key: cord-0969249-o2vy7meq authors: Yan, H.; Liang, X.; Du, J.; He, Z.; Wang, Y.; Lyu, M.; Yue, L.; Zhang, F.; Xue, Z.; Xu, L.; Ruan, G.; Li, J.; Zhu, H.; Xu, J.; Chen, S.; Zhang, C.; Lv, D.; Lin, Z.; Shen, B.; Zhu, Y.; Qian, B.; Chen, H.; Guo, T. title: Proteomic and Metabolomic Investigation of COVID-19 Patients with Elevated Serum Lactate Dehydrogenase date: 2021-01-11 journal: nan DOI: 10.1101/2021.01.10.21249333 sha: 97bf390ab45d949fd2332dfd848b9465659778f9 doc_id: 969249 cord_uid: o2vy7meq Serum lactate dehydrogenase (LDH) has been established as a prognostic indicator given its differential expression in COVID-19 patients. However, the molecular mechanisms underneath remain poorly understood. In this study, 144 COVID-19 patients were enrolled to monitor the clinical and laboratory parameters over three weeks. Serum lactate dehydrogenase (LDH) was shown elevated in the COVID-19 patients on admission and declined during the convalescence period, and its ability to classify patient severity outperformed other clinical indicators. A threshold of 247 U/L serum LDH on admission was determined for severity prognosis. Next, we classified a subset of 14 patients into high- and low-risk groups based on serum LDH expression and compared their quantitative serum proteomic and metabolomic differences. The results found COVID-19 patients with high serum LDH exhibited differentially expressed blood coagulation and immune responses including acute inflammatory responses, platelet degranulation, complement cascade, as well as multiple different metabolic responses including lipid metabolism, protein ubiquitination and pyruvate fermentation. Specifically, activation of hypoxia responses was highlighted in patients with high LDH expressions. Taken together, our data showed that serum LDH levels is associated COVID-19 severity, and that elevated serum LDH might be consequences of hypoxia and tissue injuries induced by inflammation. INTRODUCTION 5 aminotransferase (AST), alanine aminotransferase (ALT), total bilirubin, total protein, 9 9 creatinine, and creatine kinase (CK), with a Chemistry Analyzer (Beckman Coulter, 1 0 0 AU5821). 1 0 1 1 0 2 Proteomic and metabolomic data set 1 0 3 The proteomic and metabolomic data were extracted from our previous publication 1 0 4 [15]. Briefly, for proteomic experiments, inactivated serum samples were processed 1 0 5 into peptides, labeled with TMTpro 16plex chemical tags, fractionated to 40 aliquots, 1 0 6 and analyzed by LC-MS/MS. The proteomics data were analyzed with Proteome 1 0 7 Discoverer (Version 2.4.1.15, Thermo Fisher Scientific). 894 proteins were quantified 1 0 8 altogether. For metabolomic experiments, inactivated serum samples were processed 1 0 9 to collect metabolites, and divided into 4 fractions for 4 different modes of 1 1 0 LC-MS/MS data acquisition, leading to characterization of 941 metabolites. analysis was used for the selection of the best intercept point. Prediction of disease 1 2 0 progression was obtained using the Cox proportional hazards model. Statistical 1 2 1 proteomic data analysis was performed using R (version 3.6.1). Missing values in the 1 2 2 proteomic data matrix were assigned as 0.01 unless otherwise mentioned. P values ≤ 1 2 3 0.05 were considered statistically significant unless otherwise mentioned. Differential 1 2 4 protein expression was based on the cutoff: P values ≤ 0.05, |log 2 FC| > 0.25. Plotting 1 2 5 was performed with R (version 3.6.1). A total of 144 COVID-19 patients were enrolled in the study. Detailed demographic, 1 3 0 clinical, and laboratory characteristics of these patients on admission were provided in 1 3 1 Table 1 . The median age was 47 years old, and 53.5% of them were male. The severe 1 3 2 patients account for 25% (36/144) of the group, were 10 years older than the 1 3 3 non-severe patients (55 vs. 45, p < 0.001), and were more likely to have fever 1 3 4 symptoms on admission (p = 0.002). Severe patients received more treatment of 1 3 5 oxygen inhalation (p < 0.001), antibiotics (p = 0.024), glucocorticoid (p < 0.001), and 1 3 6 intravenous gamma immunoglobulin (p < 0.001). The patients did not exhibit 1 3 7 significant difference between severe and non-severe groups in terms of gender also showed higher level of alanine aminotransferase (ALT, p = 0.041), aspartate 1 4 4 aminotransferase (AST, p < 0.001), urea (p = 0.004), creatinine (p = 0.014), and 1 4 5 creatine kinase (CK, p < 0.001). We then compared their temporal changes at 7-day 1 4 6 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Here we systematically investigated serum LDH elevation in COVID-19 patients. 3 0 2 We thoroughly inspected both clinical and molecular profiles of 144 COVID-19 3 0 3 patients. We confirmed serum LDH as the best independent risk indicator, and further 3 0 4 optimized a threshold of 247 U/L for stratifying COVID-19 patients based on the 3 0 5 serum LDH level. Our data showed that the serum LDH declined thereafter, patients 3 0 6 with serum LDH levels higher than the threshold on admission are prone to severe 3 0 7 conditions, hence determined as high-risk (HR) patients, and those lower than the 3 0 8 threshold as low-risk (LR) patients. 