Whole exome sequencing analyses identified novel genes for Alzheimer's disease and related dementia.

INTRODUCTION: The heritability of Alzheimer's disease (AD) is estimated to be 58%-79%. However, known genes can only partially explain the heritability. METHODS: Here, we conducted gene-based exome-wide association study (ExWAS) of rare variants and single-variant ExWAS of common variants, utilizing data of 54,569 clinically diagnosed/proxy AD and related dementia (ADRD) and 295,421 controls from the UK Biobank. RESULTS: Gene-based ExWAS identified 11 genes predicting a higher ADRD risk, including five novel ones, namely FRMD8, DDX1, DNMT3L, MORC1, and TGM2, along with six previously reported ones, SORL1, GRN, PSEN1, ABCA7, GBA, and ADAM10. Single-variant ExWAS identified two ADRD-associated novel genes, SLCO1C1 and NDNF. The identified genes were predominantly enriched in amyloid-ß process pathways, microglia, and brain regions like hippocampus. The druggability evidence suggests that DDX1, DNMT3L, TGM2, SLCO1C1, and NDNF could be effective drug targets. DISCUSSION: Our study contributes to the current body of evidence on the genetic etiology of ADRD. HIGHLIGHTS: Gene-based analyses of rare variants identified five novel genes for Alzheimer's disease and related dementia (ADRD), including FRMD8, DDX1, DNMT3L, MORC1, and TGM2. Single-variant analyses of common variants identified two novel genes for ADRD, including SLCO1C1 and NDNF. The identified genes were predominantly enriched in amyloid-ß process pathways, microglia, and brain regions like hippocampus. DDX1, DNMT3L, TGM2, SLCO1C1, and NDNF could be effective drug targets.

Whole exome sequencing analyses reveal novel genes in telomere length and their biomedical implications.

Telomere length is a putative biomarker of aging and is associated with multiple age-related diseases. There are limited data on the landscape of rare genetic variations in telomere length. Here, we systematically characterize the rare variant associations with leukocyte telomere length (LTL) through exome-wide association study (ExWAS) among 390,231 individuals in the UK Biobank. We identified 18 robust rare-variant genes for LTL, most of which estimated effects on LTL were significant (> 0.2 standard deviation per allele). The biological functions of the rare-variant genes were associated with telomere maintenance and capping and several genes were specifically expressed in the testis. Three novel genes (ASXL1, CFAP58, and TET2) associated with LTL were identified. Phenotypic association analyses indicated significant associations of ASXL1 and TET2 with cancers, age-related diseases, blood assays, and cardiovascular traits. Survival analyses suggested that carriers of ASXL1 or TET2 variants were at increased risk for cancers; diseases of the circulatory, respiratory, and genitourinary systems; and all-cause and cause-specific deaths. The CFAP58 carriers were at elevated risk of deaths due to cancers. Collectively, the present whole exome sequencing study provides novel insights into the genetic landscape of LTL, identifying novel genes associated with LTL and their implications on human health and facilitating a better understanding of aging, thus pinpointing the genetic relevance of LTL with clonal hematopoiesis, biomedical traits, and health-related outcomes.

Mendelian randomization evidence based on European ancestry for the causal effects of leukocyte telomere length on prostate cancer.

BACKGROUND: Several lines of evidence suggest that leukocyte telomere length (LTL) can affect the development of prostate cancer (PC). METHODS: Here, we employed single nucleoside polymorphisms (SNPs) as instrumental variables (IVs) for LTL (n = 472,174) and conducted Mendelian randomization analysis to estimate their causal impact on PCs (79,148 patients/61,106 controls and 6311 patients/88,902 controls). RESULTS: Every 1-s.d extension of LTL increased the risk of PCs by 34%. Additionally, the analysis of candidate mediators between LTL and PCs via two-step Mendelian randomization revealed that among the 23 candidates, Alzheimer's disease, liver iron content, sex hormone binding global levels, naive CD4-CD8-T cell% T cell, and circulating leptin levels played substantial mediating roles. There is no robust evidence to support the reverse causal relationship between LTL and the selected mediators of PCs. Adjusting for the former four mediators, rather than adjusting for circulating leptin levels, decreased the impact of LTL on PCs. CONCLUSION: This study provides potential intervention measures for preventing LTL-induced PCs.

