wide association analyses identified 114 genes associated with response to viral infection, 12 outside of the HLA region, including ECSCR: P = 5.0 × 10−15 (MCV), NTN5: P = 1.1 × 10−9 (BKV), and P2RY13: P = 1.1 × 10−8 EBV nuclear antigen. We also demonstrated pleiotropy between viral response genes and complex diseases, from autoimmune disorders to cancer to neurodegenerative and psychiatric conditions. Conclusions Our study confirms the importance of the HLA region in host response to viral infection and elucidates novel genetic determinants beyond the HLA that contribute to host-virus interaction.

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Section: Methodsmentioning

confidence: 99%

The landscape of host genetic factors involved in immune response to common viral infections

et al. 2020

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“…The functional relevance of the lead GWAS loci for antibody response was assessed using in-silico functional annotation analyses based on Combined Annotation Dependent Depletion (CADD) 21 scores and RegulomeDB 2.0 22 , and by leveraging external datasets, such as GTEx v8, DICE (Database of Immune Cell Expression) 23 , and the Human Plasma Proteome Atlas 24,25 .…”

Section: Methodsmentioning

confidence: 99%

The landscape of host genetic factors involved in immune response to common viral infections

Kachuri

Francis

Morrison

et al. 2020

Preprint

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1 Introduction: Humans and viruses have co-evolved for millennia resulting in a complex host genetic 2 architecture. Understanding the genetic mechanisms of immune response to viral infection provides insight 3 into disease etiology and informs public health interventions.4Methods: We conducted a comprehensive study linking germline genetic variation and gene expression 5 with antibody response to 28 antigens for 16 viruses using serological data from 7924 participants in the 6 UK Biobank cohort. Using test results from 2010 UK Biobank subjects, we also investigated genetic 7 determinants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. 8 Results: Signals in human leukocyte antigen (HLA) class II region dominated the landscape of viral 9 antibody response, with 40 independent loci and 14 independent classical alleles, 7 of which exhibited 10 pleiotropic effects across viral families. Genome-wide association analyses discovered 7 novel genetic loci 11 associated with viral antibody response (P<5.0´10 -8 ), including FUT2 (19q13.33) for human polyomavirus 12 BK (BKV), STING1 (5q31.2) for Merkel cell polyomavirus (MCV), as well as CXCR5 (11q23.3) and TBKBP1 13 (17q21.32) for human herpesvirus 7. Transcriptome-wide association analyses identified 114 genes 14 associated with response to viral infection, 12 outside of the HLA region, including ECSCR: P=5.0×10 -15 15(MCV), NTN5: P=1.1×10 -9 (BKV), and P2RY13: P=1.1×10 -8 (Epstein-Barr virus nuclear antigen). We also 16 demonstrated pleiotropy between viral response genes and complex diseases, such as C4A expression in 17 varicella zoster virus and schizophrenia. Finally, our analyses of SARS-CoV-2 revealed the first genome-18 wide significant infection susceptibility signal in EHF, an epithelial-specific transcriptional repressor 19 implicated in airway disease. Targeted analyses of expression quantitative trait loci suggest a possible role 20 for tissue-specific ACE2 expression in modifying SARS-CoV-2 susceptibility. 21 Conclusions:Our study confirms the importance of the HLA region in host response to viral infection and 22 elucidates novel genetic determinants of host-virus interaction. Our results may have implications for 23 complex disease etiology and COVID-19. : medRxiv preprint 29Viruses have been infecting cells for a half a billion years 1 . During our extensive co-evolution viruses have 30 exerted significant selective pressure on humans; overtly during fatal outbreaks, and covertly through 31 cryptic immune interaction when a pathogen remains latent. The recent pandemic of severe acute 32 respiratory syndrome coronavirus 2 (SARS-CoV-2) highlights the paramount public health need to 33 understand human genetic variation in response to viral challenge. Clinical variation in COVID-19 severity 34 and symptomatic presentation may be due to differences host genetic factors relating to immune response 2 . 35Furthermore, many common infections are cryptically associated with a variety of complex illnesses, 36 especially those with an i...

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“…There had also been only one previous expression regulatory variant challenge, in CAGI4 (Kreimer et al, ). CAGI5 has a new expression regulatory challenge (Shigaki et al, ), and there are also two participant papers (Dong & Boyle, ; Kreimer, Yan, Ahituv, & Yosef, ).…”

Section: Introductionmentioning

confidence: 99%

Reports from the fifth edition of CAGI: The Critical Assessment of Genome Interpretation

et al. 2019

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Interpretation of genomic variation plays an essential role in the analysis of cancer and monogenic disease, and increasingly also in complex trait disease, with applications ranging from basic research to clinical decisions. Many computational impact prediction methods have been developed, yet the field lacks a clear consensus on their appropriate use and interpretation. The Critical Assessment of Genome Interpretation (CAGI, /'kā‐jē/) is a community experiment to objectively assess computational methods for predicting the phenotypic impacts of genomic variation. CAGI participants are provided genetic variants and make blind predictions of resulting phenotype. Independent assessors evaluate the predictions by comparing with experimental and clinical data. CAGI has completed five editions with the goals of establishing the state of art in genome interpretation and of encouraging new methodological developments. This special issue (https://onlinelibrary.wiley.com/toc/10981004/2019/40/9) comprises reports from CAGI, focusing on the fifth edition that culminated in a conference that took place 5 to 7 July 2018. CAGI5 was comprised of 14 challenges and engaged hundreds of participants from a dozen countries. This edition had a notable increase in splicing and expression regulatory variant challenges, while also continuing challenges on clinical genomics, as well as complex disease datasets and missense variants in diseases ranging from cancer to Pompe disease to schizophrenia. Full information about CAGI is at https://genomeinterpretation.org.

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Predicting functional variants in enhancer and promoter elements using RegulomeDB

Cited by 84 publications

References 31 publications

The landscape of host genetic factors involved in immune response to common viral infections

The landscape of host genetic factors involved in immune response to common viral infections

The landscape of host genetic factors involved in immune response to common viral infections

Reports from the fifth edition of CAGI: The Critical Assessment of Genome Interpretation

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