%0 Journal Article %J Genome Med %D 2021 %T Genetic and non-genetic factors affecting the expression of COVID-19-relevant genes in the large airway epithelium. %A Kasela, Silva %A Ortega, Victor E %A Martorella, Molly %A Garudadri, Suresh %A Nguyen, Jenna %A Ampleford, Elizabeth %A Pasanen, Anu %A Nerella, Srilaxmi %A Buschur, Kristina L %A Barjaktarevic, Igor Z %A Barr, R Graham %A Bleecker, Eugene R %A Bowler, Russell P %A Comellas, Alejandro P %A Cooper, Christopher B %A Couper, David J %A Criner, Gerard J %A Curtis, Jeffrey L %A Han, MeiLan K %A Hansel, Nadia N %A Hoffman, Eric A %A Kaner, Robert J %A Krishnan, Jerry A %A Martinez, Fernando J %A McDonald, Merry-Lynn N %A Meyers, Deborah A %A Paine, Robert %A Peters, Stephen P %A Castro, Mario %A Denlinger, Loren C %A Erzurum, Serpil C %A Fahy, John V %A Israel, Elliot %A Jarjour, Nizar N %A Levy, Bruce D %A Li, Xingnan %A Moore, Wendy C %A Wenzel, Sally E %A Zein, Joe %A Langelier, Charles %A Woodruff, Prescott G %A Lappalainen, Tuuli %A Christenson, Stephanie A %K Adult %K Aged %K Aged, 80 and over %K Angiotensin-Converting Enzyme 2 %K Asthma %K Bronchi %K Cardiovascular Diseases %K COVID-19 %K Gene Expression %K Genetic Variation %K Humans %K Middle Aged %K Obesity %K Pulmonary Disease, Chronic Obstructive %K Quantitative Trait Loci %K Respiratory Mucosa %K Risk Factors %K SARS-CoV-2 %K Smoking %X

BACKGROUND: The large airway epithelial barrier provides one of the first lines of defense against respiratory viruses, including SARS-CoV-2 that causes COVID-19. Substantial inter-individual variability in individual disease courses is hypothesized to be partially mediated by the differential regulation of the genes that interact with the SARS-CoV-2 virus or are involved in the subsequent host response. Here, we comprehensively investigated non-genetic and genetic factors influencing COVID-19-relevant bronchial epithelial gene expression.

METHODS: We analyzed RNA-sequencing data from bronchial epithelial brushings obtained from uninfected individuals. We related ACE2 gene expression to host and environmental factors in the SPIROMICS cohort of smokers with and without chronic obstructive pulmonary disease (COPD) and replicated these associations in two asthma cohorts, SARP and MAST. To identify airway biology beyond ACE2 binding that may contribute to increased susceptibility, we used gene set enrichment analyses to determine if gene expression changes indicative of a suppressed airway immune response observed early in SARS-CoV-2 infection are also observed in association with host factors. To identify host genetic variants affecting COVID-19 susceptibility in SPIROMICS, we performed expression quantitative trait (eQTL) mapping and investigated the phenotypic associations of the eQTL variants.

RESULTS: We found that ACE2 expression was higher in relation to active smoking, obesity, and hypertension that are known risk factors of COVID-19 severity, while an association with interferon-related inflammation was driven by the truncated, non-binding ACE2 isoform. We discovered that expression patterns of a suppressed airway immune response to early SARS-CoV-2 infection, compared to other viruses, are similar to patterns associated with obesity, hypertension, and cardiovascular disease, which may thus contribute to a COVID-19-susceptible airway environment. eQTL mapping identified regulatory variants for genes implicated in COVID-19, some of which had pheWAS evidence for their potential role in respiratory infections.

CONCLUSIONS: These data provide evidence that clinically relevant variation in the expression of COVID-19-related genes is associated with host factors, environmental exposures, and likely host genetic variation.

