key: cord-259261-fmuozy3w authors: Bickler, Stephen W.; Cauvi, David M.; Fisch, Kathleen M.; Prieto, James M.; Gaidry, Alicia D.; Thangarajah, Hariharan; Lazar, David; Ignacio, Romeo; Gerstmann, Dale R.; Ryan, Allen F.; Bickler, Philip E.; De Maio, Antonio title: AGE IS ASSOCIATED WITH INCREASED EXPRESSION OF PATTERN RECOGNITION RECEPTOR GENES AND ACE2, THE RECEPTOR FOR SARS-COV-2: IMPLICATIONS FOR THE EPIDEMIOLOGY OF COVID-19 DISEASE date: 2020-06-16 journal: bioRxiv DOI: 10.1101/2020.06.15.134403 sha: doc_id: 259261 cord_uid: fmuozy3w Older aged adults and those with pre-existing conditions are at highest risk for severe COVID-19 associated outcomes. Using a large dataset of genome-wide RNA-seq profiles derived from human dermal fibroblasts (GSE113957) we investigated whether age affects the expression of pattern recognition receptor (PRR) genes and ACE2, the receptor for SARS-CoV-2. Older age was associated with increased expression of PRR genes, ACE2 and four genes that encode proteins that have been shown to interact with SAR2-CoV-2 proteins. Assessment of PRR expression might provide a strategy for stratifying the risk of severe COVID-19 disease at both the individual and population levels. Most people infected with SARS-CoV-2 will have mild to moderate cold and flu-like symptoms, or even be asymptomatic (1) . Older aged adults, and those with underlying conditions such as diabetes mellitus, chronic lung disease and cardiovascular disease are at highest risk for severe COVID-19 associated outcomes (2) . The highest case fatality rates are in the 80 years and older age group (7.8%), with the lowest in the 0-9 years age group (0.00161%) (3) . The reasons for these markedly different outcomes at the extremes of age and for the occasional death that occurs in apparently healthy younger patients remain poorly understood. Pattern recognition receptors (PRRs) play crucial roles in the innate immune response by recognizing pathogen-associated molecular patterns (PAMPs) and molecules derived from damaged cells, referred to as damage-associated molecular patterns (DAMPs) (4) (5) (6) . PRRs are coupled to intracellular signaling cascades that control transcription of a wide spectrum of inflammatory genes. Humans have several distinct classes of PRRs, including Toll-like receptors (TLRs), NOD-like receptors (NLRs), RIG-like receptors (RLRs), C-type lectin receptors (CLRs) and intracellular DNA sensors. PRRs play a critical role in the inflammatory response induced by viruses and are important determinants of outcome (7) (8) (9) . the oldest (≥80 years) and the youngest (≤10 years) age groups (see "Methods" section). After filtering out genes with low expression (cpm >0.5 in at least two samples), a total of 1252 genes were differentially expressed between the oldest relative to the youngest age group (Fig. 1a Table 2 ). We next focused on whether the expression of individual PRR genes change with age. Between the oldest (≥80 years) and the youngest (≤10 years) age groups we found three differentially expressed PRR genes (TLR3, TLR4, and IHIF1) that had a log2FC >1.0 ( Fig. 1c and d, Additional file 1: Suppl Tables 1b and 3a-c) . Plots of the other TLR genes counts are provided in Additional file 4: Suppl Figure 1 . The expression of two PRR genes were negatively correlated with age, Nucleotide-binding oligomerization domain-containing protein 1 (NOD1) (log2FC = -0.27; Adj. P Value = 0.01; Pearson r -0.18, Adj. P Value 0.04) and Cyclic GMP-AMP Synthase (CGAS) (log2FC = -0.56, Adj. P Value 7.89E-05; Pearson r -0.34, Adj. P Value 6.6E-5). Both genes encode proteins that activate the immune response to viruses (15, 16) . To explore our findings further, we performed a differential gene expression analysis on the dermal fibroblast cell lines that had high (>75 th percentile) and low (<25 th percentile) expression of TLR4 (Additional file 5: Suppl Table 4 ). Curiously, enrichment analysis of the 789 differentially expressed genes showed cell cycle (KEGG: hsa04110) to be the canonical pathway with the greatest enrichment (FDR 1.55E-06), similar to the enrichment of the differentially expressed genes between oldest and youngest groups ( Fig. 1b and 2c , Additional file 6: Suppl Table 5 ). TLR4 is known to act via the adaptor molecule TRIF to regulate the expression of type I interferons. TLR activation of TRIF can also induce the cell cycle, an effect which is antagonized by type I interferons (17) . Our finding of both high levels of TLR4 and elevated cell cycle could thus imply changes in the expression of type I interferons. We then examined whether the expression of ACE2, the receptor for SARS-CoV-2, changes with age. ACE2 expression was detected in 35 of the 133 cell lines (26.3%) and showed a marked increase in the 80+ age group (Fig. 2b right) . ACE2 expression was correlated with the expression of 19 of the 21 PRR genes ( Fig. 2a and Additional file: Suppl Table 3a-c). Of note, ACE2 was expressed at much lower levels than TLR4, with variable expression in the 80 year and over age group. Whether the latter reflects the biological state of the individuals who donated the skin samples or is a consequence of ex vivo culture will require further study. We also asked the question if the differentially expressed genes between the oldest and youngest age groups encode proteins that interact with SARS-CoV-2 (see "Methods" section). Our analysis revealed eleven differentially expressed genes between the oldest and youngest age groups that encode proteins known to