Comprehensive analysis of T-cell regulatory factors and tumor immune microenvironment in stomach adenocarcinoma.

BACKGROUND: Gastric cancer (GC) is one of the most prevalent malignant tumors worldwide and is associated with high morbidity and mortality rates. However, the specific biomarkers used to predict the postoperative prognosis of patients with gastric cancer remain unknown. Recent research has shown that the tumor microenvironment (TME) has an increasingly positive effect on anti-tumor activity. This study aims to build signatures to study the effect of certain genes on gastric cancer. METHODS: Expression profiles of 37 T cell-related genes and their TME characteristics were comprehensively analyzed. A risk signature was constructed and validated based on the screened T cell-related genes, and the roles of hub genes in GC were experimentally validated. RESULTS: A novel T cell-related gene signature was constructed based on CD5, ABCA8, SERPINE2, ESM1, SERPINA5, and NMU. The high-risk group indicated lower overall survival (OS), poorer immune efficacy, and higher drug resistance, with SERPINE2 promoting GC cell proliferation, according to experiments. SERPINE2 and CXCL12 were significantly correlated, indicating poor OS via the Youjiang cohort. CONCLUSIONS: This study identified T cell-related genes in patients with stomach adenocarcinoma (STAD) for prognosis estimation and proposed potential immunotherapeutic targets for STAD.

Large-scale whole-exome sequencing of neuropsychiatric diseases and traits in 350,770 adults.

While numerous genomic loci have been identified for neuropsychiatric conditions, the contribution of protein-coding variants has yet to be determined. Here we conducted a large-scale whole-exome-sequencing study to interrogate the impact of protein-coding variants on 46 neuropsychiatric diseases and 23 traits in 350,770 adults from the UK Biobank. Twenty new genes were associated with neuropsychiatric diseases through coding variants, among which 16 genes had impacts on the longitudinal risks of diseases. Thirty new genes were associated with neuropsychiatric traits, with SYNGAP1 showing pleiotropic effects across cognitive function domains. Pairwise estimation of genetic correlations at the coding-variant level highlighted shared genetic associations among pairs of neurodegenerative diseases and mental disorders. Lastly, a comprehensive multi-omics analysis suggested that alterations in brain structures, blood proteins and inflammation potentially contribute to the gene-phenotype linkages. Overall, our findings characterized a compendium of protein-coding variants for future research on the biology and therapeutics of neuropsychiatric phenotypes.

Extracellular vesicles related gene HSPH1 exerts anti-tumor effects in prostate cancer via promoting the stress response of CD8 + T cells.

BACKGROUND: T cell stress response state (TSTR), as a novel immune concept previous studies have proposed, has not yet been explored in prostate cancer (PC). As a type of cellular efflux, exosomes play important roles in the occurrence and development of PC. METHOD: Here, we conducted a combined analysis on extracellular vesicle related genes (EVRGs) in PC using data from single-cell RNA (scRNA), spatial transcriptome (ST), and bulk RNA sequencing. RESULT: Preliminary findings have revealed that heat shock protein family H (Hsp110) member 1 (HSPH1) possesses two identities, one being EVRGs and the other being a member of the heat shock protein family involved in TSTR, which may promote the differentiation of conventional T cells towards Th1 or Th2 cells through the pathway of IL2-MYC-IL2RA, thereby promoting the increase of CD8 + T cells in the tumor area, especially in the invasive zone, and inhibiting the invasion of PCs. We also notice the negative response of HSPH1 + CD8 + T cell related genes in immune checkpoint blockade (ICB). Western blot (WB) and droplet digital Polymerase Chain Reaction (ddPCR) demonstrated that the mRNA and protein levels of HSPH1 in EVs of PCs were significantly higher than those in adjacent tissues. CONCLUSION: Results above indicate the potential of HSPH1 as a critical therapeutic target in PC.

Plasma metabolic profiles predict future dementia and dementia subtypes: a prospective analysis of 274,160 participants.

