key: cord-0837647-tqtxhepr authors: Schmidt, Frank; Abdesselem, Houari B.; Suhre, Karsten; Sohail, Muhammad U.; Al-Nesf, Maryam; Bensmail, Ilham; Mashod, Fathima; Sarwath, Hina; Bernhardt, Joerg; Tan, Ti-Myen; Morris, Priscilla E; Schenck, Edward J.; Price, David; Vaikath, Nishant N.; Mohamed-Ali, Vidya; Al-Maadheed, Mohammed; Arredouani, Abdelilah; Decock, Julie; Blackburn, Jonathan M.; Choi, Augustine M.K.; El-Agnaf, Omar M. title: Auto-Immunoproteomics Analysis of COVID-19 ICU Patients Revealed Increased Levels of Autoantibodies Related to Male Reproductive System date: 2022-02-09 journal: bioRxiv DOI: 10.1101/2022.02.09.479669 sha: 9824165ad5aeb80c7ae4e342576f055f9aa7376c doc_id: 837647 cord_uid: tqtxhepr The role of autoantibodies in coronavirus disease (COVID-19) complications is not yet fully understood. The current investigation screened two independent cohorts of 97 COVID-19 patients (Discovery (Disc) cohort from Qatar (n = 49) and Replication (Rep) cohort from New York (n = 48)) utilizing high-throughput KoRectly Expressed (KREX) immunome protein-array technology. Autoantibody responses to 57 proteins were significantly altered in the COVID-19 Disc cohort compared to healthy controls (P ≤ 0.05). The Rep cohort had altered autoantibody responses against 26 proteins compared to non-COVID-19 ICU patients that served as controls. Both cohorts showed substantial similarities (r2 = 0.73) and exhibited higher autoantibodies responses to numerous transcription factors, immunomodulatory proteins, and human disease markers. Analysis of the combined cohorts revealed elevated autoantibody responses against SPANXN4, STK25, ATF4, PRKD2, and CHMP3 proteins in COVID-19 patients. KREX analysis of the specific IgG autoantibody responses indicates that the targeted host proteins are supposedly increased in COVID-19 patients. The autoantigen-autoantibody response was cross-validated for SPANXN4 and STK25 proteins using Uniprot BLASTP and sequence alignment tools. SPANXN4 is essential for spermiogenesis and male fertility, which may predict a potential role for this protein in COVID-19 associated male reproductive tract complications and warrants further research. Significance Statement Coronavirus disease (COVID-19), caused by the SARS-CoV-2 virus, has emerged as a global pandemic with a high morbidity rate and multiorgan complications. It is observed that the host immune system contributes to the varied responses to COVID-19 pathogenesis. Autoantibodies, immune system proteins that mistakenly target the body’s own tissue, may underlie some of this variation. We screened total IgG autoantibody responses against 1,318 human proteins in two COVID-19 patient cohorts. We observed several novel markers in COVID-19 patients that are associated with male fertility, such as sperm protein SPANXN4, STK25, and the apoptotic factor ATF4. Particularly, elevated levels of autoantibodies against the testicular tissue-specific protein SPANXN4 offer significant evidence of anticipating the protein role in COVID-19 associated male reproductive complications. Coronavirus disease , caused by novel SARS-CoV-2 virus, has emerged as global 90 pandemic with severe complications and high morbidity rate. The disease manifests a wide range 91 of clinical symptoms, which are exacerbated by overactive and malfunctioning immune system of 92 the host. Despite extensive research on innate and adaptive immune responses in little 93 is known about the role of autoantibodies on disease progression and severe complications. 94 Infection with the SARS-CoV-2 causes a variety of symptoms, with most cases being moderate or 95 asymptomatic, and only a smaller proportion advancing to more severe state of COVID-19 96 disease 1 . Many questions about the COVID-19 pathophysiology remain open, particularly why 97 some people develop severe disease symptoms while others remain asymptomatic. 98 Acute respiratory distress syndrome (ARDS) affects a small percentage of patients, whereas others 99 experience persistent lung damage and multi-organ illness that lasts months, even after the virus 100 has been eliminated from the body 2 . High expression of angiotensin-converting enzyme 2 (ACE2) 101 receptors in several organs of the body extends infection beyond respiratory tract, resulting in 102 complex multiorgan complications 3 . ACE2 receptors are highly expressed in the male reproductive 103 system, demonstrating the involvement of SARS-CoV-2 in male fertility, which is one of the 104 unexplained manifestations of COVID-19 4 . 