Potential Risk Genes Research Articles

M6A-mRNA Reader YTHDF2 Identified as a Potential Risk Gene in Autism With Disproportionate Megalencephaly.

Among autistic individuals, a subphenotype of disproportionate megalencephaly (ASD-DM) seen at three years of age is associated with co-occurring intellectual disability and poorer prognoses later in life. However, many of the genes contributing to ASD-DM have yet to be delineated. In this study, we identified additional ASD-DM candidate genes with the aim to better define the genetic etiology of this subphenotype of autism. We expanded the previously studied sample size of ASD-DM individuals ten fold by including probands from the Autism Phenome Project and Simons Simplex Collection, totaling 766 autistic individuals meeting the criteria for megalencephaly or macrocephaly and revealing 154 candidate ASD-DM genes harboring de novo protein-impacting variants. Our findings include 14 high confidence autism genes and seven genes previously associated with DM. Five impacted genes have previously been associated with both autism and DM, including CHD8 and PTEN. By performing functional network analysis, we expanded to additional candidate genes, including one previously implicated in ASD-DM (PIK3CA) as well as 184 additional genes connected withASD or DM alone. Using zebrafish, we modeled a de novo tandem duplication impacting YTHDF2, encoding an N6-methyladenosine (m6A)-mRNA reader, in an ASD-DM proband. Testing zebrafish CRISPR knockdown led to reduced head/brain size, while overexpressing YTHDF2 resulted in increased head/brain size matching that of the proband. Single-cell transcriptomes of YTHDF2 gain-of-function larvae point to reduced expression of Fragile-X-syndrome-associated FMRP-target genes globally and in the developing brain, providing insight into the mechanism underlying autistic phenotypes. We additionally discovered a variant impacting a different gene encoding an m6A reader, YTHDC1, in our ASD-DM cohort. Though we highlight only two cases to date, our study provides support for the m6A-RNA modification pathway as potentially contributing to this severe form of autism.

P1296 Exploring the role of BOC mutations in Crohn’s disease using whole exome sequencing and molecular dynamics simulation

Abstract Background Crohn’s disease (CD) is a chronic inflammatory bowel disease, whose pathogenesis involves genetic component. In this study, BOC was identified as a potential risk gene for CD, whose gene product is a member of the cell adhesion molecule family. It is suggested that BOC binds to the N-terminus of Dhh protein (DhhN) through its Fn2-Fn3 domain, facilitating hh protein signal transduction. This signal has been shown to maintain endothelial cell barrier integrity, which is critical in the development of CD. Hence, we hypothesize that mutations in the BOC protein could alter its structure, impairing its ability to bind or release hh proteins, leading to abnormal hh signal transduction and affecting endothelial cell barrier function. Therefore, we employed molecular dynamics simulation to investigate the characteristics and affinity changes of the domain, and the domain with DhhN complex, both before and after mutation. Methods The target risk gene BOC was identified, and employed molecular dynamics simulation to investigate the characteristics and affinity changes of the BOC Fn2-Fn3 domain, and the domain with DhhN complex, both before and after mutation. Results 1. From the list of gene mutations, 121 candidate risk genes were identified. 2. The target risk gene BOC was identified, which is highly expressed on the colorectal endothelial cell membrane surface, and its expression shows a difference between CD patients and normal colorectal tissues. 3. The Arg697 mutation leads to decreased flexibility and increased stability of the BOC Fn2-Fn3 domain. 4. The Arg697 mutation increases the affinity of the domain with the DhhN complex, adding to the number of key amino acids and hydrogen bonds maintaining the complex’s affinity. Conclusion 1. Whole exome sequencing analysis revealed specific BOC gene mutations in CD patients, with differential expression between patients and healthy individuals suggesting an important role for BOC in CD. 2. Molecular dynamics simulations revealed that the Arg697 mutation increases the stability of BOC, and also showed increased stability and affinity of its binding with DhhN, which might prevent BOC from properly releasing hh proteins after binding, leading to abnormal hh signal transduction and thus impairing endothelial cell barrier function, which may promote the development and progression of CD. 3. The increased affinity of the complex following the Arg697 mutation is due to an increase in the number of key amino acid residues at the binding interface, resulting in more hydrogen bonds. Modifying these key amino acids to alter the affinity of the complex could normalize hh signal transduction, thereby restoring endothelial cell barrier function.

