Difference in serum complement component C4a levels between hepatitis C virus carriers with persistently normal alanine aminotransferase levels or chronic hepatitis C

Abstract

Certain hepatitis C virus (HCV) carriers exhibit persistently normal alanine aminotransferase (ALT) levels (PNALT) (≤30 IU/l) accompanied by normal platelet counts (≥15×104/μl); these individuals show milder disease activity and slower progression to cirrhosis. This study aimed to elucidate the characteristics of HCV carriers with PNALT using serum proteomics. The first group of subjects, who underwent clinical evaluation in the hospital, consisted of 19 HCV carriers with PNALT (PNALT-1) and 20 chronic hepatitis C (CHC-1) patients. The second group of subjects was part of a cohort study on the natural history of liver disease, and included 37 PNALT (PNALT-2) and 30 CHC (CHC-2) patients. Affinity bead-purified serum protein was subjected to matrix-assisted laser desorption ionization time-of-flight mass spectrometry analysis. Serum proteomics showed that 6 protein peaks with mass-to-charge ratios ranging from 1,000 to 3,000 differed significantly between the PNALT-1 and CHC-1 groups. Among these peaks, a 1738-m/z peak protein was identified as a fragment of complement component 4 (C4) and correlated significantly with serum C4a concentrations as determined by enzyme immunoassay. Serum C4a levels were also significantly higher in the PNALT-2 group compared to the CHC-2 group and healthy volunteers. Furthermore, in the PNALT-2 group, serum C4a levels negatively correlated with transaminase levels, but not with other biochemical tests, HCV core antigen levels, peripheral blood cell counts or serum hepatic fibrosis markers. This study indicates that host factors such as C4a not only differ between HCV carriers with PNALT and CHC, but that proteomic approaches could also contribute to the elucidation of factors in PNALT as more differences are discovered.

Identification of Differentially Expressed Genes and Enriched Pathways in SARS-CoV-2/ COVID-19 using Bioinformatics Analysis

“…Similarly, GO enrichment analysis, many up and down-regulated genes may play a very key role in the progression of SARS-CoV-2 infection. Enriched genes such as IFNL4 [117], ZFP36 [118], CD274 [119], MIR21 [120], CYP1A1 [121], CMPK2 [122], C4A [123], SERPINE1 [124], CCRL2 [125], CD69 [126], FAH (fumarylacetoacetate hydrolase) [127], ERFE (erythroferrone) [128], SERINC5 [129], ADI1 [130], AP2M1 [131], PRIMPOL (primase and DNA directed polymerase) [132], BIRC5 [133] and TF (transferrin) [134] were responsible for the advancement of various viral infections, but these genes may be involved in the progression of SARS-CoV-2 infection. Enriched genes such as APOBEC3G [135], NLRC5 [136], PTX3 [137], FAP ( broblast activation protein alpha) [138] and CAT (catalase) [139] were linked with the development of in uenza viral infection, but these genes may be associated with progression of SARS-CoV-2 infection as well.…”

Identification of potential mRNA panels for severe acute respiratory syndrome coronavirus 2 (COVID-19) diagnosis and treatment using microarray dataset and bioinformatics methods

“…Novel biomarkers such as KLRK1, IKZF3, ZBTB16, CLEC7A, C2 (complement C2), IKZF1, LCP2, KLRC1, GFI1, CCRL2 and MAP4K2 were highly expressed and might be involved in progression of SARS-CoV-2 infection. Studies have reported that low expression of enriched genes such as IRGM (immunity-related GTPase M) (Hansen et al 2017 ), MASP1 (El Saadany et al 2011 ), CD244 (Raziorrouh et al 2010 ), MBL2 (Spector et al 2010 ), CD46 (Gaggar et al 2003 ), C4A (Imakiire et al 2012 ), C9 (Kim et al 2013 ), ZEB1 (Lacher et al 2011 ), ICAM2 (Wang et al 2009), BTLA (B and T lymphocyte associated) (Cai et al 2013 ), CD1A (Sacchi et al 2007 ), CD19 (Zehender et al 1997 ), ICAM5 (Wei et al 2016 ), CD34 (Fahrbach et al 2007 ), CD48 (Ezinne et al 2014 ), CD59 (Amet et al 2012 ), CD74 (Le Noury et al 2015 ) and DEFB1 (Estrada-Aguirre et al 2014 ) were linked with development of various viral infections, but low expression of these genes may be liable for progression of SARS-CoV-2 infection. Recent studies reported that enriched genes such as IDO1 (Fox et al 2015 ), CD55 (Li et al 2016), PTPN22 (Crabtree et al 2016 ), FCGR2A (Maestri et al 2016 ), CARD9 (Uematsu et al 2015 ), MIF (macrophage migration inhibitory factor) (Arndt et al 2002 ) and PLAU (plasminogen activator, urokinase) (Sidenius et al 2000 ) were low expressed in influenza virus infection, but decrease expression of these genes may be key for progression of SARS-CoV-2 infection.…”

Bioinformatics analysis of expression profiling by high throughput sequencing for identification of potential key genes among SARS-CoV-2/COVID 19

“…Similarly, GO enrichment analysis, many up and down regulated genes may play a very key role in progression of SARS-CoV-2 infection. Enriched genes such as IFNL4 [116], ZFP36 [117], CD274 [118], MIR21 [119], CYP1A1 [120], CMPK2 [121], C4A [122], SERPINE1 [123], CCRL2 [124], CD69 [125], FAH (fumarylacetoacetate hydrolase) [126], ERFE (erythroferrone) [127], SERINC5 [128], ADI1 [129], AP2M1 [130], PRIMPOL (primase and DNA directed polymerase) [131], BIRC5 [132] and TF (transferrin) [133] were responsible for advancement of various viral infections, but these genes may be involved in progression of SARS-CoV-2 infection. Enriched genes such as APOBEC3G [134], NLRC5 [135], PTX3 [136], FAP ( broblast activation protein alpha) [137] and CAT (catalase) [138] were linked with development of in uenza viral infection, but these genes may be associated with progression of SARS-CoV-2 infection.…”