BACKGROUND: Blood-based biomarkers for dementia are gaining attention due to their non-invasive nature and feasibility in regular healthcare settings. Here, we explored the associations between 249 metabolites with all-cause dementia (ACD), Alzheimer's disease (AD), and vascular dementia (VaD) and assessed their predictive potential. METHODS: This study included 274,160 participants from the UK Biobank. Cox proportional hazard models were employed to investigate longitudinal associations between metabolites and dementia. The importance of these metabolites was quantified using machine learning algorithms, and a metabolic risk score (MetRS) was subsequently developed for each dementia type. We further investigated how MetRS stratified the risk of dementia onset and assessed its predictive performance, both alone and in combination with demographic and cognitive predictors. RESULTS: During a median follow-up of 14.01 years, 5274 participants developed dementia. Of the 249 metabolites examined, 143 were significantly associated with incident ACD, 130 with AD, and 140 with VaD. Among metabolites significantly associated with dementia, lipoprotein lipid concentrations, linoleic acid, sphingomyelin, glucose, and branched-chain amino acids ranked top in importance. Individuals within the top tertile of MetRS faced a significantly greater risk of developing dementia than those in the lowest tertile. When MetRS was combined with demographic and cognitive predictors, the model yielded the area under the receiver operating characteristic curve (AUC) values of 0.857 for ACD, 0.861 for AD, and 0.873 for VaD. CONCLUSIONS: We conducted the largest metabolome investigation of dementia to date, for the first time revealed the metabolite importance ranking, and highlighted the contribution of plasma metabolites for dementia prediction.

Identifying High Gleason Score Prostate Cancer by Prostate Fluid Metabolic Fingerprint-Based Multi-Modal Recognition.

Prostate cancer (PCa) is the second most common cancer in males worldwide. The Gleason scoring system, which classifies the pathological growth pattern of cancer, is considered one of the most important prognostic factors for PCa. Compared to indolent PCa, PCa with high Gleason score (h-GS PCa, GS ≥ 8) has greater clinical significance due to its high aggressiveness and poor prognosis. It is crucial to establish a rapid, non-invasive diagnostic modality to decipher patients with h-GS PCa as early as possible. In this study, ferric nanoparticle-assisted laser desorption/ionization mass spectrometry (FeNPALDI-MS) to extract prostate fluid metabolic fingerprint (PSF-MF) is employed and combined with the clinical features of patients, such as prostate-specific antigen (PSA), to establish a multi-modal diagnosis assisted by machine learning. This approach yields an impressive area under the curve (AUC) of 0.87 to diagnose patients with h-GS, surpassing the results of single-modal diagnosis using only PSF-MF or PSA, respectively. Additionally, using various screening methods, six key metabolites that exhibit greater diagnostic efficacy (AUC = 0.96) are identified. These findings also provide insights into related metabolic pathways, which may provide valuable information for further elucidation of the pathological mechanisms underlying h-GS PCa.

Effects of exogenous steroid hormones on growth, body color, and gonadal development in the Opsariichthys bidens.

To investigate the effects of exogenous steroid hormones on growth, body color, and gonadal development in the Opsariichthys bidens (O. bidens), synthetic methyltestosterone (MT) and 17ß-estradiol (E2) were used for 28 days' treatment of 4-month-old O. bidens before the breeding season. Our results suggested that MT had a significant growth-promoting effect (P < 0.05), whereas E2 played an inhibitory role. On the body surface, the females in the MT group showed gray stripes, and the fish in other groups showed no obvious stripes. The males with MT treatment displayed brighter blue-green stripes compared to the CK and E2 groups. The histological analysis showed that the MT significantly promoted testes development in males, blocked oocyte development, and caused massive apoptosis in females, whereas the E2 group promoted ovarian development and inhibited testes development. Based on qRT-PCR analysis, in females, the expression of igf-1, dmrt1, and cyp19a1a genes revealed that E2 treatment resulted in down-regulation of igf-1 expression and up-regulation of cyp19a1a expression. In males, igf-1 and dmrt1 were significantly up-regulated after MT treatment, and E2 treatment led to down-regulation of igf-1. Therefore, this study demonstrates that MT and E2 play an important role in reversing the morphological sex characteristics of females and males.

Causal associations between gut microbiota, gut microbiota-derived metabolites, and cerebrovascular diseases: a multivariable Mendelian randomization study.