A network-based systems genetics framework identifies pathobiology and drug repurposing in Parkinson’s disease

Parkinson’s disease (PD) is the second most prevalent neurodegenerative disorder. However, current treatments only manage symptoms and lack the ability to slow or prevent disease progression. We utilized a systems genetics approach to identify potential risk genes and repurposable drugs for PD. First, we leveraged non-coding genome-wide association studies (GWAS) loci effects on five types of brain-specific quantitative trait loci (xQTLs, including expression, protein, splicing, methylation and histone acetylation) under the protein–protein interactome (PPI) network. We then prioritized 175 PD likely risk genes (pdRGs), such as SNCA, CTSB, LRRK2, DGKQ, and CD44, which are enriched in druggable targets and differentially expressed genes across multiple human brain-specific cell types. Integrating network proximity-based drug repurposing and patient electronic health record (EHR) data observations, we identified Simvastatin as being significantly associated with reduced incidence of PD (hazard ratio (HR) = 0.91 for fall outcome, 95% confidence interval (CI): 0.87–0.94; HR = 0.88 for dementia outcome, 95% CI: 0.86–0.89) after adjusting for 267 covariates. In summary, our network-based systems genetics framework identifies potential risk genes and repurposable drugs for PD and other neurodegenerative diseases if broadly applied.

Germline predisposition in multiple myeloma.

We present a study of rare germline predisposition variants in 954 unrelated individuals with multiple myeloma (MM) and 82 MM families. Using a candidate gene approach, we identified such variants across all age groups in 9.1% of sporadic and 18% of familial cases. Implicated genes included genes suggested in other MM risk studies as potential risk genes (DIS3, EP300, KDM1A, and USP45); genes involved in predisposition to other cancers (ATM, BRCA1/2, CHEK2, PMS2, POT1, PRF1, and TP53); and BRIP1, EP300, and FANCM in individuals of African ancestry. Variants were characterized using loss of heterozygosity (LOH), biallelic events, and gene expression analyses, revealing 31 variants in 3.25% of sporadic cases for which pathogenicity was supported by multiple lines of evidence. Our results suggest that the disruption of DNA damage repair pathways may play a role in MM susceptibility. These results will inform improved surveillance in high-risk groups and potential therapeutic strategies.

Ganoderma lucidum (Curtis) P. Karst. Immunomodulatory Protein Has the Potential to Improve the Prognosis of Breast Cancer Through the Regulation of Key Prognosis-Related Genes.

Background/Objectives: Breast cancer in women is the most commonly diagnosed and most malignant tumor. Although luminal A breast cancer (LumA) has a relatively better prognosis, it still has a persistent pattern of recurrence. Ganoderma lucidum (Curtis) P. Karst. is a kind of traditional Chinese medicine and has antitumor effects. In this study, we aimed to identify the genes relevant to prognosis, find novel targets, and investigate the function of the bioactive protein from G. lucidum, called FIP-glu, in improving prognosis. Methods: Gene expression data and clinical information of LumA breast cancer patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Using bioinformatics methods, a predictive risk model was constructed to predict the prognosis for each patient. The cell counting kit-8 (CCK8) and clone formation assays were used to validate gene function. The ability of FIP-glu to regulate RNA levels of risk genes was validated. Results: Six risk genes (slit-roundabout GTPase-activating protein 2 (SRGAP2), solute carrier family 35 member 2 (SLC35A2), sequence similarity 114 member A1 (FAM114A1), tumor protein P53-inducible protein 11 (TP53I11), transmembrane protein 63C (TMEM63C), and polymeric immunoglobulin receptor (PIGR)) were identified, and a prognostic model was constructed. The prognosis was worse in the high-risk group and better in the low-risk group. The receiver operating characteristic (ROC) curve confirmed the model's accuracy. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that the differentially expressed genes (DEGs) between the high- and low-risk groups were significantly enriched in the immune responses. TMEM63C could promote tumor viability, growth, and proliferation in vitro. FIP-glu significantly regulated these risk genes, and attenuated the promoting effect of TMEM63C in breast cancer cells. Conclusions: SRGAP2, SLC35A2, FAM114A1, TP53I11, TMEM63C, and PIGR were identified as the potential risk genes for predicting the prognosis of patients. TMEM63C could be a potential novel therapeutic target. Moreover, FIP-glu was a promising drug for improving the prognosis of LumA breast cancer.

