There is increasing evidence that several genes are associated with an increased risk of type 2 diabetes (T2D); genome-wide association investigations and whole-genome re‑sequencing investigations offer a useful approach for the identification of genes involved in common human diseases. To further investigate which polymorphisms confer susceptibility to T2D, the present study screened for high‑contribution susceptibility gene variants Chinese patients with T2D using whole‑genome re‑sequencing with DNA pooling. In total, 100 Chinese individuals with T2D and 100 healthy Chinese individuals were analyzed using whole‑genome re‑sequencing using DNA pooling. To minimize the likelihood of systematic bias in sampling, paired‑end libraries with an insert size of 500 bp were prepared for in T2D in all samples, which were then subjected to whole‑genome sequencing. Each library contained four lanes. The average sequencing depth was 35.70. In the present study, 1.36 GB of clean sequence data were generated, and the resulting calculated T2D genome consensus sequence covered 99.88% of the hg19 sequence. A total of 3,974,307 single nucleotide polymorphisms were identified, of which 99.88% were in the dbSNP database. The present study also found 642,189 insertions and deletions, 5,590 structure variants (SVs), 4,713 copy number variants (CNVs) and 13,049 single nucleotide variants. A total of 1,884 somatic CNVs and 74 somatic SVs were significantly different between the cases and controls. Therefore, the present study provided validation of whole‑genome re‑sequencing using the DNA pooling approach. It also generated a whole-genome re-sequencing genotype database for future investigations of T2D.

Over-expression of TROP2 (the trophoblast cell surface antigen 2) was reported to predict poor prognosis in various solid tumors in number of studies. However, the results remained not comprehensive. Therefore, we here carried out this meta-analysis of relevant studies published on this topic to quantitatively evaluate the clinicopathological significance of TROP2 in solid tumors. Relevant articles were identified through searching the PubMed, Web of Science and Embase database. The primary outcomes were overall survival (OS) and disease-free survival (DFS). In this meta-analysis, 16 studies involving 2,569 participants were included, and we drew the conclusion that TROP2 overexpression was significantly associated with poor OS (pooled HR = 1.896, 95% CI = 1.599-2.247, P < 0.001) and short DFS (pooled HR = 2.336, 95% CI = 1.596-3.419, P < 0.001). Furthermore, the subgroup analysis revealed that the associations between TROP2 overexpression and the outcome endpoints (OS or DFS) were significant in in patients with female genital system neoplasms, as well in gastrointestine neoplasms. In addition, subgroup analysis found no difference HR across populations of different descent.Taken together, TROP2 overexpression was associated with poor survival in human solid tumors. TROP2 may be a valuable prognosis predictive biomarker and a potential therapeutic target in human solid tumors.

The T-cell receptor (TCR) repertoire is a mirror of the human immune system that reflects processes caused by infections, cancer, autoimmunity, and aging. Next-generation sequencing has become a powerful tool for deep TCR profiling. Herein, we used this technology to study the repertoire features of TCR beta chain in the blood of healthy individuals.Peripheral blood samples were collected from 10 healthy donors. T cells were isolated with anti-human CD3 magnetic beads according to the manufacturer's protocol. We then combined multiplex-PCR, Illumina sequencing, and IMGT/High V-QUEST to analyze the characteristics and polymorphisms of the TCR.Most of the individual T cell clones were present at very low frequencies, suggesting that they had not undergone clonal expansion. The usage frequencies of the TCR beta variable, beta joining, and beta diversity gene segments were similar among T cells from different individuals. Notably, the usage frequency of individual nucleotides and amino acids within complementarity-determining region (CDR3) intervals was remarkably consistent between individuals. Moreover, our data show that terminal deoxynucleotidyl transferase activity was biased toward the insertion of G (31.92%) and C (27.14%) over A (21.82%) and T (19.12%) nucleotides.Some conserved features could be observed in the composition of CDR3, which may inform future studies of human TCR gene recombination.