Background: Mounting evidence has demonstrated the associations between gut microbiota, gut microbiota-derived metabolites, and cerebrovascular diseases (CVDs). The major categories of CVD are ischemic stroke (IS), intracerebral hemorrhage (ICH), and subarachnoid hemorrhage (SAH). However, the causal relationship is still unclear. Methods: A two-sample Mendelian randomization (MR) study was conducted leveraging the summary data from genome-wide association studies. The inverse variance-weighted, maximum likelihood, weighted median, and MR.RAPS methods were performed to detect the causal relationship. Several sensitivity analyses were carried out to evaluate potential horizontal pleiotropy and heterogeneity. Finally, reverse MR analysis was conducted to examine the likelihood of reverse causality, and multivariable MR was performed to adjust the potential confounders. Results: We collected 1,505 host single nucleotide polymorphisms (SNPs) linked to 119 gut microbiota traits and 1,873 host SNPs associated with 81 gut metabolite traits as exposure data. Among these, three gut bacteria indicated an elevated risk of IS, two of ICH, and one of SAH. In contrast, five gut bacteria were associated with a reduced risk of IS, one with ICH, and one with SAH. Our study also demonstrated the potential causal associations between 11 gut microbiota-derived metabolites and CVD. Conclusions: This study provided evidence of the causal relationship between gut microbiota, gut microbiota-derived metabolites, and CVD, thereby offering novel perspectives on gut biomarkers and targeted prevention and treatment for CVD.

Construction of cuproptosis signature based on bioinformatics and experimental validation in clear cell renal cell carcinoma.

BACKGROUND: Cuproptosis was defined as a novel nonapoptotic cell death pathway and its potential function in clear cell renal cell carcinoma (ccRCC) remains unclear. METHODS: We obtained gene expression profiles, somatic mutation and corresponding clinical information of 881 ccRCC samples from 3 cohorts including the cancer genome atlas cohort, GSE29609 cohort and CheckMate 025 cohort. As described in the latest published article, we enrolled 16 genes as cuproptosis-related genes (CRGs). We explored the expression level, variants and copy number variation of the CRGs. Univariate and multi-variate regression were utilized to assess the prognostic significance of the CRGs. Non-negative matrix factorization was used to identify potential subgroup and gene set variation analysis was used to explore the potential biological functions. CIBERSORT, ESTIMATE algorithm and single sample gene set enrichment analysis were used to evaluate the tumor microenvironment. In vitro experiments including CCK-8, transwell and wound healing assays were utilized to explore the potential biological function of DLAT in ccRCC. RESULTS: We found that except for CDKN2A, the CRGs were positively associated with patients' OS. Cuproptosis cluster, cuproptosis gene cluster and cuproptosis score were established, respectively, and higher cuproptosis score was significantly associated with a worse OS in ccRCC (p < 0.001). The area under the receiver operating characteristic curve of the cuproptosis-related nomogram at 1 year, 3 years, 5 years was 0.858, 0.821 and 0.78, respectively. In addition, we found that the cuproptosis score was positively associated with PDCD1, CTLA4 expression level, thus the cuproptosis score may also reflect the dysfunction of tumor infiltrating immune cells. In vitro experiments indicated that overexpression of DLAT could inhibited the migration and proliferation ability of ccRCC cells. CONCLUSION: Our findings identify a novel cuproptosis-related signature and the cuproptosis characteristics may influence the anti-tumor immunity though complex regulating networks, and thus cuproptosis may play a role in developing novel therapeutic target of ccRCC.

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OBJECTIVES: Intracerebral hemorrhage (ICH) has the highest mortality and disability rates among various subtypes of stroke. Previous studies have shown that the gut microbiome (GM) is closely related to the risk factors and pathological basis of ICH. This study aims to explore the causal effect of GM on ICH and the potential mechanisms. METHODS: Genome wide association study (GWAS) data on GM and ICH were obtained from Microbiome Genome and International Stroke Genetics Consortium. Based on the GWAS data, we first performed Mendelian randomization (MR) analysis to evaluate the causal association between GM and ICH. Then, a conditional false discovery rate (cFDR) method was conducted to identify the pleiotropic variants. RESULTS: MR analysis showed that Pasteurellales, Pasteurellaceae, and Haemophilus were negatively correlated with the risk of ICH, whileVerrucomicrobiae, Verrucomicrobiales, Verrucomicrobiaceae, Akkermansia, Holdemanella, and LachnospiraceaeUCG010 were positively correlated with ICH. By applying the cFDR method, 3 pleiotropic loci (rs331083, rs4315115, and rs12553325) were found to be associated with both GM and ICH. CONCLUSIONS: There is a causal association and pleiotropic variants between GM and ICH.