105 Autoantibodies have been identified in significant proportion of COVID-19 hospitalized patients 106 with positive correlation with immune responses to SARS-CoV-2 proteins 5 . Several studies 107 observed significant rise in a diverse range of autoantibodies against immunomodulatory proteins, 108 a-and w-interferons, cardiolipin and prothrombin during antiviral responses in severely ill 109 COVID-19 patients 6, 7, 8, 9, 10, 11 . Particularly, autoantibodies against immune-related signaling 110 proteins were found to contribute to COVID-19 pathogenesis by antagonizing the function of the 111 innate immune system 12 . Although there have been some reports on disease-modifying 112 autoantibody responses, the immunological and clinical consequences of autoantibodies in 113 COVID-19 are yet to be fully understood. Here, we therefore screened total IgG autoantibody 114 responses against 1,318 human proteins in COVID-19 patients using KREX immunome protein-115 array technology. Sengenics KREX technology employs full-length, naturally folded proteins that 116 allow maximum epitopes binding to discover autoantibody biomarker proteins 13 . The quantitative 117 signal measured on the arrays for each autoantibody-autoantigen pair is directly proportional to 118 the autoantibody concentration in the blood with higher autoantibody titres to these proteins 119 simplistically implying higher autoantigen concentrations in COVID-19 patients compared to 120 controls, albeit the correlation is non-linear. 121 Autoantibody-based precision immuno-profiling has previously been shown to aid discovery of 122 biomarkers of immune-related adverse events, as well as therapeutic prediction of drug response 14 . 123 In the present study, by utilizing a broad array-based immunoproteomics strategy that 124 simultaneously quantifies autoantibody responses across multiple organ systems in ICU COVID-125 19 patients and post recovery cohort, we aimed to better identify novel markers of comorbidities 126 in COVID-19 patients. We identified a number of novel markers in COVID-19 patients that are 127 also associated with male fertility, such as the sperm protein SPANXN4 15 , the androgenic kinase 128 197 Biotinylated human IgG (detected by fluorescently labelled secondary antibody) and biotinylated 198 human anti-IgG (detected only when plasma or serum is added to the slide) were used as positive 199 controls to assess assay integrity. Extrapolated data was then filtered, normalized and transformed 200 as follows: Briefly, the median background pixel intensity (RFU) was subtracted from the median 201 foreground pixel intensity (RFU) for each antigen to give the median net intensity per spot (RFU); 202 CVs were calculated for each antigen based on the quadruplicate technical replica spots for each 203 antigen on a given array, any antigens with CV above 20% were flagged and outlier spots removed, 204 providing that at least two valid values remained; net intensity values for each antigen in a given 205 sample were calculated as the mean of the net intensity values for technical replica spots on that 206 array; and data was normalised across replica arrays based on the Cy3-BSA controls as previously 207 described 27 . Z-scores were then calculated by subtracting the overall mean antigen intensity 208 (within a single sample) from the net intensity data for each antigen in that sample, and dividing 209 that result by the standard deviation of all of the measured net intensities in that sample, according 210 to the formula: z = (x -μ) / σ where x is the net intensity of an antigen in a given sample, m is the 211 mean net intensity calculated across all antigens in that sample, and s is the standard deviation of 212 the net intensities for all antigens in that sample. All downstream statistical analysis was done 213 based on the calculated z-scores. 214 We needed to be cautious in directly comparing the results across different antigens on the arrays 216 because the autoantigen-autoantibody response is not always linear and is an indirect way of 217 prediction of protein concentrations. Since it can depend amongst others on both B cell activation 218 and sequence identity among proteins that express similar antigen epitopes. To check this latter 219 possibility, we selected two proteins (SPANXN4 and STK25) that showed the highest 220 autoantibody alterations to perform their sequence alignment and antigen specificity analysis. 221 Uniprot BLASTP program was used to compare proteins sequences. All human and viral protein 222 sequences with more than 50% sequence similarity were aligned for epitope mapping to determine 223 whether the evaluated RFU values were specific to the protein of interest or could be derived from 224 highly homologous epitopes on other proteins. 