Genetic Architecture of Postpartum Psychosis: From Common to Rare Genetic Variation.

Postpartum psychosis is a severe psychiatric condition marked by the abrupt onset of psychosis, mania, or psychotic depression following childbirth. Despite evidence for a strong genetic basis, the roles of common and rare genetic variation remain poorly understood. Leveraging data from Swedish national registers and genomic data from the All of Us Research Program, we estimated family-based heritability at 55% and WGS-based heritability at 37%, with an overrepresentation on the X chromosome. Rare coding variant analysis identified DNMT1 and HMGCR as potential risk genes (q < 0.1). Analysis of 240,009 samples from All of Us demonstrated significant associations between these genes and multiple psychiatric disorders, supporting their biological relevance. Additionally, 17% of bipolar disorder, 21% of schizophrenia, and 16-25% of multiple autoimmune disorder risk genes overlapped with postpartum psychosis. These findings reveal unique genetic contributions and shared pathways, providing a foundation for understanding pathophysiology and advancing therapeutic strategies.

SLC2A3 promotes head and neck squamous cancer developing through negatively regulating CD8+ T cell in tumor microenvironment

Recent studies have identified SLC2A3 as being abnormally upregulated in multiple tumor types, correlating with poor survival and disrupted microenvironments. However, its prognostic significance in head and neck squamous cell carcinoma (HNSC) remains underexplored. In this study, SLC2A3 was screened as a potential risk gene influencing both immune and tumor components within the tumor microenvironment (TME) of 504 HNSC patients from the TCGA database. Immune infiltration analyses and clinical significance on SLC2A3 were conducted using ESTIMATE, CIBERSORT, ssGSEA, TIMER and clinical prognosis parameters. Additionally, the single-cell dataset is used to analyze the expression of SLC2A3 in various subpopulations. The magnetic activated cell sorting (MACS) is used to isolate CD8+ T cells from PBMCs or tumor tissues. Flow cytometry is used to identify purified and activated CD8+ T cells. GSEA and WB were used to investigate the molecular mechanism of SLC2A3 in CD8+ T cells. The co-culture system of CD8+ T cells and TU686 was used to investigate the effects of SLC2A3 on immune cells and tumor development. In this study, SLC2A3 was identified as a potential risk gene affecting both immune cells and tumor components within the TME of 504 HNSC patients derived from the TCGA database. We conducted immune infiltration analyses and assessed the clinical significance of SLC2A3 using various bioinformatics tools, including ESTIMATE, CIBERSORT, ssGSEA, and TIMER, along with clinical prognosis parameters. The single-cell RNA sequencing dataset was utilized to examine SLC2A3 expression across different cellular subpopulations. Magnetic activated cell sorting (MACS) was employed to isolate CD8+ T cells from peripheral blood mononuclear cells (PBMCs) or tumor tissues. Flow cytometry was implemented to confirm the purity and activation state of the isolated CD8+ T cells. GSEA and Western blot were applied to explore the molecular mechanisms underlying SLC2A3’s role in CD8+ T cells. Lastly, a co-culture system involving CD8+ T cells and TU686 tumor cells was established to study the impact of SLC2A3 on immune cell function and tumor progression. SLC2A3 emerges as an actively variable gene within the immune and stromal components of the TME, linked to aggravated immune infiltration and poor clinical outcomes. The upregulated expression of SLC2A3 is predominantly enriched in immune-related biological processes and linked to the suppression of CD8+ T cells, which are crucial for the survival of HNSC patients. Furthermore, SLC2A3 exhibits specific overexpression in CD8+ T cells and may potentially trigger ferroptosis. Knockdown of SLC2A3 led to a significant increase in the proliferation of CD8+ T cells compared to those without knockdown. In co-culture systems, CD8+ T cells with SLC2A3 knockdown demonstrated an enhanced ability to eliminate tumor cells compared to those without the knockdown. SLC2A3 is associated with changes in the TME and prognostic indicators. Moreover, high SLC2A3 expression in CD8+ T cells may drive cell death through ferroptosis, fostering tumor progression.

