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Background We aim to investigate the profile of acute antibody response in COVID-19 patients, and provide proposals for the usage of antibody test in clinical practice.Methods A multi-center cross-section study (285 patients) and a single-center follow-up study (63 patients) were performed to investigate the feature of acute antibody response to SARS-CoV-2. A cohort of 52 COVID-19 suspects and 64 close contacts were enrolled to evaluate the potentiality of the antibody test. ResultsThe positive rate for IgG reached 100% around 20 days after symptoms onset.The median day of seroconversion for both lgG and IgM was 13 days after symptoms onset. Seroconversion of IgM occurred at the same time, or earlier, or later than that of IgG. IgG levels in 100% patients (19/19) entered a platform within 6 days after seroconversion. The criteria of "IgG seroconversion" and "≥ 4-fold increase in the IgG titers in sequential samples" together diagnosed 82.9% (34/41) of the patients.Antibody test aided to confirm 4 patients with COVID-19 from 52 suspects who failed to be confirmed by RT-PCR and 7 patients from 148 close contacts with negative RT-PCR. ConclusionIgM and IgG should be detected simultaneously at the early phase of infection. The serological diagnosis criterion of seroconversion or the "≥ 4-fold increase in the IgG titer" is suitable for a majority of COVID-19 patients. Serologic test is helpful for the diagnosis of SARS-CoV-2 infection in suspects and close contacts.

In this study, we analyzed the clinical significance of ferroptosis-related genes (FRGs) in 32 cancer types in the GSCA database. We detected a 2-82% mutation rate among 36 FRGs. In clear cell renal cell carcinoma (ccRCC; n=539) tissues from the The Cancer Genome Atlas database, 30 of 36 FRGs were differentially expressed (up- or down-regulated) compared to normal kidney tissues (n=72). Consensus clustering analysis identified two clusters of FRGs based on similar co-expression in ccRCC tissues. We then used LASSO regression analysis to build a new survival model based on five risk-related FRGs ( CARS, NCOA4, FANCD2, HMGCR, and SLC7A11 ). Receiver operating characteristic curve analysis confirmed good prognostic performance of the new survival model with an area under the curve of 0.73. High FANCD2, CARS, and SLC7A11 expression and low HMGCR and NCOA4 expression were associated with high-risk ccRCC patients. Multivariate analysis showed that risk score, age, stage, and grade were independent risk factors associated with prognosis in ccRCC. These findings demonstrate that this five risk-related FRG-based survival model accurately predicts prognosis in ccRCC patients, and suggest FRGs are potential prognostic biomarkers and therapeutic targets in several cancer types.

The major histocompatibility complex (MHC) is one of the most variable and gene-dense regions of the human genome. Most studies of the MHC, and associated regions, focus on minor variants and HLA typing, many of which have been demonstrated to be associated with human disease susceptibility and metabolic pathways. However, the detection of variants in the MHC region, and diagnostic HLA typing, still lacks a coherent, standardized, cost effective and high coverage protocol of clinical quality and reliability. In this paper, we presented such a method for the accurate detection of minor variants and HLA types in the human MHC region, using high-throughput, high-coverage sequencing of target regions. A probe set was designed to template upon the 8 annotated human MHC haplotypes, and to encompass the 5 megabases (Mb) of the extended MHC region. We deployed our probes upon three, genetically diverse human samples for probe set evaluation, and sequencing data show that ∼97% of the MHC region, and over 99% of the genes in MHC region, are covered with sufficient depth and good evenness. 98% of genotypes called by this capture sequencing prove consistent with established HapMap genotypes. We have concurrently developed a one-step pipeline for calling any HLA type referenced in the IMGT/HLA database from this target capture sequencing data, which shows over 96% typing accuracy when deployed at 4 digital resolution. This cost-effective and highly accurate approach for variant detection and HLA typing in the MHC region may lend further insight into immune-mediated diseases studies, and may find clinical utility in transplantation medicine research. This one-step pipeline is released for general evaluation and use by the scientific community.

Excessive monocyte activation with the development of excessive or uncontrolled release of proinflammatory cytokines often results in host tissue injury and even death in patients with pneumonia caused by the 2019 novel coronavirus. However, the changes of cytokine profiles of coronavirus disease 2019 (COVID‐19) patients, as well as the underlying mechanisms that are involved, remain unknown. Using a cytokine array containing 174 inflammation‐related cytokines, we found significantly altered cytokine profiles in severe COVID‐19 patients compared with those in mild patients or healthy controls, and identified leptin, CXCL‐10, IL‐6, IL‐10, IL‐12, and TNF‐α as the top differentially expressed cytokines. Notably, leptin showed high consistency with CXCL‐10 and TNF‐α in predicting disease severity, and correlated with body mass index, decreased lymphocyte counts, and disease progression. Further analysis demonstrated that monocytes in severe patients with higher leptin levels were inclined toward M1 polarization. Mechanistic studies revealed that leptin synergistically up‐regulated expression levels of inflammatory cytokines and surface markers with IL‐6 in monocytes through STAT3 and NF‐κB signaling pathways. Collectively, our results suggest that overweight COVID‐19 patients were prone to have higher leptin levels, which further activated monocytes, resulting in amplified or dysregulated immune responses. Taken together, our findings argue that leptin correlates severity of COVID‐19 and may indicate a possible mechanism by which overweight patients have a greater tendency to develop severe conditions.

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Growing evidence indicates that clear cell renal cell carcinoma (ccRCC) is a metabolism-related disease. Changes in fatty acid (FA) and cholesterol metabolism play important roles in ccRCC development. As a nuclear transcription factor receptor, Liver X receptor (LXR) regulates a variety of key molecules associated with FA synthesis and cholesterol transport. Therefore, targeting LXR may provide new therapeutic targets for ccRCC. However, the potential regulatory effect and molecular mechanisms of LXR in ccRCC remain unknown. In the present study, we found that both an LXR agonist and an XLR inverse agonist could inhibit proliferation and colony formation and induce apoptosis in ccRCC cells. We observed that the LXR agonist LXR623 downregulated the expression of the low-density lipoprotein receptor (LDLR) and upregulated the expression of ABCA1, which resulted in reduced intracellular cholesterol and apoptosis. The LXR inverse agonist SR9243 downregulated the FA synthesis proteins sterol regulatory element-binding protein 1c (SREBP-1c), fatty acid synthase (FASN) and stearoyl-coA desaturase 1 (SCD1), causing a decrease in intracellular FA content and inducing apoptosis in ccRCC cells. SR9243 and LXR623 induced apoptosis in ccRCC cells but had no killing effect on normal renal tubular epithelial HK2 cells. We also found that SRB1-mediated high-density lipoprotein (HDL) in cholesterol influx is the cause of high cholesterol in ccRCC cells. In conclusion, our data suggest that an LXR inverse agonist and LXR agonist decrease the intracellular FA and cholesterol contents in ccRCC to inhibit tumour cells but do not have cytotoxic effects on non-malignant cells. Thus, LXR may be a safe therapeutic target for treating ccRCC patients.

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