225 The assingment of KREX array proteins to functional KEGG categories and their hierarchical 227 organisation was displayed by using Paver, a software for the visualization of Voronoi Treemaps 28 . 228 Any main category is displayed in different colors. The cell sizes were calculated according the 229 signal intensity of the proteins immunofluorescence (highly fluorescent signals give larger cells). 230 Functional Enrichment Analysis was performed to identify biological functions that were over-231 represented in differentially expressed proteins with a p-value less than 0.05. Differentially 232 expressed proteins, both up-regulated and down-regulated, were used separately as proteins of 233 interest and the proteins detected from all probes were used as the background set. The proteins 234 were further annotated using KEGG-and WIKI-Pathways data prior to performing Fisher's exact 235 test to determine pathways in which the proteins of interest were significantly over-represented. 236 This analysis was performed on R 3.6.2 using clusterProfiler 3.14.3. GOSemSim was used to 237 eliminate redundant GO-BP results. Only significantly over-represented pathways with a p-value 238 less than 0.05 (-log10 p-value cut-off 1.3) are shown. 239 Proteins are reported using the symbols of the genes that encode them to offer a clear and uniform 241 nomenclature. Autoantibody response, measured as relative fluorescence units (RFU), was 242 normalized to calculate z-score. Statistical analysis was performed using R (version 4.1.0) and 243 rstudio (version 1.4.1717). Two kinds of inferal statistical tests were performed to test the 244 hypotheses of whether a given autoantibody was differentially expressed in COVID cases versus 245 controls. First, the means between cases and controls were compared using a linear model, using 246 the z-scored autoantibody responses as dependant variables and the COVID state as independent 247 variable (coded as 0=controls and 1=cases). Note that this approach is equivalent to conducting an 248 unrelated T-test and that the effect size of the linear model matches the estimated difference of the 249 means in a T-test. Second, binarized autoantibody responses were tested against cases versus 250 controls using Fisher's exact test. The cutoff for binarization of the autoimmune response was set 251 to one. As the response is z-scored, this means that all samples with an RFU score above one 252 standard deviation from the mean were considered as being positive for the respective 253 autoantibody whereas all other were considered negative. were included as controls for the Rep cohort. Because of the special composition of the cohorts, 277 we were able to specifically look for COVID-19-related autoantibody signals compared with 278 healthy-baseline-and general infection-baseline-titres. A combined analysis (discovery and 279 replication) allowed stringent COVID-19-specific autoimmune responses to be monitored. Table 280 1 summarises the demographic and status-specific information of the study cohorts. 281 To discover functional IgG-related autoantibodies that could influence COVID-19 predictions 283 and/or outcomes, we used the KREX high-throughput autoantibody assay technology that includes 284 a variety of known human-autoantigens such as cancer-, kinase-, interleukins-, cytokine, 285 ribonuclear transcription and signaling-proteins 29 . Total IgG autoantibody responses were 286 quantified for 1,600 proteins in the Discovery Cohort and for a subset of 1,318 proteins in the 287 Replication Cohort. However, to increase stringency and reduce complexity, only the 1,318 288 overlapping proteins were subsequently used in the analysis pipeline. The majority of antigens on 289 the array are found in the cytoplasm, nucleus, or cell membrane, but there are also proteins from 290 the mitochondria, endoplasmic reticulum, and cytoskeleton. 291 The KREX assay reports RFU values for autoantigen-specific autoantibody binding, with linearity 292 over 6 orders of magnitude and with a detection limit in the pg/ml range. These measured RFU 293 values correlate directly with the antigen-specific IgG autoantibody titres, since ligand binding 294 theory shows that the measured signal on-array is linearly proportional to autoantibody 295 concentration. Thus, a higher RFU value for a specific autoantibody-autoantigen interaction 296 indicates a higher autoantibody titre, whilst a higher antibody titer in turn implies a higher 297 autoantigen concentration (or repeated exposure to the autoantigen), accepting that this latter 298 correlation is non-linear. In a first overview, the general intensity distributions were calculated 299 based on the mean autoantibody-antigen titers across all samples and further examined using 300 KEGG-Brite-based Voronoi treemaps using the replication cohort as an example (Figure 1) . 