Identification of Risk Genes for Attention-Deficit/Hyperactivity Disorder During Early Human Brain Development

ObjectiveAttention-Deficit/Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder with high heritability. Demontis et al. (2023) identified 27 genome-wide significant loci for ADHD through genome-wide association studies (GWASs), but the identification of risk genes that confer susceptibility to ADHD has remained largely unexplored. MethodAs ADHD is a neurodevelopmental disorder, we integrated human brain prenatal gene and transcript expression weight data (n=120) and ADHD GWAS summary statistics (n=225,534; 38,691 cases and 186,843 controls) to perform a transcriptome-wide association study (TWAS) by FUSION (an analytic suite). ResultsOur analysis identified 10 genes, including LSM6, HYAL3, METTL15, RPS26, LRRC37A15P, RP11-142I20.1, ABCB9, AP006621.5, AC000068.5, and PDXDC1, that are significantly associated with ADHD, along with 8 transcripts of 7 genes. We also conducted TWAS analysis using CommonMind Consortium (CMC) adult brain gene and splicing expression weights (n=452), which highlighted several risk genes that showed associations with ADHD in both prenatal and postnatal stages, such as LSM6 and HYAL3. ConclusionOverall, our TWAS of ADHD, by integrating human prenatal brain transcriptome and ADHD GWAS results, uncovered the cis-effects of gene/transcript regulation that are predicted to be associated with ADHD. By combining colocalization and FOCUS fine-mapping analysis, we further unraveled potential causal candidate risk genes. The risk genes/transcripts we identified in this study can serve as a valuable resource for further investigation of the disease mechanisms underlying ADHD.

Identification of Potential Drug Targets for Sleep Apnea Through Mendelian Randomization

Background: Sleep apnea is a significant health impediment, and it presently lacks efficacious therapeutic interventions. Thus, it is imperative to discover novel therapeutic targets that could guide clinical treatment strategies. Objective: This study aims to utilize an integrative analytic approach to unearth previously unappreciated protein-encoding genes implicated in sleep apnea susceptibility. Methods: Through the Multi-Marker Analysis of Genomic Annotation (MAGMA), we aligned Single-Nucleotide Polymorphism (SNP) summary statistics from Genome-Wide Association Studies (GWAS) of gene bodies to discern potential risk genes. Following the MAGMA results, we conducted a round of Transcriptome-Wide Association Studies (TWAS) and Proteome-Wide Association Studies (PWAS) to expedite the conversion of genetic associations into probable protein targets. Mendelian Randomization (MR) and co-localization analysis were employed to ascertain the causal linkage between the candidate target genes and sleep apnea. Finally, a mediation analysis was undertaken to explore the possible intermediary role of 150 inflammatory metabolites and 1,124 proteins. Results: The MAGNA analysis revealed 2,819 genes in association with sleep apnea. TWAS and PWAS analyses indicated that cis-regulation of nine particular genes could play a role in sleep apnea onset via blood protein level alterations. MR and co-localization analyses also suggested a causal relationship with sleep apnea for three genes (ACADVL, CCDC134, UPP1). Consistent associations were found between genetically predicted biomarkers and Albumin, HCC-1, N-acetyl carnosine, and RELT, pointing towards their potential mediating roles in sleep apnea's etiological pathway. result: The MAGNA analysis revealed 2,819 genes in association with sleep apnea. TWAS and PWAS analyses indicated that cis-regulation of nine particular genes could play a role in sleep apnea onset via blood protein level alterations. MR and co-localization analyses also suggested a causal relationship with sleep apnea for three genes (ACADVL, CCDC134, UPP1). Consistent associations were found between genetically predicted biomarkers and Albumin, HCC-1, N-acetylcarnosine, and RELT, pointing towards their potential mediating roles in sleep apnea&amp;#039;s etiological pathway. Conclusion: Our findings indicate that ACADVL, CCDC134, and UPP1 genes are potentially significant targets for further functional investigation and therapeutic interventions for sleep apnea.

A network-based systems genetics framework identifies pathobiology and drug repurposing in Parkinson's disease.