3 0 9 Proteomic differences between LR and HR groups exposed a list of dysregulated 3 1 0 host responses. Among them, acute inflammatory responses, platelet degranulation 3 1 1 and complement cascade have been reported in previous studies comparing severe and 3 1 2 non-severe COVID-19 patients [15, 37] . Blood coagulation has been highlighted in 3 1 3 another report that compares COVID-19 patients with high and low IL-6 levels [38] . Immune behaviors including activation of immune response and humoral immune 3 1 5 response were further enriched during the intra-comparison within HR patients, 3 1 6 suggesting that the immune behaviors are closely related to serum LDH expression. 3 1 7 Proteomic profiling also highlighted a list of hypoxia related proteins and functions, 3 1 8 including P4HB, DPP4, GAPDH, HSP90AA1, NF-κB and HIF signaling, suggesting 3 1 9 that hypoxia might have contributed to elevated LDH. The metabolomic profiling 3 2 0 complements findings on the proteomic level and further emphasizes dysregulated 3 2 1 lipid metabolism. Taken together, we propose that elevation of serum LDH might 3 2 2 attribute to inflammation-related tissue injuries and hypoxia-related metabolism. This study is limited by several factors. Firstly, the single-center study with a 3 2 4 relatively small patient cohort is subject to experimental bias. Moreover, proteome 3 2 5 data from only 14 individuals were acquired, from which only 2 patients were 3 2 6 determined as high-risk group outliers for comparative analysis. It is worth noting that 3 2 7 serum LDH elevation is not specific to COVID-19 disease [39] . Further studies 3 2 8 should conduct clinical validation on larger cohorts, and compare the molecular 3 2 9 differences including control patients with other diseases with similar symptoms. The research group of T.G. is partly supported by Tencent, Thermo Fisher Scientific, 3 3 3 SCIEX, and Pressure Biosciences Inc. T.G. is a shareholder of Westlake Omics Inc. G.R. is an employee of Westlake Omics Inc. This work was supported by grants from National Key R&D Program of China (No . 3 3 7 2020YFE0202200), National Natural Science Foundation of China (81972492, 3 3 8 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Foundation. We thank Westlake University Supercomputer Center for assistance in 3 4 3 data storage and computation. 3 4 4 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted January 11, 2021. ; https://doi.org/10.1101/2021.01.10.21249333 doi: medRxiv preprint e a t u r e s o f p a t i e n t s i n f e c t e d w i t h 2 0 1 9 3 4 6 n o v e l c o r o n a v i r u s i n W u h a n , C h i n a . L a n c e t 2 0 2 0 , 3 9 5 , 4 9 3 5 8 a r a n c e a n d All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted January 11, 2021. ; https://doi.org/10.1101/2021.01.10.21249333 doi: medRxiv preprint ] D a n g , D . T . , C h u n , S . Y . , B u r k i t t , K . , A b e , M . , e t a l . , H y p o x i a -i n d u c i b l e f a c t o r -1 t a r g e t 4 2 1 g e n e s a s i n d i c a t o r s o f t u m o r v e s s e l r e s p o n s e t o v a s c u l a r e n d o t h e l i a l g r o w t h f a c t o r i n h i b i t i o n . 4 2 2 C a n c e r r e s e a r c h 2 0 0 8 , 6 8 , 1 8 7 2 -1 8 8 0 . 4 2 3 [ 3 2 ] L e u n g , L . L . K . , M o r s e r , J . , C a r b o x y p e p t i d a s e B 2 a n d c a r b o x y p e p t i d a s e N i n t h e c r o s s t a l All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted January 11, 2021. ; https://doi.org/10.1101/2021.01.10.21249333 doi: medRxiv preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted January 11, 2021. ; https://doi.org/10.1101/2021.01.10.21249333 doi: medRxiv preprint μ mol/L 1-7 day 75.5 (66.0-93.0) 71.5 (62.5-84.0) All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted January 11, 2021. ; https://doi.org/10.1101/2021.01.10.21249333 doi: medRxiv preprint 1 8 (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted January 11, 2021. ; https://doi.org/10.1101/2021.01.10.21249333 doi: medRxiv preprint 2 4 7 9 Figure 2 Molecular differences between low-and high-risk patients. A) Heatmap 4 8 0 of 34 differentially expressed proteins and two differentially expressed metabolites. 4 8 1 LR, low-risk patients. HR, high-risk patients. B) Boxplots of nine selected 4 8 2 differentially expressed proteins and two selected differentially expressed metabolites. 4 8 3 C) Protein network including 12 selected differentially expressed proteins. 4 8 4 4 8 5 4 8 6 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted January 11, 2021. ; https://doi.org/10.1101/2021.01.10.21249333 doi: medRxiv preprint 5-211.0) 156.0 (131.3-182.0) Heatmap of 38 differentially expressed proteins. LR, low-risk patients. HR, high-risk 4 8 8 patients. B) Boxplots of 13 selected differentially expressed proteins. C) Proposed 4 8 9 mechanism for serum LDH elevation in COVID-19 patients. 4 9 0 4 9 1 4 9 2 4 9 3 4 9 4 4 9 5 4 9 6 4 9 7 4 9 8