%B Genome Med %V 13 %P 66 %8 2021 04 21 %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/33883027?dopt=Abstract %R 10.1186/s13073-021-00866-2 %0 Journal Article %J Science %D 2020 %T The impact of sex on gene expression across human tissues. %A Oliva, Meritxell %A Muñoz-Aguirre, Manuel %A Kim-Hellmuth, Sarah %A Wucher, Valentin %A Gewirtz, Ariel D H %A Cotter, Daniel J %A Parsana, Princy %A Kasela, Silva %A Balliu, Brunilda %A Viñuela, Ana %A Castel, Stephane E %A Mohammadi, Pejman %A Aguet, François %A Zou, Yuxin %A Khramtsova, Ekaterina A %A Skol, Andrew D %A Garrido-Martín, Diego %A Reverter, Ferran %A Brown, Andrew %A Evans, Patrick %A Gamazon, Eric R %A Payne, Anthony %A Bonazzola, Rodrigo %A Barbeira, Alvaro N %A Hamel, Andrew R %A Martinez-Perez, Angel %A Soria, José Manuel %A Pierce, Brandon L %A Stephens, Matthew %A Eskin, Eleazar %A Dermitzakis, Emmanouil T %A Segrè, Ayellet V %A Im, Hae Kyung %A Engelhardt, Barbara E %A Ardlie, Kristin G %A Montgomery, Stephen B %A Battle, Alexis J %A Lappalainen, Tuuli %A Guigo, Roderic %A Stranger, Barbara E %K Chromosomes, Human, X %K Disease %K Epigenesis, Genetic %K Female %K Gene Expression %K Gene Expression Regulation %K Genetic Variation %K Genome-Wide Association Study %K Humans %K Male %K Organ Specificity %K Promoter Regions, Genetic %K Quantitative Trait Loci %K Sex Characteristics %K Sex Factors %X

Many complex human phenotypes exhibit sex-differentiated characteristics. However, the molecular mechanisms underlying these differences remain largely unknown. We generated a catalog of sex differences in gene expression and in the genetic regulation of gene expression across 44 human tissue sources surveyed by the Genotype-Tissue Expression project (GTEx, v8 release). We demonstrate that sex influences gene expression levels and cellular composition of tissue samples across the human body. A total of 37% of all genes exhibit sex-biased expression in at least one tissue. We identify cis expression quantitative trait loci (eQTLs) with sex-differentiated effects and characterize their cellular origin. By integrating sex-biased eQTLs with genome-wide association study data, we identify 58 gene-trait associations that are driven by genetic regulation of gene expression in a single sex. These findings provide an extensive characterization of sex differences in the human transcriptome and its genetic regulation.

%B Science %V 369 %8 2020 09 11 %G eng %N 6509 %1 https://www.ncbi.nlm.nih.gov/pubmed/32913072?dopt=Abstract %R 10.1126/science.aba3066 %0 Journal Article %J N Engl J Med %D 2020 %T RNA Identification of PRIME Cells Predicting Rheumatoid Arthritis Flares. %A Orange, Dana E %A Yao, Vicky %A Sawicka, Kirsty %A Fak, John %A Frank, Mayu O %A Parveen, Salina %A Blachère, Nathalie E %A Hale, Caryn %A Zhang, Fan %A Raychaudhuri, Soumya %A Troyanskaya, Olga G %A Darnell, Robert B %K Adult %K Arthritis, Rheumatoid %K B-Lymphocytes %K Female %K Fibroblasts %K Flow Cytometry %K Gene Expression %K Humans %K Male %K Mesenchymal Stem Cells %K Middle Aged %K Patient Acuity %K Sequence Analysis, RNA %K Surveys and Questionnaires %K Symptom Flare Up %K Synovial Fluid %X

BACKGROUND: Rheumatoid arthritis, like many inflammatory diseases, is characterized by episodes of quiescence and exacerbation (flares). The molecular events leading to flares are unknown.

METHODS: We established a clinical and technical protocol for repeated home collection of blood in patients with rheumatoid arthritis to allow for longitudinal RNA sequencing (RNA-seq). Specimens were obtained from 364 time points during eight flares over a period of 4 years in our index patient, as well as from 235 time points during flares in three additional patients. We identified transcripts that were differentially expressed before flares and compared these with data from synovial single-cell RNA-seq. Flow cytometry and sorted-blood-cell RNA-seq in additional patients were used to validate the findings.

RESULTS: Consistent changes were observed in blood transcriptional profiles 1 to 2 weeks before a rheumatoid arthritis flare. B-cell activation was followed by expansion of circulating CD45-CD31-PDPN+ preinflammatory mesenchymal, or PRIME, cells in the blood from patients with rheumatoid arthritis; these cells shared features of inflammatory synovial fibroblasts. Levels of circulating PRIME cells decreased during flares in all 4 patients, and flow cytometry and sorted-cell RNA-seq confirmed the presence of PRIME cells in 19 additional patients with rheumatoid arthritis.

CONCLUSIONS: Longitudinal genomic analysis of rheumatoid arthritis flares revealed PRIME cells in the blood during the period before a flare and suggested a model in which these cells become activated by B cells in the weeks before a flare and subsequently migrate out of the blood into the synovium. (Funded by the National Institutes of Health and others.).