Parkinson's disease (PD) is the second most prevalent neurodegenerative disorder. However, current treatments are directed at symptoms and lack ability to slow or prevent disease progression. Large-scale genome-wide association studies (GWAS) have identified numerous genomic loci associated with PD, which may guide the development of disease-modifying treatments. We presented a systems genetics approach to identify potential risk genes and repurposable drugs for PD. First, we leveraged non-coding GWAS loci effects on multiple human brain-specific quantitative trait loci (xQTLs) under the protein-protein interactome (PPI) network. We then prioritized a set of PD likely risk genes (pdRGs) by integrating five types of molecular xQTLs: expression (eQTLs), protein (pQTLs), splicing (sQTLs), methylation (meQTLs), and histone acetylation (haQTLs). We also integrated network proximity-based drug repurposing and patient electronic health record (EHR) data observations to propose potential drug candidates for PD treatments. We identified 175 pdRGs from QTL-regulated GWAS findings, such as SNCA, CTSB, LRRK2, DGKQ, CD38 and CD44. Multi-omics data validation revealed that the identified pdRGs are likely to be druggable targets, differentially expressed in multiple cell types and impact both the parkin ubiquitin-proteasome and alpha-synuclein (a-syn) pathways. Based on the network proximity-based drug repurposing followed by EHR data validation, we identified usage of simvastatin as being significantly associated with reduced incidence of PD (fall outcome: hazard ratio (HR) = 0.91, 95% confidence interval (CI): 0.87-0.94; for dementia outcome: HR = 0.88, 95% CI: 0.86-0.89), after adjusting for 267 covariates. Our network-based systems genetics framework identifies potential risk genes and repurposable drugs for PD and other neurodegenerative diseases if broadly applied.

RNF144A as a potential risk gene for endometrial carcinoma: Insights from Mendelian randomization, bulk RNA sequencing, single-cell RNA, and experimental analysis.

Endometrial carcinoma (EC) is a prevalent gynecological malignancy that poses a significant threat to women's health worldwide. However, its pathogenesis and underlying mechanisms remains unclear. In this study, expression quantitative trait loci data, Mendelian randomization analysis, and differential expression analysis were performed to identify potential targets. A prognostic risk signature was subsequently constructed for EC patients based on the expression of these genes. Four bioinformatics algorithms, including generalized linear model, extreme gradient boosting, support vector machine, and random forest, were used to identify hub genes in EC. The expression of ring finger protein 144A (RNF144A) was validated using quantitative real-time polymerase chain reaction. Cellular proliferation and migration ability were evaluated using CCK-8 and Transwell assays, respectively. The genes RNF144A, ketohexokinase, and Rab interacting lysosomal protein like 2 were identified as potential targets for EC. Their differential expression was observed in EC patients, and Mendelian randomization analysis revealed a negative correlation between these genes and the development of EC. Mechanistic analyses suggested a strong association between these genes and the tumor immune microenvironment. The constructed risk signature was significantly associated with the prognosis, age, cancer stage, and grade of EC patients. Furthermore, based on interacted model algorithms, RNF144A was identified as a hub gene in EC. It was found to be significantly downregulated in EC samples, and its expression was positively correlated with the stage and grade of EC patients. In vitro experiments showed that overexpression of RNF144A significantly promoted cell growth and migration in EC cells. In conclusion, this study provides insights into the molecular mechanisms underlying EC progression and identifies preliminary candidate biomarkers for the development of EC treatment strategies.

Integrative analysis of transcriptome-wide association study and mRNA expression profile identified risk genes for bipolar disorder

ObjectiveBipolar disorder (BD) is a debilitating neuropsychiatric disorder, which is associated with genetic variation through “vast but mixed” Genome-Wide Association Studies (GWAS). Transcriptome-Wide Association Study (TWAS) is more effective in explaining genetic factors that influence complex diseases and can help identifying risk genes more reliably. So, this study aims to identify potential BD risk genes in pedigrees with TWAS. MethodsWe conducted a TWAS analysis with expression quantitative trait loci (eQTL) analysis on extended BD pedigrees, and the BD genome-wide association study (GWAS) summary data acquired from the Psychiatric Genomics Consortium (PGC). Furthermore, the BD-associated genes identified by TWAS were validated by mRNA expression profiles from the Gene Expression Omnibus (GEO) Datasets (GSE23848 and GSE46416). Functional enrichment and annotation analysis were implemented by RStudio (version 4.2.0). ResultsTWAS identified 362 genes with P value < 0.05, and 18 genes remain significant after Bonferroni correction, such as SEMA3G (PTWAS=1.07 × 10-11), ALOX5AP (PTWAS=3.12 × 10-8), and PLEC (PTWAS=1.27 × 10-7). Further 6 overlapped genes were detected in integrative analysis, such as UQCRB (PTWAS=0.0020, PmRNA=0.0000), TMPRSS9 (PTWAS=0.0405, PmRNA=0.0032), and SNX10 (PTWAS=0.0104, PmRNA=0.0015). Using genes identified by TWAS, Gene Ontology (GO) enrichment analysis identified 40 significant GO terms, such as mitochondrial ATP synthesis coupled electron transport, mitochondrial respiratory, aerobic electron transport chain, oxidative phosphorylation, mitochondrial membrane proteins, and ubiquinone activity. The Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway enrichment analysis identified significant 15 pathways for BD, such as Oxidative phosphorylation, endocannabinoids signaling, neurodegeneration, and reactive oxide species. ConclusionsWe found a set of BD-associated genes and pathways, validating the important role of neurodevelopmental abnormalities, inflammatory responses, and mitochondrial dysfunction in the pathology of BD, offering novel information for comprehending the genetic basis of BD.

