key: cord-0788334-ylnoewoq authors: Franzen, J.; Nuechtern, S.; Tharmapalan, V.; Vieri, M.; Nikolic, M.; Han, Y.; Balfanz, P.; Marx, N.; Dreher, M.; Bruemmendorf, T. H.; Dahl, E.; Beier, F.; Wagner, W. title: Epigenetic clocks are not accelerated in COVID-19 patients date: 2020-11-16 journal: nan DOI: 10.1101/2020.11.13.20229781 sha: 3af5705a676d2cfa80b60e96bdff7fdd01a82598 doc_id: 788334 cord_uid: ylnoewoq Age is a major risk factor for severe outcome of coronavirus disease 2019 (COVID-19), but it remains unclear if this is rather due to increased chronological age or biological age. During lifetime, specific DNA methylation changes are acquired in our genome that act as "epigenetic clocks" allowing to estimate donor age and to provide a surrogate marker for biological age. In this study, we followed the hypothesis that particularly patients with accelerated epigenetic age are affected by severe outcomes of COVID-19. Using four different age predictors, we did not observe accelerated age in global DNA methylation profiles of blood samples of nine COVID-19 patients. Alternatively, we used targeted bisulfite amplicon sequencing of three age-associated genomic regions to estimate donor-age of blood samples of 95 controls and seventeen COVID-19 patients. The predictions correlated well with chronological age, while COVID-19 patients even tended to be predicted younger than expected. Furthermore, lymphocytes in nineteen COVID-19 patients did not reveal significantly accelerated telomere attrition. Our results demonstrate that these biomarkers of biological age are therefore not suitable to predict a higher risk for severe COVID-19 infection in elderly patients. Coronavirus disease 2019 with severe or even fatal outcome disproportionately affects elderly people (Mueller et al., 2020) . The infection fatality rate (IFR) exponentially increases with age: while the IFR is zero in children it starts to increase at approximately 55 years (0.4 %) and finally leads to an IFR of 15 % in 85 year old adults (Levin et al., 2020) . Chronological age is thus one of the major risk factors to develop severe symptoms during an infection with severe acute respiratory syndrome coronavirus 2 and this risk is independent of other age-related comorbidities like diabetes, cardiovascular diseases, obesity (Mueller et al., 2020) , or the detection of clonal hematopoiesis of indeterminate potential (CHIP) (Hameister et al., 2020) . Recently, it has been suggested that particularly elderly people with accelerated biological age are susceptible to severe disease outcomes . The process of biological aging is reflected by molecular hallmarks of aging, which include epigenetic modifications (Lopez-Otin et al., 2013) . There are highly reproducible DNA methylation changes during aging that are acquired at specific CG dinucleotides, so called "CpG sites". The DNA methylation levels of several age-associated CpGs can therefore be combined into "epigenetic clocks" to predict donor age (Bell et al., 2019; Koch and Wagner, 2011) . Notably, various diseases have been associated with accelerated epigenetic aging and accelerated epigenetic age predictions for blood samples are indicative for higher all-cause mortality (Marioni et al., 2015) . Thus, epigenetic age of blood does not only reflect chronological age but also aspects of biological age (Field et al., 2018) . We therefore followed the hypothesis that accelerated epigenetic age increases susceptibility to severe COVID-19 infections (Mueller et al., 2020; Santesmasses et al., 2020) . . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint The copyright holder for this this version posted November 16, 2020. ; https://doi.org/10.1101 https://doi.org/10. /2020 In this study, we used blood samples of 20 patients with severe SARS-CoV-2 infection either with or without acute respiratory distress syndrome (ARDS; Supplemental Table S1 ). All samples were collected at the University Hospital of RWTH Aachen, after written informed consent, and were provided by RWTH cBMB, the biobank of the Medical Faculty of RWTH Aachen University. The mean age was 66 years (32 -85 years) and 13 of the 20 samples suffered from ARDS. Since DNA methylation profiles of COVID-19 patients have so far hardly been addressed, the initial nine samples were tested with the Illumina EPIC methylation microarray that investigates approximately 850,000 CpG sites across the genome as part of a pilot study. For comparison we utilized publicly available DNA methylation profiles of 185 healthy blood control samples, which were generated before the first outbreak of SARS-CoV-2. A direct comparison of these studies was hampered by different Illumina BeadChip platforms (450k and EPIC) and batch effects, which despite quantile normalization become apparent in principle component analysis (PCA; Supplemental Figure S1 ). However, despite batch effects, the results of Illumina BeadChip profiles usually provide relatively robust results for epigenetic signatures, which are based on multiple CpGs (Han et al., 2020; Horvath, 2013; Lin et al., 2016) . For orientation, we initially estimated the cellular composition of leucocytes based on DNA methylation profiles, as described by Houseman et al. (2012) . We observed significantly lower predictions for CD4 T cells in COVID-19 patients as compared to controls (p = 0.0024, Welch's t-test; Supplemental Figure S2A ), which is in line with results of other groups that investigated leukocyte subsets by flow cytometry (Diao et al., 2020) . Furthermore, for our 18 COVID-19 samples with available blood counts the percentage of lymphocytes was significantly lower than in healthy control samples (p < 10 -08 , Welch's t-test; Supplemental Figure S2B ). . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint The copyright holder for this this version posted November 16, 2020. ; https://doi.org/10. 1101 We used four different epigenetic age predictors for the Illumina BeadChip profiles: 1) a frequently used aging signature that has been trained for multiple tissues by Horvath (2013) with 353 CpGs; 2) a more recent skin and blood clock of Horvath et al. based on 391 relevant CpGs (Horvath et al., 2018) ; 3) a frequently used aging signature by Hannum et al. (2013) , which was trained on blood samples and utilizes 71 CpGs; and 4) our recently described age-predictor for blood that was trained on 65 CpGs (Han et al., 2020) . Signatures 1 and 3 comprise CpGs that were not measured by the EPIC BeadChip (19 and 6, respectively), and this might result in a moderate offset of age-predictions. Nevertheless, with all four signatures the epigenetic age-predictions of the nine COVID-19 samples correlated clearly with chronological age ( Figure 1A ) and there was a mean absolute error of 6 years, 5 years, 7 years, and 6 years, respectively. Notably, in comparison to controls the COVID-19 samples did not reveal accelerated epigenetic age: the difference between epigenetic age predictions and chronological age, referred to as "delta age", centered around zero years with the different predictors ( Figure 1B) . . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint The copyright holder for this this version posted November 16, 2020. ; https://doi.org/10.1101/2020.11.13.20229781 doi: medRxiv preprint (2020). B) Boxplots present the deviation of epigenetic age prediction and chronological age (delta age). Overall, the DNA methylation profiles of the nine COVID-19 samples (indicated in red) did not show consistent age-acceleration across the different aging signatures. Subsequently, we tested these and additional COVID-19 samples with a targeted bisulfite amplicon sequencing (BA-seq) of age-associated regions. We have recently described BA-seq for nine CpGs that provide robust and reliable age predictions (Han et al., 2020) . To further ease applicability of the method we have meanwhile refined the signature to focus on the three regions with highest correlation with chronological age and with a combination of hyper-and hypomethylated CpGs to reduce the PCR bias. The three relevant CpG sites are associated with the genes Coiled-Coil Domain-Containing Protein Phosphodiesterase 4C (PDE4C), as described before (Han et al., 2020) . We utilized BA-. CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this this version posted November 16, 2020. ; https://doi.org/10.1101/2020.11.13.20229781 doi: medRxiv preprint seq data of 40 healthy blood samples of our previous work to derive the following multivariable model: Epigenetic age (years) = -0.34 DNAm CCDC102B + 0.83 DNAm FHL2 + 1.18 DNAm PDE4C + 3.86 We initially validated this method with 78 blood samples of healthy donors (18 -83 years) that were collected before the begin of the SARS-CoV-2 pandemic. The epigenetic age predictions revealed a mean absolute error of 4.23 years and a coefficient of determination with chronological age of R² = 0.83. Subsequently, we processed blood samples of 17 COVID-19 patients in parallel with 17 age-matched healthy controls (Figure 2A ). There was no evidence for accelerated epigenetic aging in the COVID-19 samples, even if we stratified into samples with or without ARDS ( Figure 2B ). There was also no evidence for accelerated DNA methylation changes when we analyzed the age-associated CpGs individually (Supplemental Figure S3 ). Telomere attrition is another hallmark of aging and correlates with age in peripheral blood cells (Brümmendorf and Balabanov, 2006) . A recent study indicated that in leukocytes of COVID-19 patients telomere attrition below the 10 th percentile is more frequent than in healthy controls (Froidure et al., 2020) , however the results of this study might be affected by the lymphopenia observed in COVID-19 patients (Benetos et al., 2020) . To further investigate if this alternative biomarker for biological age is accelerated, we analyzed telomere length in lymphocytes of 19 COVID-19 patients with Flow-FISH, as described in detail before Kirschner et al., 2020) . In comparison to the telomere length distribution of 356 healthy controls (Werner et al., 2015) there was overall no evidence for significant telomere attrition in COVID-19 patients ( Figure 2C,D) . . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint The copyright holder for this this version posted November 16, 2020. ; https://doi.org/10.1101/2020.11.13.20229781 doi: medRxiv preprint A) Three age-associated CpGs in the genes CCDC102B, FHL2, and PDE4C were analyzed with targeted bisulfite amplicon sequencing (BA-seq). A multivariable model for epigenetic age-predictions was validated with 78 controls (grey). Subsequently, we analyzed 17 blood samples of red) or without ARDS (n = 5, light red) and 17 age-matched controls (blue). B) The deviation of chronological and predicted epigenetic age (delta-age) is presented (no significant differences; Welch's t test). C) Telomere lengths in kilo bases of 19 COVID-19 patients. Lines indicate percentiles of the telomere lengths of 356 healthy controls. D) The telomere length difference of no ARDS and ARDS patients to the respective age-adapted telomere length. Taken together, despite of the limitations of a rather small sample size, our results do not provide evidence that severe outcome of COVID-19 is associated with accelerated epigenetic age or significantly shortened telomere length. Thus, we did not observe signs . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint The copyright holder for this this version posted November 16, 2020. ; https://doi.org/10.1101/2020.11.13.20229781 doi: medRxiv preprint of premature biological aging in our COVID-19 patients. On the other hand, the infection with SARS-CoV-2 did not directly impact on epigenetic age-predictions. It has recently been demonstrated that HIV infection leads to an average aging advancement of 4.9 years, linking molecular aging, epigenetic regulation and disease progression in this retroviral disease (Gross et al., 2016) . Furthermore, coronavirus infections have been suggested to mediate DNA methylation at antigen-presentation-associated gene promoters (Menachery et al., 2018) . It is still unclear if the different tissues of a human organism reveal the same pace of epigenetic aging and hence it is conceivable that nasopharyngeal and bronchial epithelium, which is preferentially infected by SARS-CoV-2, reveals higher delta-age with epigenetic age-predictions. A recent study suggested that in airway epithelial cells of healthy controls there is age-associated hypomethylation at a CpG site (cg08559914) located near the transcription start site of the receptor angiotensinconverting enzyme 2 (ACE2) that permits cell entry of SARS-CoV-2 (Corley and Ndhlovu, 2020) . Thus, specific age-associated DNA methylations may be functionally relevant to increase susceptibility to fatal COVID-19. A follow up study with a larger sample size would be required to ultimately rule out a predictive value of either telomere length or ageassociated methylation changes in defined subpopulations of patients affected by COVID-19. Either way, our results demonstrate that age-associated DNA methylation changes are not generally accelerated in patients with severe SARS-CoV-2 infections. Analysis of epigenetic age in blood is therefore not suitable to stratify elderly patients that are potentially even more susceptible to severe COVID-19 infections. . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint The copyright holder for this this version posted November 16, 2020. ; https://doi.org/10. 1101 DNA methylation aging clocks: challenges and recommendations A Mechanism for Severity of Disease in Older Patients with COVID-19: The Nexus between Telomere Length and Lymphopenia Telomere length dynamics in normal hematopoiesis and in disease states characterized by increased stem cell turnover DNA Methylation Analysis of the COVID-19 Host Cell Receptor, Angiotensin I Converting Enzyme 2 Gene (ACE2) in the Respiratory System Reveal Age and Gender Differences Reduction and Functional Exhaustion of T Cells in Patients With Coronavirus Disease 2019 (COVID-19) Comparison of flow-FISH and MM-qPCR telomere length assessment techniques for the screening of telomeropathies DNA Methylation Clocks in Aging: Categories, Causes, and Consequences Short telomeres increase the risk of severe COVID-19 Methylome-wide Analysis of Chronic HIV Infection Reveals Five-Year Increase in Biological Age and Epigenetic Targeting of HLA Clonal Hematopoiesis in Hospitalized Elderly Patients With COVID-19. Hemasphere New targeted approaches for epigenetic age predictions Genome-wide Methylation Profiles Reveal Quantitative Views of Human Aging Rates DNA methylation age of human tissues and cell types Epigenetic clock for skin and blood cells applied to Hutchinson Gilford Progeria Syndrome and ex vivo studies DNA methylation arrays as surrogate measures of cell mixture distribution Androgen derivatives improve blood counts and elongate telomere length in adult cryptic dyskeratosis congenita Epigenetic-aging-signature to determine age in different tissues COVID-19 severity is predicted by earlier evidence of accelerated aging. medRxiv : the preprint server for health sciences Assessing the age specificity of infection fatality rates for COVID-19: Systematic review, meta-analysis, and public policy implications. medRxiv DNA methylation levels at individual age-associated CpG sites can be indicative for life expectancy The hallmarks of aging DNA methylation age of blood predicts all-cause mortality in later life MERS-CoV and H5N1 influenza virus antagonize antigen presentation by altering the epigenetic landscape Why does COVID-19 disproportionately affect older people? COVID-19 is an emergent disease of aging Reconstructing the in vivo dynamics of hematopoietic stem cells from telomere length distributions