301 Approximately 1,150 of the 1,318 proteins could be assigned to the annotation, with the relative 302 size of each cell on the Voronoi treemaps reflecting the observed autoantibody response against 303 that protein (Figure 1 left) . Nearly all proteins showed a total IgG AB-signal in the cases and the 304 corresponding controls, the latter represents the natural autoimmunity or the healthy repertoire of 305 autoantibodies. In Figure 1 right, the corresponding pathways are summarized in different colors, 306 with most proteins belonging to the MAPK pathway (light blue), followed by transcription factors 307 (green), chromosomal proteins (green), ribosomes (all blue), and metabolic proteins (yellow). A 308 few proteins belong to the cell cycle (red), chemokines (cyan) or cancer (black). The 10 highest 309 autoantibody titers were found against RBPJ, TPM1, TACC1, KRT19, PTPN20, TBCB, KRT15, 310 AFF4, HSPD1, and CBFA2T3, many of these are structure related proteins. The 10 proteins with 311 the lowest titers were AIF1, IL18, NCK1, COMMD3, NEK11, TGFBR2, SLA, PKM, MAPK6, 312 and MLKL, many of which are cytoplasmic proteins involved in phosphorylation. 313 Relative autoantibody response in the Disc cohort revealed significantly higher level of 314 SPANXN4 and ATF4 315 To examine the effects of SARS-CoV-2 infection on the autoantibody response, we first performed 316 a differential expression analysis in Disc cohort between COVID-19 cases and healthy controls 317 using T-test. Autoantibody responses of fifty-seven proteins were altered significantly (T-test p-318 value ≤ 0.05) (Supplementary file sheet 3). Autoantibody responses in COVID-19 patients were 319 increased for forty proteins, while decreased for seventeen proteins (Figure 2A ). The most elevated 320 autoantibody responses in COVID-19 patients were against ATF4 (effect size (beta) = 3.32 SD; 321 T-test p-value ≤ 0.001) and the sperm protein associated with the nucleus on the X chromosome 322 N4 (SPANXN4) (effect size (beta) = 3.32 SD; T-test p-value ≤ 0.001). The latter is also known as 323 spermiogenesis-related protein and belongs to the family of cancer/testis-associated proteins 324 (CTAs) 30 . 325 We then conducted an analysis using binarized autoimmune response, assuming that all samples 326 with an autoimmune response that exceeds the mean by one s.d. as positive and all others as 327 negative (Supplementary file sheet 4). Using Fisher's exact test, we found twenty-five COVID-19 328 patients had higher RFU values for SPANXN4 compared to only five in controls (Fisher's test p-329 value ≤ 0.0001) ( Figure 2B ). Autoantibodies against ATF4, recombining signal binding protein J 330 (RBPJ), and programmed cell death 5 (PDCD5) were also significantly elevated (Fisher's test p-331 value ≤ 0.05) in the COVID-19 patients. Only the binarized SPANXN4 association reaches the 332 most stringent Bonferroni significance level, that is p < 0.05 / number of proteins = 1,318. In the 333 control group EAPP, SSNA1, and LDHB proteins showed higher autoantibody responses than the 334 cases. 335 Following the initial blood sample collection at the time of ICU admission, follow-up samples 338 were collected from fifteen patients at six weeks after recovery from COVID-19. For several 339 proteins, a strong correlation (Pearson's r 2 ≥ 0.69) was observed between the autoantibody 340 responses at the two sampling time points ( Figure 3A ). Autoantibody responses against several 341 proteins, including SPANXN4, STK25, TRAF3IP1, AMOTL2, PSMD4, and PPP1R2P9 remained 342 highly elevated (p ≤ 0.05) at 6 weeks post-recovery follow-up. Particularly, autoantibody 343 responses against SPANXN4 ( Figure 3B ) stayed elevated at both initial (T1) and follow-up (T2) 344 time points. These observations reveal that SPANXN4 autoantibody responses remain elevated for 345 extended periods, suggesting potential association with chronic health issues. 