Whole-genome sequencing identifies novel genes for autism in Chinese trios.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with high genetic heritability but heterogeneity. Fully understanding its genetics requires whole-genome sequencing (WGS), but the ASD studies utilizing WGS data in Chinese population are limited. In this study, we present a WGS study for 334 individuals, including 112 ASD patients and their non-ASD parents. We identified 146 de novo variants in coding regions in 85 cases and 60 inherited variants in coding regions. By integrating these variants with an association model, we identified 33 potential risk genes (P<0.001) enriched in neuron and regulation related biological process. Besides the well-known ASD genes (SCN2A, NF1, SHANK3, CHD8 etc.), several high confidence genes were highlighted by a series of functional analyses, including CTNND1, DGKZ, LRP1, DDN, ZNF483, NR4A2, SMAD6, INTS1, and MRPL12, with more supported evidence from GO enrichment, expression and network analysis. We also integrated RNA-seq data to analyze the effect of the variants on the gene expression and found 12 genes in the individuals with the related variants had relatively biased expression. We further presented the clinical phenotypes of the proband carrying the risk genes in both our samples and Caucasian samples to show the effect of the risk genes on phenotype. Regarding variants in non-coding regions, a total of 74 de novo variants and 30 inherited variants were predicted as pathogenic with high confidence, which were mapped to specific genes or regulatory features. The number of de novo variants found in patient was significantly associated with the parents' ages at the birth of the child, and gender with trend. We also identified small de novo structural variants in ASD trios. The results in this study provided important evidence for understanding the genetic mechanism of ASD.

Prognostic Value of Fatty Acid Metabolism-related Genes in Patients with Bladder Cancer.

This study aimed to explore the expression profiles of fatty acid metabolism- related genes (FAMRGs) in patients with bladder cancer (BLCA). The corresponding clinicopathological features of BLCA patients and RNA sequencing data were downloaded from TCGA and GSE13507. Univariate Cox regression was used to determine the prognostic value of FRGS in BLCA patients. LASSO regression analysis was then performed to select potential risk genes and eliminate genes that might overfit the model. Based on the independent prognostication-related FRGs, the nomogram survival model was established using the root mean square value of the R packet to predict the 1-year, 3-year, and 5-year survival rates of BLCA patients. By determining the area under the curve (AUC) value, the time-dependent receiver operating characteristic curve (ROC) was used to evaluate the prognostic efficiency of our model. A total of 243 DEFRGs were identified. Twenty FRGs were found to be related to the prognosis of BLCA in the TCGA database. Survival curves showed that high-risk patients had significantly shorter OS than low-risk cases (p < 0.001). The AUC of risk was 0.784, which was superior to age, sex, and stage, suggesting that the risk score was more favorable in predicting OS than traditional pathologic prognostic factors. The AUC was 0.757 at 1 year, 0.732 at 3 years, and 0.733 at 5 year-OS. In this study, we demonstrated that a FAMRG prognosis biomarker is associated with the tumor immune microenvironment in patients with BLCA.

The paired immunoglobulin-like type 2 receptor alpha (PILRA) gene polymorphism rs1859788 reduces risk of Alzheimer's Disease in men homozygous for the ApoE ε4 allele.