interact with SARS-CoV-2 (Fig. 3d) . Four of these genes (ADAM9, FBLN5, FAM8A1, CLIP4) have increased expression in the older compared to the younger age groups. Interestingly, the SAR-CoV-2 proteins to which they bind relate to lipid modifications and vesicle trafficking. Host interactions of Orf8 (endoplasmic reticulum quality control), M (ER structural morphology proteins), and NSp13 (golgins) may facilitate the dramatic reconfiguration of ER/Golgi trafficking during coronavirus infection (18) . Whether age-related increases in the expression of host proteins that bind SARS-CoV-2 protein predispose to COVID-19 disease or change its clinical course deserves further study. The COVID-19 (Coronavirus Disease-2019) pandemic is presenting unprecedented challenges to health care systems and governments worldwide. As of June 15, 2020 there have been 7,949,073 confirmed cases worldwide, resulting in 434,181 deaths (19) . COVID-19 disease is caused by the novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). In this study, we used RNA-seq data from a large collection of dermal fibroblasts to demonstrate that PRR genes and ACE2 vary with age. Further, we show that aging is associated with increased expression of several genes that encode proteins known to bind to SARS-CoV-2. Whether these gene expression differences contribute to the epidemiology of SARS-CoV-2 infection will require further study. Nevertheless, overexpression of PRR genes, TLR4 in particular, is an intriguing mechanism to explain the relationship between age and SARS-CoV-2 infection, and potentially the TLR-mediated cytokine storm that characterizes the morbidity and mortality in COVID-19 disease. TLR4 has been previously suggested to have a role in the damaging responses that occurs during viral infections, acting via both PAMPs and DAMPs Our study does have some limitations. Foremost, is that health information was not available for the individuals donating skin samples to the dermal fibroblast collection. Although, the skin samples are reported to be from "apparently healthy individuals", we believe it is unlikely that individuals in the oldest age group were completely free of chronic diseases. Another limitation was that minority groups are inadequately represented in the collection. The dermal fibroblast collection includes samples from one American Indian (<1%), one Hispanic (<1%), two Asians (1.5%), and nine Blacks (6.7%)-way too few to draw any meaningful conclusions on the ethnic groups that have been the hardest hit by the COVID-19 pandemic. Finally, as the scientific community ramps up research in response to the COVID-19 pandemic, the dermal fibroblast model could prove useful for investigating SARS-CoV-2 biology. Fibroblasts have been previously used to investigate host antiviral defenses during Coronavirus infection (29) . The potential strength of the dermal fibroblast model is that skin samples can be easily obtained from donors of different ages, sex, and ethnicities, and those with varying comorbidities such a high blood pressure and diabetes; and from smokers and non-smokers. Such a model would also have an advantage over transfection models as these cells would not only have increased expression of ACE2 and TLR4, but also have an aged transcriptome which could be important for the infectivity and outcome of the SARS-CoV-2 infection. The critical role PRRs play in mediating host-pathogen interactions, and their increased expression in some comorbidities associated with poor COVID-19 outcomes, make them an attractive target for developing tools to predict risk for and outcomes of SARS-CoV-2 infection at both the individual and population levels. Using a large dataset of genome-wide RNA-seq profiles derived from human dermal fibroblasts we show that expression of PRR genes and ACE2, the receptor for SARS-CoV-2 vary with age. Advanced age was also associated with increased expression of several genes that encode proteins which interact with SARS-CoV-2. Given that PRRs function as a critical interface between the host and invading pathogens, further research is needed to better understand how changes in PRR expression affects the susceptibility to and outcome of SARS-CoV-2 infection. Our analysis was done using RNA-seq data (GSE113957) from the National Center for Biotechnology Information (NCBI, Bethesda, MD, USA). Normalized TMM gene counts per million for the individual dermal fibroblast cell lines were downloaded from the GEO RNA-seq Experiments Interactive Navigator (GREIN) (30, 31) . Limma-Voom (32, 33) was used to identify differentially expressed genes between the oldest (≥80 years, N=33) and youngest (≤10 years, N=14) age groups. Differentially expressed genes were defined as those with an Adjusted P value <0.05 after multiple testing correction and an absolute log2Fold Change >1.0. Enrichment analysis of the differentially expressed genes was performed with ToppGene (34). Pairwise Pearson correlation coefficients were calculated between the normalized gene counts of the 21 PRR genes, ACE2 and age, over all 133 samples using GraphPad Prism version 8.0. Protein-protein interactions linking differentially expressed genes and SARS-CoV-2 proteins were identified by overlaying differentially expressed genes in the oldest and youngest age groups on to the SARS-CoV-2 human protein-protein interaction map reported by Gordon, et al (18) . Network visualization was performed using Cytoscape (35) the NDEx v2.4.5 (36) . 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