Longitudinal change of gut microbiota in hypertensive disorders in pregnancy: a nested case-control and Mendelian randomization study.

Mounting evidence has shown that gut microbiota (GM) is related to hypertensive disorders in pregnancy (HDP), however, most studies only focused on one time point in pregnancy. In this study, we conducted a nested case-control study utilizing a follow-up cohort, resulting in the collection of 47 HDP patients and 30 healthy controls. The GM profiles were explored using 16S rRNA sequencing at three time points during pregnancy. The diversity analysis of GM showed no significant difference between HDP patients and controls, however, we found 21 differential GM during pregnancy. Trend analysis showed that there are statistical differences in the relative abundance of Thermomonas, Xanthomonas, and Phenylobacteriumat during pregnancy in the gestational hypertension group, and of Xanthomonas, Polycyclovorans, and Phenylobacterium in the control group. The correlation study found that six genera of GM are related to blood pressure. Furthermore, the MR analysis identified the causal relationship between Methanobrevibacter and pre-eclampsia (PE). This study first explored the longitudinal change of GM in HDP patients during pregnancy, found the differential GM, and detected the causal association. Our findings may promote the prevention and treatment of HDP from the perspective of GM and provide valuable insights into the pathogenesis of HDP.

Application of three-dimensional reconstruction technology in dentistry: a narrative review.

BACKGROUND: Three-dimensional(3D) reconstruction technology is a method of transforming real goals into mathematical models consistent with computer logic expressions and has been widely used in dentistry, but the lack of review and summary leads to confusion and misinterpretation of information. The purpose of this review is to provide the first comprehensive link and scientific analysis of 3D reconstruction technology and dentistry to bridge the information bias between these two disciplines. METHODS: The IEEE Xplore and PubMed databases were used for rigorous searches based on specific inclusion and exclusion criteria, supplemented by Google Academic as a complementary tool to retrieve all literature up to February 2023. We conducted a narrative review focusing on the empirical findings of the application of 3D reconstruction technology to dentistry. RESULTS: We classify the technologies applied to dentistry according to their principles and summarize the different characteristics of each category, as well as the different application scenarios determined by these characteristics of each technique. In addition, we indicate their development prospects and worthy research directions in the field of dentistry, from individual techniques to the overall discipline of 3D reconstruction technology, respectively. CONCLUSIONS: Researchers and clinicians should make different decisions on the choice of 3D reconstruction technology based on different objectives. The main trend in the future development of 3D reconstruction technology is the joint application of technology.

Gut microbiota and hypertensive disorders in pregnancy: evidence from the Mendelian randomization study.

BACKGROUND: Recent studies have shown that gut microbiota (GM) is related to hypertensive disorders in pregnancy (HDP). However, the causal relationship needs to be treated with caution due to confounding factors and reverse causation. METHODS: We obtained genetic variants from genome-wide association studies including GM (N = 18,340) in MiBioGen Consortium as well as HDP (7,686 cases/115,893 controls) and specific subtypes in FinnGen Consortium. Then, Inverse variance weighted, maximum likelihood, weighted median, MR-Egger, and MR.RAPS methods were applied to examine the causal association. Reverse Mendelian randomization (RMR) and multivariable MR were performed to confirm the causal direction and adjust the potential confounders, respectively. Furthermore, sensitivity analyses including Cochran's Q statistics, MR-Egger intercept, MR-PRESSO global test, and the leave-one-out analysis were conducted to detect the potential heterogeneity and horizontal pleiotropy. RESULTS: The present study found causalities between eight gut microbial genera and HDP. The HDP-associated gut microbial genera identified by MR analyses varied in different subtypes. Specifically, our study found causal associations of LachnospiraceaeUCG010, Olsenella, RuminococcaceaeUCG009, Ruminococcus2, Anaerotruncus, Bifidobacterium, and Intestinibacter with GH, of Eubacterium (ruminantium group), Eubacterium (ventriosum group), Methanobrevibacter, RuminococcaceaeUCG002, and Tyzzerella3 with PE, and of Dorea and RuminococcaceaeUCG010 with eclampsia, respectively. CONCLUSIONS: This study first applied the MR approach to detect the causal relationships between GM and specific HDP subtypes. Our findings may promote the prevention and treatment of HDP targeted on GM and provide valuable insights to understand the mechanism of HDP in different subtypes from the perspective of GM.