The APOE gene has long been associated with Alzheimer Disease (AD) risk. Emerging research indicates that other genetic loci, including the paired immunoglobulin-like type 2 receptor alpha (PILRA) gene, may play a crucial role. In the current study we used UK Biobank data to assess the relationship between PILRA and AD. We examined the PILRA polymorphism rs1859788, a single nucleotide missense variant, G > A, minor allele frequency 0.3. Single nucleotide polymorphism (SNP) data for rs429358 and rs7412 determined APOE isoform. We used PheWeb to perform a phenome wide association study (phewas) of rs1859788 and identify other conditions that might be related to both AD and rs1859788. In male subjects homozygous for ApoE isoform ε4/ε4, of the men without AD, 9.7% had AA genotype; of the men with AD, 1.8% had AA genotype. This difference was significant (p = 0.006, two tail Fisher exact test). In female subjects homozygous for ApoE isoform ε4/ε4, of the women without AD, 10.4% had AA genotype; of the women with AD 7.9% had AA genotype. This difference was not significant (p = 0.481). In subjects not homozygous for ApoE isoform ε4/ε4, the effect of PILRA genotype was not significant. A phewas of rs1859788 found an association with megaloblastic anemia. We have confirmed the previously noted PILRA snp rs1859788 risk reduction of AD, as well as a PILRA link to the ApoE ε4 isoform that has been previously described. We are uncertain why the significant association is only with men who are homozygous for the ε4/ε4 isoform. A phewas indicated that PILRA SNP rs1859788 is associated with megaloblastic anemia, which may explain an observed association between AD and anemia. The identification of PILRA as a potential risk gene for Alzheimer's disease underscores the complexity of the genetic landscape contributing to AD. Alongside APOE, PILRA may play a significant role in modulating key pathological processes such as neuroinflammation and amyloid-beta accumulation.

Bioinformatics analysis of potential pathogenesis and risk genes of neuroinflammation-promoted brain injury in intracerebral hemorrhage

IntroductionSpontaneous (non-traumatic) intracerebral hemorrhage (ICH) is one of the major causes of global death. The purpose of our bioinformatics analysis was to detect viable pathophysiological targets and small-molecule drug candidates and to identify the precise secondary mechanisms of brain injury in ICH. Material and methodsThe GSE24265 dataset, consisting of data from four perihematomal brain tissues and seven contralateral brain tissues, was downloaded from the Gene Expression Omnibus (GEO) database and screened for differentially expressed genes (DEGs) in ICH. Online analysis tool GEO2R and Drug Susceptibility Assessment Module within the ACBI Bioinformation tool was used for data differential expression analysis. TargetScan, miRDB, and RNA22 were used to investigate the miRNAs regulating the DEGs. The functional annotation of DEGs was performed using Gene Ontology (GO) resources, and the cell signaling pathway analysis of DEGs was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG). DAVID is used to perform GO function enrichment analysis and KEGG pathway analysis of candidate target genes. Enrichment analysis was performed for delving the molecular mechanism of DEGs, and protein–protein interaction (PPI) networks and microRNA (miRNA)-messenger RNA (mRNA) networks were used to reveal the hub nodes and the related interaction relationships. Hub genes and miRNA-mRNA interaction of PPI network were identified by STRING version 12.0 online software and Cytoscape. Next, the DEGs were analyzed using the L1000CDS2 database to identify small-molecule compounds with potential therapeutic effects. ResultsA total of 325 upregulated genes and 103 downregulated genes associated with ICH were identified. The biological functions of DEGs associated with ICH are mainly involved in the inflammatory response, chemokine activity, and immune response. The KEGG analysis identified several pathways significantly associated with ICH, including but not limited to cytokine-cytokine receptor interaction and MAPK signaling pathway. A PPI network consisting of 188 nodes and 563 edges was constructed using STRING, and 27 hub genes were identified with Cytoscape software. The miRNA-mRNA network with high connectivity contained key 27 mRNAs (from C-C motif chemokine ligand 5 (CCL5), C-C motif chemokine ligand 8 (CCL8), …., to dishevelled-associated activator of morphogenesis 1 (DAAM1), and FRAT regulator of WNT signaling pathway 1 (FRAT1)) and 135 candidate miRNAs. These genes and miRNAs are closely related to secondary brain injury induced by ICH. In addition, a L1000CDS2 analysis of six small-molecule compounds revealed their therapeutic potential. ConclusionsOur study explores the pathogenesis of brain tissue injury promoted by neuroinflammation in ICH and extends the clinical utility of its key genes. At the same time, we constructed a miRNA-mRNA network which may play crucial roles in the pathogenesis of ICH. In addition, we obtained six small molecule compounds that will have anti-inflammatory effects on ICH, including Geldanamycin, Dasatinib, BMS-345541, Saracatinib, and Afatinib.