346 Autoantibody response for the Rep cohort (n = 48) was compared with the non-COVID-19 ICU 348 control patients (N = 28) ( Figure 4A ). Autoantibody responses of twenty-six proteins altered 349 significantly ( Principal components analysis (PCA) of protein RFU data from the two cohorts demonstrated 363 strong overlap between COVID-19 samples and the two cohorts did not separate into discrete 364 clusters ( Figure 5 ). Pearson's correlation analysis revealed that the autoantibody responses of the 365 two cohorts have high correlation (r 2 = 0.73). 366 At third stage, we combine data from both the Disc and Rep cohorts (n = 97) and compared them 367 with combined controls (n = 76). Case vs. control analysis revealed that autoantibody responses 368 against fifty-six proteins were significantly altered: 35 autoantibodies with increased and 21 369 autoantibodies with decreased responses (T-test p ≤ 0.05) ( Figure 6A ). SPANXN4, ATF4, STK25, 370 and PRKD2 were the proteins with the highest effect size (beta). In total forty patients had 371 SPANXN4 RFU higher than 1 sigma value (Fisher's exact test p-value ≤ 0.0001) in the combined 372 COVID-19 cohorts compared with the six patients only in controls ( Figure 6B ). 373 Furthermore, the autoantibody responses, expressed as RFU z-score for fifty-six proteins that 374 differed significantly between the study groups are shown in Figure 7A . The heatmap shows that 375 most of the proteins display similar pattern of autoantibody ratios across the study cohorts. These 376 analyses demonstrate that our autoantibody response data are highly reproducible despite 377 differences in population ethnicity, different laboratories, and sampling materials (serum vs. 378 plasma in Disc vs. Rep cohorts, respectively). 379 KEGG and WIKI pathways analysis was performed to identify the functional contribution of 381 autoantibodies targeted proteins in cellular processes and immune-inflammatory systems. 382 Pathways associated with T helper cells (Th1, Th2, and Th17) differentiation, bacterial/viral 383 infections, stress hormones release, and prostate cancer were upregulated in COVID-19 patients 384 ( Figure 7B ). WIKI pathways were also activated for host immunity and interferon signaling, 385 including T cell activation for SARS-CoV-2 and Staphylococcus aureus infections ( Figure 7B ). 386 SPANXN4 and STK25 share sequence identity with SPANX-and STK-family proteins but 387 showed unique AB-titers in COVID-19 patients 388 In order to check cross-reactivities, sequence homology and antigen specificity analysis were 389 performed for SPANXN4 and STK25 against human and viral protein databases. Only few 390 proteins appeared to have more than 50% sequence identity with our target proteins ((SPANXN4 391 with SPANXN1, 2, 3, and 5) and (STK25 with STK 3, 4, 24, and 26)) ( Figure 8 and 9 ). However, 392 many of these homologous proteins were also part of our KREX immunome panel but did not 393 show any significant changes, which means that the observed RFUs are highly specific against the 394 targeted proteins. 395 396 Discussion 397 In the current COVID-19 pandemic, there is increasing interest globally in understanding the 398 underlying immunology of COVID-19, as well as revealing new health issues arising from 399 COVID-19 complications. Several papers have described the existence and cross-reactivity of 400 SARS-CoV-2 specific T-cell responses 33, 34, 35, 36 and KRT15) that are responsible for epithelial cell structural integrity are linked to COVID-19 416 pathogenesis and disease severity 42 . Furthermore, many of these proteins are also involved in male 417 reproductive system physiology and fertility, yet there has been no previous report in COVID-19 418 patients. 419 Our Disc cohort reported higher autoantibodies against SPANXN4, ATF4, RBPJ, and PDCD5 420 proteins compared to the controls. Comparison between COVID-19 baseline (T1) vs. follow-up 421 (T2) samples indicated that SPANXN4 autoantibodies remained elevated at post-recovery stage. 422 Prolonged autoantibody responses may highlight COVID-19 post-acute sequelae by stimulating 423 the humoral immune response in a way that leads to long-term autoantibody production 43 . The 424 diverse variety of proteins linked to a prolonged autoantibody response suggest that SARS-CoV-425 2 may stimulate autoantibody formation by molecular mimicry 44 , targeting cardiolipin, 426 cardiolipin-binding proteins, platelet factor 4, prothrombin, and coagulation factors, suggesting 427 their role in coagulopathies, chronic comorbidities and post-infection recovery 45, 46, 47 . We 428 hypothesize that elevated autoimmune antibodies against SPANXN4, STK25, TRAF3IP1, 429 AMOTL2, PSMD4, and PPP1R2P9 might suggest a similar role. However, Dotan et al. 48 430 investigated in-silico sequence homology of all human proteins with the virus but could not find 431 evidence that any of the proteins mentioned here are part of such a mimicry process. Vice versa, 432 we cannot exclude that the titers might be elevated before the exposure to SARS-CoV-2, due to 433 pre-existing diseases such as cancer or prolonged inflammation. 