Investigating causal associations among gut microbiota, gut microbiota-derived metabolites, and gestational diabetes mellitus: a bidirectional Mendelian randomization study.

BACKGROUND: Previous studies have shown that gut microbiota (GM) and gut microbiota-derived metabolites are associated with gestational diabetes mellitus (GDM). However, the causal associations need to be treated with caution due to confounding factors and reverse causation. METHODS: This study obtained genetic variants from genome-wide association study including GM (N = 18,340), GM-derived metabolites (N = 7,824), and GDM (5,687 cases and 117,89 controls). To examine the causal association, several methods were utilized, including inverse variance weighted, maximum likelihood, weighted median, MR-Egger, and MR.RAPS. Additionally, reverse Mendelian Randomization (MR) analysis and multivariable MR were conducted to confirm the causal direction and account for potential confounders, respectively. Furthermore, sensitivity analyses were performed to identify any potential heterogeneity and horizontal pleiotropy. RESULTS: Greater abundance of Collinsella was detected to increase the risk of GDM. Our study also found suggestive associations among Coprobacter, Olsenella, Lachnoclostridium, Prevotella9, Ruminococcus2, Oscillibacte, and Methanobrevibacter with GDM. Besides, eight GM-derived metabolites were found to be causally associated with GDM. For the phenylalanine metabolism pathway, phenylacetic acid was found to be related to the risk of GDM. CONCLUSIONS: The study first used the MR approach to explore the causal associations among GM, GM-derived metabolites, and GDM. Our findings may contribute to the prevention and treatment strategies for GDM by targeting GM and metabolites, and offer novel insights into the underlying mechanism of the disease.

Mendelian randomization analyses support causal relationship between gut microbiota and childhood obesity.

Background: Childhood obesity (CO) is an increasing public health issue. Mounting evidence has shown that gut microbiota (GM) is closely related to CO. However, the causal association needs to be treated with caution due to confounding factors and reverse causation. Methods: Data were obtained from the Microbiome Genome Consortium for GM as well as the Early Growth Genetics Consortium for childhood obesity and childhood body mass index (CBMI). Inverse variance weighted, maximum likelihood, weighted median, and MR.RAPS methods were applied to examine the causal association. Then replication dataset was used to validate the results and reverse Mendelian randomization analysis was performed to confirm the causal direction. Additionally, sensitivity analyses including Cochran's Q statistics, MR-Egger intercept, MR-PRESSO global test, and the leave-one-out analysis were conducted to detect the potential heterogeneity and horizontal pleiotropy. Results: Our study found suggestive causal relationships between eight bacterial genera and the risk of childhood obesity (five for CO and four for CBMI). After validating the results in the replication dataset, we finally identified three childhood obesity-related GM including the genera Akkermansia, Intestinibacter, and Butyricimonas. Amongst these, the genus Akkermansia was both negatively associated with the risk of CO (OR = 0.574; 95% CI: 0.417, 0.789) and CBMI (ß = -0.172; 95% CI: -0.306, -0.039). Conclusions: In this study, we employed the MR approach to investigate the causal relationship between GM and CO, and discovered that the genus Akkermansia has a protective effect on both childhood obesity and BMI. Our findings may provide a potential strategy for preventing and intervening in CO, while also offering novel insights into the pathogenesis of CO from the perspective of GM.

Integrated machine learning and bioinformatic analyses used to construct a copper-induced cell death-related classifier for prognosis and immunotherapeutic response of hepatocellular carcinoma patients.