Whole-exome sequencing identifies high-confidence genes for tic disorders in a Chinese Han population

BackgroundTic disorder (TD) is a polygenic neurodevelopmental disorder with high susceptibility. However, identifying high-confidence risk genes has been challenging due to poor replication across multiple studies. MethodsWhole-exome sequencing was performed on 390 TD patients and 372 unaffected individuals in a Chinese Han population. Analysis of variance, burden analysis and in silico prediction were used to identify candidate genes for TD. To facilitate data analysis and to focus on high-confidence genes, we defined a panel of 160 genes as known causal or candidate TD genes from previous studies. Gene enrichment and protein–protein interaction analysis were utilized to detect potential novel TD risk genes. ResultsTotally, 14 variants across 12 known TD candidate genes were considered potential susceptibility variants. Ten variants across 10 known TD candidate genes were identified as potential disease-causing variants. Burden analysis identified variants of 28 known genes were significantly excess in TD patients. In addition, 354 previously unproven TD genes are over-represented in patients. Genes enriched in the PI3K-Akt signaling, sphingolipid metabolism and serotonergic synaptic pathways, as well as those interacting with FN1, were considered potential new candidate genes for TD. ConclusionsThis is the largest WES study focusing on TD patients in a Chinese Han population. Several variants recurring in our cohort were identified as high-confidence risk loci for TD. Moreover, we provided potential new risk genes that may be prioritized for further investigation.

Functional Genomics and Insights into the Pathogenesis and Treatment of Psoriasis.

Psoriasis is a lifelong, systemic, immune mediated inflammatory skin condition, affecting 1-3% of the world's population, with an impact on quality of life similar to diseases like cancer or diabetes. Genetics are the single largest risk factor in psoriasis, with Genome-Wide Association (GWAS) studies showing that many psoriasis risk genes lie along the IL-23/Th17 axis. Potential psoriasis risk genes determined through GWAS can be annotated and characterised using functional genomics, allowing the identification of novel drug targets and the repurposing of existing drugs. This review is focused on the IL-23/Th17 axis, providing an insight into key cell types, cytokines, and intracellular signaling pathways involved. This includes examination of currently available biological treatments, time to relapse post drug withdrawal, and rates of primary/secondary drug failure, showing the need for greater understanding of the underlying genetic mechanisms of psoriasis and how they can impact treatment. This could allow for patient stratification towards the treatment most likely to reduce the burden of disease for the longest period possible.

Multi-ancestry meta-analysis of tobacco use disorder identifies 461 potential risk genes and reveals associations with multiple health outcomes.

Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviours and although strides have been made using genome-wide association studies to identify risk variants, most variants identified have been for nicotine consumption, rather than TUD. Here we leveraged four US biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records) in 653,790 individuals (495,005 European, 114,420 African American and 44,365 Latin American) and data from UK Biobank (ncombined = 898,680). We identified 88 independent risk loci; integration with functional genomic tools uncovered 461 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviours in children and hundreds of medical outcomes, including HIV infection, heart disease and pain. This work furthers our biological understanding of TUD and establishes electronic health records as a source of phenotypic information for studying the genetics of TUD.

Sex differences orchestrated by androgens at single-cell resolution.

Sex differences in mammalian complex traits are prevalent and are intimately associated with androgens1-7. However, a molecular and cellular profile of sex differences and their modulation by androgens is still lacking. Here we constructed a high-dimensional single-cell transcriptomic atlas comprising over 2.3 million cells from 17 tissues in Mus musculus and explored the effects of sex and androgens on the molecular programs and cellular populations. In particular, we found that sex-biased immune gene expression and immune cell populations, such as group 2 innate lymphoid cells, were modulated by androgens. Integration with the UK Biobank dataset revealed potential cellular targets and risk gene enrichment in antigen presentation for sex-biased diseases. This study lays the groundwork for understanding the sex differences orchestrated by androgens and provides important evidence for targeting the androgen pathway as a broad therapeutic strategy for sex-biased diseases.