FTY720, a new chemical substance derived from the ascomycete Isaria sinclairii, is used for treating multiple sclerosis, renal cancer, and asthma. Sphingosine 1-phosphate (S1P) is a bioactive sphingolipid metabolite and exists in red blood cells. FTY720 is a synthetic S1P analog which can block S1P evoking physiological effects. Recently studies show that S1P was participating in activated inflammation cells induced renal injury. The objective of this study was to assess the protective effect of FTY720 on kidney damage and the potential mechanism of FTY720 which alleviate podocyte injury in chronic kidney disease. In this study, we selected 40 patients with IgA nephropathy and examined their clinical characteristics. Ang II-infusion rat renal injury model was established to evaluate the glomeruli and tubulointerstitial lesion. The result showed that the concentration of S1P in serum and urine was positively correlated with IgA nephropathy patients' renal injury. FTY720 could reduce renal histological lesions induced by Ang II-infusion in rats. Moreover, FTY720 decreased S1P synthesis in Ang II-infusion rats via downregulation of inflammatory cytokines including TNF-α and IL-6. In addition, FTY720 alleviated exogenous S1P-induced podocyte damage. In conclusion, FTY720 is able to attenuate S1P-induced podocyte damage via reducing inflammatory cytokines.

CIP2A, cancerous inhibitor of protein phosphatase 2A, was initially recognized as an oncoprotein. Recently several studies revealed that CIP2A could function as a prognosis biomarker, however, the result remained not comprehensive, partly due to small number of patients included individually. Here we carried out a meta-analysis of published studies to assess the prognostic significance of CIP2A in solid tumors. All eligible studies were identified through searching PubMed, Embase and Web of Science database. In this meta-analysis, 22 studies involving 4,579 participants were included, and we verified that CIP2A over-expression was significantly related with poor overall survival (pooled HR = 1.844, 95% CI = 1.528-2.225, P<0.001) and short disease free survival (pooled HR = 1.808, 95% CI = 1.591-2.055, P<0.001) in solid tumors. Additionally, subgroup analysis suggested that the trend of a poor overall survival with an increased CIP2A expression was present in East-Asian and European patients, as well as in lung cancer and colorectal cancer. To sum up, CIP2A over-expression was associated with poor survival in human solid tumors and might be a predictive factor of poor prognosis.

The present study aims to evaluate the potential of transcriptomic profiles in evaluating the impacts of complex mixtures of pollutants at environmentally relevant concentrations on aquatic vertebrates. The changes in gene expression were determined using microarray in the liver of male zebrafish (Danio rerio) exposed to surface water collected from selected locations on the Hun River, China. The numbers of differentially expressed genes (DEGs) in each treatment ranged from 728 to 3292, which were positively correlated with chemical oxygen demand (COD). Predominant transcriptomic responses included peroxisome proliferator-activated receptors (PPAR) signaling and steroid biosynthesis. Key pathways in immune system were also affected. Notably, two human diseases related pathways, insulin resistance and Salmonella infection were enriched. Clustering analysis and principle component analysis with DEGs differentiated the upstream and downstream site of Shenyang City, and the mainstream and the tributary sites near the junction. Comparison the gene expression profiles of zebrafish exposed to river surface water with those to individual chemicals found higher similarity of the river water with estradiol than several other organic pollutants and metals. Results suggested that the transcriptomic profiles of zebrafish is promising in differentiating surface water with pollution gradient and different discharges and in providing valuable information to support discharge management.

Amyotrophic lateral sclerosis (ALS) is a late-onset fatal neurodegenerative disorder that is predicted to increase across the globe by ~70% in the following decades. Understanding the disease causal mechanism underlying ALS and identifying modifiable risks factors for ALS hold the key for the development of effective preventative and treatment strategies. Here, we investigate the causal effects of four blood lipid traits that include high-density lipoprotein, low-density lipoprotein (LDL), total cholesterol and triglycerides on the risk of ALS. By leveraging instrument variables from multiple large-scale genome-wide association studies in both European and East Asian populations, we carry out one of the largest and most comprehensive Mendelian randomization analyses performed to date on the causal relationship between lipids and ALS. Among the four lipids, we found that only LDL is causally associated with ALS and that higher LDL level increases the risk of ALS in both the European and East Asian populations. Specifically, the odds ratio of ALS per 1 standard deviation (i.e. 39.0 mg/dL) increase of LDL is estimated to be 1.14 [95% confidence interval (CI), 1.05-1.24; P = 1.38E-3] in the European population and 1.06 (95% CI, 1.00-1.12; P = 0.044) in the East Asian population. The identified causal relationship between LDL and ALS is robust with respect to the choice of statistical methods and is validated through extensive sensitivity analyses that guard against various model assumption violations. Our study provides important evidence supporting the causal role of higher LDL on increasing the risk of ALS, paving ways for the development of preventative strategies for reducing the disease burden of ALS across multiple nations.