Background: Copper as phytonutrient has powerful activity against health diseases. A newly discovered mechanism of cell death that affects energy metabolism by copper ("cuproptosis") can induce multiple cuproptosis-related genes. Hepatocellular carcinoma (HCC) is a poorly prognosed widespread cancer having danger of advanced metastasis. Therefore, earlier diagnosis followed by the specific targeted therapy are required for improved prognosis. The work herein constructed scoring system built on ten cuproptosis-related genes (CRGs) to predict progression of tumor and metastasis more accurately and test patient reaction toward immunotherapy. Methods: A comprehensive assessment of cuproptosis patterns in HCC samples from two databases and a real-world cohort was performed on ten CRGs, that were linked to immune cell infiltration signatures of TME (tumor microenvironment). Risk signatures were created for quantifying effect of cuproptosis on HCC, and the effects of related genes on cellular function of HCC were investigated, in addition to the effects of immunotherapy and targeted therapy drugs. Results: Two distinct cuproptosis-associated mutational patterns were identified, with distinct immune cell infiltration characteristics and survival likelihood. Studies have shown that assessment of cuproptosis-induced tumor mutational patterns can help predict tumor stage, phenotype, stromal activity, genetic diversity, and patient prognosis. High risk scores are characterized by lower survival and worse treatment with anti-PD-L1/CTAL4 immunotherapy and first-line targeted drugs. Cytological functional assays show that CDKN2A and GLS promote proliferation, migration and inhibit copper-dependent death of HCC cells. Conclusion: HCC patients with high-risk scores exhibit significant treatment disadvantage and survival rates. Cuproptosis plays a non-negligible role in the development of HCC. Quantifying cuproptosis-related designs of tumors will aid in phenotypic categorization, leading to efficient personalized and targeted therapeutics and precise prediction of prognosis and metastasis.

Bioinformatic analyzes and validation of cystathionine gamma-lyase as a prognostic biomarker and related to immune infiltrates in hepatocellular carcinoma.

Background: The role of cystathionine γ-lyase (CTH) in the prognosis and immune invasion of hepatocellular carcinoma (HCC) remains poorly understood. Methods: In this study, the clinical data of patients with HCC were analyzed, and the expression level of CTH was compared between HCC and normal tissues using the R package and various databases. Results: We found that CTH expression was significantly decreased in HCC compared with normal tissues, and its expression was associated with various clinicopathological factors, including tumor stage, gender, tumor status, residual tumor, histologic stage, race, alpha-fetoprotein (AFP), albumin, drinking, and smoking. Our results suggest that CTH might be a protective factor for the survival of patients with HCC. Further functional analysis revealed that high CTH expression was enriched in the Reactome signaling by interleukins and the Reactome neutrophil degranulation. Moreover, CTH expression was closely correlated with a variety of immune cells, including a negative correlation with the CD56 (bright) NK cells and follicular helper T cell (TFH), while a positive correlation with Th17 cells and central memory T cell (Tcm). High expression of CTH in immune cells predicted a better prognosis of HCC. Our findings further indicated Pyridoxal phosphate, l-cysteine, Carboxymethylthio-3-(3-chlorophenyl)-1,2,4-oxadiazol, 2-[(3-Hydroxy-2-Methyl-5-Phosphonooxymethyl-Pyridin-4-Ylmethyl)-Imino]-5-phosphono-pent-3-enoic acid and L-2-amino-3-butynoic acid as potential target candidate medications for HCC treatment based on CTH. Conclusion: Our study suggests that CTH can serve as a biomarker to predict the prognosis and immune infiltration of HCC.

Identifying modifiable factors and their joint effect on dementia risk in the UK Biobank.

Previous hypothesis-driven research has identified many risk factors linked to dementia. However, the multiplicity and co-occurrence of risk factors have been underestimated. Here we analysed data of 344,324 participants from the UK Biobank with 15 yr of follow-up data for 210 modifiable risk factors. We first conducted an exposure-wide association study and then combined factors associated with dementia to generate composite scores for different domains. We then evaluated their joint associations with dementia in a multivariate Cox model. We estimated the potential impact of eliminating the unfavourable profiles of risk domains on dementia using population attributable fraction. The associations varied by domain, with lifestyle (16.6%), medical history (14.0%) and socioeconomic status (13.5%) contributing to the majority of dementia cases. Overall, we estimated that up to 47.0%-72.6% of dementia cases could be prevented.