434 In contrast, the Rep cohort had higher levels of autoantibody responses to SPANXN4, PDCD2L, 435 PRKD2, and STK25 proteins than the controls. Except for SPANXN4, all other proteins with the 436 high autoantibody response were not significantly elevated between the two cohorts but often 437 showed similar trends. These differences could be attributed to the fact that the control group in 438 the Disc cohort was comprised of healthy volunteers, whereas the control group in the Rep study 439 was comprised of ICU patients suffering from bacterial or viral ARDS, or pneumonia. 440 When all COVID-19 patients (N = 97) from both cohorts were merged and compared to all controls 441 (N = 76) from both cohorts, the most significant autoantibody responses were observed against 442 SPANXN4, ATF4, STK25, and PRKD2. ATF4 regulates metabolic and redox processes in the 443 human body, and an increased ATF4 response has been observed in previous coronavirus disease 49, 444 50 . Fischer et al. 18 suggested that ATF4 also plays role in differentiation of the vas deferens lamina 445 propria layer that helps improve spermatozoa fertilization rate. STK25 and PRKD2 are two 446 important kinases with several physiological roles in our body. However, their role in male 447 reproductive tract physiology is least discussed. A few studies highlight STK25 as androgenic 448 kinase 16, 17 and PRKD2 role in male reproductive tract development 19 . 449 SPANXN4 belongs to a protein family called "sperm protein associated with nucleus in the X 450 chromosome" (SPANX) that are essential for motility and fertilization capacity of male-ejaculated 451 spermatozoa 15 . SPANXNs are also known as cancer testis antigens ( Urizar-Arenaza I, et al. SPANX-A/D protein subfamily plays a key role in nuclear 568 organisation, metabolism and flagellar motility of human spermatozoa Testosterone Retention Mechanism in Sertoli Cells: A Biochemical 572 Perspective Role of Endocytosis in Cellular Uptake of Sex Steroids Activating transcription factor 4 is required for the differentiation of the 578 lamina propria layer of the vas deferens Exploration of miRNA and mRNA Profiles in Fresh and Frozen-Thawed 581 Boar Sperm by Transcriptome and Small RNA Sequencing 585 Comprehensive functional enrichment analysis of male infertility Clinical management of severe acute respiratory infection when novel 589 coronavirus ( nCoV) infection is suspected: interim guidance Identifying organ dysfunction trajectory-based subphenotypes in critically ill 593 patients with COVID-19. medRxiv Comparison of qSOFA and SIRS for predicting adverse outcomes of 596 patients with suspicion of sepsis outside the intensive care unit Circulating cell death biomarker TRAIL is associated with increased 599 organ dysfunction in sepsis Novel potential serological 602 prostate cancer biomarkers using CT100+ cancer antigen microarray platform in a multi-603 cultural South African cohort Miniaturized, microarray-based assays for 606 chemical proteomic studies of protein function Analyser, a user-friendly tool for data processing and normalization Visualizing Gene Expression Data via 613 Voronoi Treemaps Epitope-specific Patients Using a Novel Multiplexed Array-based Immunoassay Platform. medRxiv The SPANX gene family of cancer/testis-specific antigens: rapid 621 evolution and amplification in African great apes and hominids Novel roles of Pkd2 in male reproductive system development Cigarette Smoking Is Associated with Human Semen Quality in Synergy with 628 Functional NRF2 Polymorphisms1 Targets of T Cell Responses to SARS-CoV-2 Coronavirus in Humans with 631 COVID-19 Disease and Unexposed Individuals Broad and strong memory CD4(+) and CD8(+) T cells induced by SARS-CoV-634 2 in UK convalescent individuals following COVID-19 Discordant neutralizing antibody and T cell responses in 638 asymptomatic and mild SARS-CoV-2 infection Robust T Cell Immunity in Convalescent Individuals with Asymptomatic or 641 Mild COVID-19 COVID-19 and 644 male fertility: Taking stock of one year after the outbreak began Keratin 6, 16 and 17-Critical Barrier Alarmin Molecules in Skin 648 Wounds and Psoriasis RBPJ inhibition impairs the growth of lung cancer KRT19 directly interacts with β-catenin/RAC1 complex to regulate NUMB-654 dependent NOTCH