%B N Engl J Med %V 383 %P 218-228 %8 2020 07 16 %G eng %N 3 %1 https://www.ncbi.nlm.nih.gov/pubmed/32668112?dopt=Abstract %R 10.1056/NEJMoa2004114 %0 Journal Article %J Nat Commun %D 2017 %T Genetic regulatory effects modified by immune activation contribute to autoimmune disease associations. %A Kim-Hellmuth, Sarah %A Bechheim, Matthias %A Pütz, Benno %A Mohammadi, Pejman %A Nédélec, Yohann %A Giangreco, Nicholas %A Becker, Jessica %A Kaiser, Vera %A Fricker, Nadine %A Beier, Esther %A Boor, Peter %A Castel, Stephane E %A Nöthen, Markus M %A Barreiro, Luis B %A Pickrell, Joseph K %A Müller-Myhsok, Bertram %A Lappalainen, Tuuli %A Schumacher, Johannes %A Hornung, Veit %K Acetylmuramyl-Alanyl-Isoglutamine %K Adjuvants, Immunologic %K Adolescent %K Adult %K Autoimmune Diseases %K Gene Expression %K Gene Expression Profiling %K Gene Expression Regulation %K Genetic Predisposition to Disease %K Healthy Volunteers %K Humans %K Indicators and Reagents %K Lipids %K Lipopolysaccharides %K Male %K Monocytes %K Quantitative Trait Loci %K Regulatory Sequences, Nucleic Acid %K RNA, Double-Stranded %K RNA, Messenger %K Young Adult %X

The immune system plays a major role in human health and disease, and understanding genetic causes of interindividual variability of immune responses is vital. Here, we isolate monocytes from 134 genotyped individuals, stimulate these cells with three defined microbe-associated molecular patterns (LPS, MDP, and 5'-ppp-dsRNA), and profile the transcriptomes at three time points. Mapping expression quantitative trait loci (eQTL), we identify 417 response eQTLs (reQTLs) with varying effects between conditions. We characterize the dynamics of genetic regulation on early and late immune response and observe an enrichment of reQTLs in distal cis-regulatory elements. In addition, reQTLs are enriched for recent positive selection with an evolutionary trend towards enhanced immune response. Finally, we uncover reQTL effects in multiple GWAS loci and show a stronger enrichment for response than constant eQTLs in GWAS signals of several autoimmune diseases. This demonstrates the importance of infectious stimuli in modifying genetic predisposition to disease.Insight into the genetic influence on the immune response is important for the understanding of interindividual variability in human pathologies. Here, the authors generate transcriptome data from human blood monocytes stimulated with various immune stimuli and provide a time-resolved response eQTL map.

%B Nat Commun %V 8 %P 266 %8 2017 08 16 %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/28814792?dopt=Abstract %R 10.1038/s41467-017-00366-1 %0 Journal Article %J Genome Res %D 2017 %T Quantifying the regulatory effect size of -acting genetic variation using allelic fold change. %A Mohammadi, Pejman %A Castel, Stephane E %A Brown, Andrew A %A Lappalainen, Tuuli %K Alleles %K Databases, Genetic %K Gene Expression %K Gene Expression Profiling %K Gene Regulatory Networks %K Genetic Variation %K Humans %K Models, Theoretical %K Quantitative Trait Loci %X

Mapping -acting expression quantitative trait loci (-eQTL) has become a popular approach for characterizing proximal genetic regulatory variants. In this paper, we describe and characterize log allelic fold change (aFC), the magnitude of expression change associated with a given genetic variant, as a biologically interpretable unit for quantifying the effect size of -eQTLs and a mathematically convenient approach for systematic modeling of -regulation. This measure is mathematically independent from expression level and allele frequency, additive, applicable to multiallelic variants, and generalizable to multiple independent variants. We provide efficient tools and guidelines for estimating aFC from both eQTL and allelic expression data sets and apply it to Genotype Tissue Expression (GTEx) data. We show that aFC estimates independently derived from eQTL and allelic expression data are highly consistent, and identify technical and biological correlates of eQTL effect size. We generalize aFC to analyze genes with two eQTLs in GTEx and show that in nearly all cases the two eQTLs act independently in regulating gene expression. In summary, aFC is a solid measure of -regulatory effect size that allows quantitative interpretation of cellular regulatory events from population data, and it is a valuable approach for investigating novel aspects of eQTL data sets.

%B Genome Res %V 27 %P 1872-1884 %8 2017 11 %G eng %N 11 %1 https://www.ncbi.nlm.nih.gov/pubmed/29021289?dopt=Abstract %R 10.1101/gr.216747.116