Genome-wide association studies (GWAS) have identified multiple causal genes associated with amyotrophic lateral sclerosis (ALS); however, the genetic architecture of ALS remains completely unknown and a large number of causal genes have yet been discovered. To full such gap in part, we implemented an integrative analysis of transcriptome-wide association study (TWAS) for ALS to prioritize causal genes with summary statistics from 80,610 European individuals and employed 13 GTEx brain tissues as reference transcriptome panels. The summary-level TWAS analysis with single brain tissue was first undertaken and then a flexible p-value combination strategy, called summary data-based Cauchy Aggregation TWAS (SCAT), was proposed to pool association signals from single-tissue TWAS analysis while protecting against highly positive correlation among tests. Extensive simulations demonstrated SCAT can produce well-calibrated p-value for the control of type I error and was often much more powerful to identify association signals across various scenarios compared with single-tissue TWAS analysis. Using SCAT, we replicated three ALS-associated genes (i.e., ATXN3, SCFD1, and C9orf72) identified in previous GWASs and discovered additional five genes (i.e., SLC9A8, FAM66D, TRIP11, JUP, and RP11-529H20.6) which were not reported before. Furthermore, we discovered the five associations were largely driven by genes themselves and thus might be new genes which were likely related to the risk of ALS. However, further investigations are warranted to verify these results and untangle the pathophysiological function of the genes in developing ALS.

Associations between type 2 diabetes (T2D) and amyotrophic lateral sclerosis (ALS) were discovered in observational studies in both European and East Asian populations. However, whether such associations are causal remains largely unknown.

Multidrug-resistant organisms (MDROs) have emerged as an important cause of poor prognoses of patients in the intensive care unit (ICU). This study aimed to establish an easy-to-use nomogram for predicting the occurrence of MDRO colonization or infection in ICU patients.

Long non-coding RNAs (lncRNAs) are emerging as important regulators in the modulation of virus infection by targeting mRNA transcription. However, their roles in chronic hepatitis B (CHB) remain to be elucidated.

In the past few years many prediction approaches have been proposed and widely employed in high dimensional genetic data for disease risk evaluation. However, those approaches typically ignore in model fitting the important group structures that naturally exists in genetic data.

The adaptive immune system uses several strategies to generate a repertoire of T cell receptors (TCR) with sufficient diversity to recognize the universe of potential pathogens. However, it remains unclear how differences in the T cell receptor (TCR) contribute to heterogeneity in T cell state. In this study, we used polychromatic flow cytometry to isolate highly pure CD4+/CD8+ naive and memory T cells, and applied deep sequencing to characterize corresponding TCR β-chain (TCRβ) complementary-determining region 3 (CDR3) repertoires. We find that shorter TCRβ CDR3s with fewer insertions were highly enriched during thymic selection. Antigen-experienced T cells (memory T cells) harbor shorter CDR3s vs. naive T cells. Moreover, the public TCRβ CDR3 clonotypes within cell subsets or interindividual tend to have shorter CDR3 length and a significantly larger size compared with "private" clonotypes. Taken together, shorter CDR3s highly enriched during thymic selection and antigen-driven selection, and further enriched in public T-cell responses. These results indicated that it may be evolutionary pressures drive short CDR3s to recognize most of antigen in nature.

Background: Smoking addiction is a major public health issue which causes a series of chronic diseases and mortalities worldwide. We aimed to explore the most discriminative gray matter regions between heavy smokers and healthy controls with a data-driven multivoxel pattern analysis technique, and to explore the methodological differences between multivoxel pattern analysis and voxel-based morphometry. Methods: Traditional voxel-based morphometry has continuously contributed to finding smoking addiction-related regions on structural magnetic resonance imaging. However, voxel-based morphometry has its inherent limitations. In this study, a multivoxel pattern analysis using a searchlight algorithm and support vector machine was applied on structural magnetic resonance imaging to identify the spatial pattern of gray matter volume in heavy smokers. Results: Our proposed method yielded a voxel-wise accuracy of at least 81% for classifying heavy smokers from healthy controls. The identified regions were primarily located at the temporal cortex and prefrontal cortex, occipital cortex, thalamus (bilateral), insula (left), anterior and median cingulate gyri, and precuneus (left). Conclusions: Our results suggested that several regions, which were seldomly reported in voxel-based morphometry analysis, might be latently correlated with smoking addiction. Such findings might provide insights for understanding the mechanism of chronic smoking and the creation of effective cessation treatment. Multivoxel pattern analysis can be efficient in locating brain discriminative regions which were neglected by voxel-based morphometry.