signaling pathway and breast cancer properties The Notch Pathway: A Link Between COVID-19 Pathophysiology and 658 Its Cardiovascular Complications Longitudinal proteomic profiling of dialysis patients with COVID-19 reveals 661 markers of severity and predictors of death Long COVID or Post-acute Sequelae of COVID-19 (PASC): An 664 Overview of Biological Factors That May Contribute to Persistent Symptoms COVID-19 and autoimmune diseases Potential microenvironment of SARS-CoV-2 infection in airway epithelial 671 cells revealed by Human Protein Atlas database analysis. bioRxiv Host-Viral Interactions Revealed among Shared 675 Transcriptomics Signatures of ARDS and Thrombosis: A Clue 677 678 47. Root-Bernstein R. COVID-19 coagulopathies: Human blood proteins mimic SARS-CoV-2 679 virus, vaccine proteins and bacterial co-infections inducing autoimmunity The SARS-CoV-2 as an 683 instrumental trigger of autoimmunity Oxygen-dependent ATF-4 stability is mediated by the PHD3 oxygen 686 sensor Upregulation of CHOP/GADD153 689 during coronavirus infectious bronchitis virus infection modulates apoptosis by 690 restricting activation of the extracellular signal-regulated kinase pathway The human SPANX multigene family: genomic organization, 694 alignment and expression in male germ cells and tumor cell lines Modulation of mitogen-activated 698 protein kinase-activated protein kinase 3 by hepatitis C virus core protein Male Fertility and the COVID-19 Pandemic: Systematic Review of the 702 Literature Male genital damage in COVID-19 patients: Are available data 705 relevant? COVID-19 disrupts the blood-testis barrier through the induction of 708 inflammatory cytokines and disruption of junctional proteins Impaired spermatogenesis in COVID-19 patients Bioinformatic analyses hinted at augmented T helper 17 cell differentiation 715 and cytokine response as the central mechanism of COVID-19-associated Guillain-Barré 716 syndrome Downregulated Gene Expression Spectrum and Immune Responses 719 Changed During the Disease Progression in Patients With COVID-19 Advances in the role of helper T cells in autoimmune 723 diseases Sperm fibrous sheath proteins: a 726 potential new class of target antigens for use in human therapeutic cancer vaccines Figure 1: Mapping of KREX Array proteins to KEGG categories (KEGG Pathway and KEGG 736 The other 738 main categories are defined as cellular processes (top left -red), Human diseases (top middle -739 greyish purple), Organismal systems (to right -magenta), Genetic information processing (left -740 blue), Brite protein families (center -dark green), metabolism (right -orange), environmental 741 information processing (bottom right -cyan) Red dots represent proteins with 749 an elevated autoantibody response, while blue dots represent proteins with a lower autoantibody 750 response in COVID-19 patients. Proteins with Fisher's test p-value ≤ 0.05 are labelled in the 751 volcano graph. B) Table on Fisher's exact statistics comparing subjects (numbers) of COVID-19 752 (n = 49) and the control (n = 48) groups for only thirteen proteins that showed significantly altered Red dots represent 766 proteins with a high autoantibody response, while blue dots represent proteins with a low 767 autoantibody response in COVID-19 positive patients. Only proteins with Fisher's test p-value ≤ 768 0.05 are labelled in the volcano graph. B) Table on Fisher's exact statistics comparing subjects 769 (numbers) of COVID-19 (n = 49) and the control (n = 48) groups for only thirteen proteins that 770 showed significantly altered Principal Components Analysis of the Discovery (n = 49, blue circles) and the 774 Each point represents a sample. A) PCA pair plot 775 compares PC1 to PC3. The proportion of variance explained in our cohorts by each PC is shown 776 in parentheses on the axis labels. B) PCA 2D plot with PC1 and PC2 Red dots represent proteins with a high 783 autoantibody response, while blue dots represent proteins with a low autoantibody response in 784 COVID-19 positive patients. Only proteins with Fisher's test p-value ≤ 0.05 are labelled in the 785 volcano graph. B) Table on Fisher's exact statistics comparing subjects (numbers) of COVID-19 786 (n = 49) and the control (n = 48) groups for only thirteen proteins that showed significantly altered Only proteins with 793 significantly altered autoantibody responses were selected. Red color indicates higher and blue 794 color indicates lower autoantibody responses against the proteins. B) KEGG and WIKI pathways 795 analysis presented as bar-plot shows overactivated pathways in COVID-19 patients