Clinical and epidemiological studies have suggested systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA) are comorbidities and common genetic etiologies can partly explain such coexistence. However, shared genetic determinations underlying the two diseases remain largely unknown.

In two-sample Mendelian randomization (MR) studies, sex instrumental heterogeneity is an important problem needed to address carefully, which however is often overlooked and may lead to misleading causal inference.

Cardiovascular diseases (CVDs) remain the main cause of morbidity and mortality worldwide. The pathological mechanism and underlying biological processes of these diseases with metabolites remain unclear. In this study, we conducted a two-sample Mendelian randomization (MR) analysis to evaluate the causal effect of metabolites on these diseases by making full use of the latest GWAS summary statistics for 486 metabolites and six major CVDs. Extensive sensitivity analyses were implemented to validate our MR results. We also conducted linkage disequilibrium score regression (LDSC) and colocalization analysis to investigate whether MR findings were driven by genetic similarity or hybridization between LD and disease-associated gene loci. We identified a total of 310 suggestive associations across all metabolites and CVDs, and finally obtained four significant associations, including bradykinin, des-arg(9) (odds ratio [OR] = 1.160, 95% confidence intervals [CIs]: 1.080-1.246, false discovery rate [FDR] = 0.022) on ischemic stroke, N-acetylglycine (OR = 0.946, 95%CIs: 0.920-0.973, FDR = 0.023), X-09026 (OR = 0.845, 95%CIs: 0.779-0.916, FDR = 0.021) and X-14473 (OR = 0.938, 95%CIs = 0.907-0.971, FDR = 0.040) on hypertension. Sensitivity analyses showed that these causal associations were robust, the LDSC and colocalization analyses demonstrated that the identified associations were unlikely confused by LD. Moreover, we identified 15 important metabolic pathways might be involved in the pathogenesis of CVDs. Overall, our work identifies several metabolites that have a causal relationship with CVDs, and improves our understanding of the pathogenesis and treatment strategies for these diseases.

Background: Coronavirus disease 2019 (COVID-19) is a worldwide emergency, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Long non-coding RNAs (lncRNAs) do not encode proteins but could participate in immune response. Methods: In our study, 39 COVID-19 patients were enrolled. The microarray of peripheral blood mononuclear cells from healthy and COVID-19 patients was applied to identify the expression profiles of lncRNAs and mRNAs. Identified differentially expressed (DE) lncRNAs were validated by qRT-PCR. Then, the lncRNA-mRNA network was constructed and visualized using Cytoscape (3.6.1) based on the Pearson correlation coefficient. The enrichment of DE mRNAs was analyzed using Metascape. The difference in frequencies of immune cells and cytokines was detected using CIBERSORT and ImmPort based on DE mRNAs. Results: All patients with COVID-19 displayed lymphopenia, especially in T cells, and hyper-inflammatory responses, including IL-6 and TNF-α. Four immune-related lncRNAs in COVID-19 were found and further validated, including AC136475.9, CATG00000032642.1, G004246, and XLOC_013290. Functional analysis enriched in downregulation of the T-cell receptor and the antigen processing and presentation as well as increased apoptotic proteins, which could lead to T-cell cytopenia. In addition, they participated in monocyte remodeling, which contributed to releasing cytokines and chemokines and then recruiting more monocytes and aggravating the clinical severity of COVID-19 patients. Conclusion: Taken together, four lncRNAs were in part of immune response in COVID-19, which was involved in the T-cell cytopenia by downregulating the antigen processing and presentation, the T-cell receptor, and an increased proportion of monocytes, with a distinct change in cytokines and chemokines.

Previous studies demonstrated a positive relationship between birthweight and breast cancer; however, inconsistent, sometimes even controversial, observations also emerged, and the nature of such relationship remains unknown.

Adverse childhood experiences (ACEs) and anxiety-depression co-morbidity are attracting widespread attention. Previous studies have shown the relationship between individual psychiatric disorders and ACEs. This study will analyze the correlation between anxiety-depression co-morbidity and different levels of ACEs.