C3orf70 Is Involved in Neural and Neurobehavioral Development

Nasal epithelial gene expression and total IgE in children and adolescents with asthma

BACKGROUND

Little is known about nasal epithelial gene expression and total IgE in youth.

OBJECTIVE

We aimed to identify genes whose nasal epithelial expression differs by total IgE in youth, and group them into modules that could be mapped to airway epithelial cell types.

METHODS

We conducted a transcriptome-wide association study of total IgE in 469 Puerto Ricans aged 9 to 20 years who participated in the Epigenetic Variation and Childhood Asthma in Puerto Ricans study, separately in all subjects and in those with asthma. We then attempted to replicate top findings for each analysis using data from 3 cohorts. Genes with a Benjamini-Hochberg-adjusted P value of less than .05 in the Epigenetic Variation and Childhood Asthma in Puerto Ricans study and a P value of less than .05 in the same direction of association in 1 or more replication cohort were considered differentially expressed genes (DEGs). DEGs for total IgE in subjects with asthma were further dissected into gene modules using coexpression analysis, and such modules were mapped to specific cell types in airway epithelia using public single-cell RNA-sequencing data.

RESULTS

A higher number of DEGs for total IgE were identified in subjects with asthma (n = 1179 DEGs) than in all subjects (n = 631 DEGs). In subjects with asthma, DEGs were mapped to 11 gene modules. The top module for positive correlation with total IgE was mapped to myoepithelial and mucus secretory cells in lower airway epithelia and was regulated by IL-4, IL5, IL-13, and IL-33. Within this module, hub genes included CDH26, FETUB, NTRK2, CCBL1, CST1, and CST2. Furthermore, an enrichment analysis showed overrepresentation of genes in signaling pathways for synaptogenesis, IL-13, and ferroptosis, supporting interactions between interleukin- and acetylcholine-induced responses.

CONCLUSIONS

Our findings for nasal epithelial gene expression support neuroimmune coregulation of total IgE in youth with asthma.

Uncharacterized Proteins CxORFx: Subinteractome Analysis and Prognostic Significance in Cancers

Functions of about 10% of all the proteins and their associations with diseases are poorly annotated or not annotated at all. Among these proteins, there is a group of uncharacterized chromosome-specific open-reading frame genes (CxORFx) from the 'Tdark' category. The aim of the work was to reveal associations of CxORFx gene expression and ORF proteins' subinteractomes with cancer-driven cellular processes and molecular pathways. We performed systems biology and bioinformatic analysis of 219 differentially expressed CxORFx genes in cancers, an estimation of prognostic significance of novel transcriptomic signatures and analysis of subinteractome composition using several web servers (GEPIA2, KMplotter, ROC-plotter, TIMER, cBioPortal, DepMap, EnrichR, PepPSy, cProSite, WebGestalt, CancerGeneNet, PathwAX II and FunCoup). The subinteractome of each ORF protein was revealed using ten different data sources on physical protein-protein interactions (PPIs) to obtain representative datasets for the exploration of possible cellular functions of ORF proteins through a spectrum of neighboring annotated protein partners. A total of 42 out of 219 presumably cancer-associated ORF proteins and 30 cancer-dependent binary PPIs were found. Additionally, a bibliometric analysis of 204 publications allowed us to retrieve biomedical terms related to ORF genes. In spite of recent progress in functional studies of ORF genes, the current investigations aim at finding out the prognostic value of CxORFx expression patterns in cancers. The results obtained expand the understanding of the possible functions of the poorly annotated CxORFx in the cancer context.

An Alzheimer’s Disease Patient-Derived Olfactory Stem Cell Model Identifies Gene Expression Changes Associated with Cognition

An early symptom of Alzheimer’s disease (AD) is an impaired sense of smell, for which the molecular basis remains elusive. Here, we generated human olfactory neurosphere-derived (ONS) cells from people with AD and mild cognitive impairment (MCI), and performed global RNA sequencing to determine gene expression changes. ONS cells expressed markers of neuroglial differentiation, providing a unique cellular model to explore changes of early AD-associated pathways. Our transcriptomics data from ONS cells revealed differentially expressed genes (DEGs) associated with cognitive processes in AD cells compared to MCI, or matched healthy controls (HC). A-Kinase Anchoring Protein 6 (AKAP6) was the most significantly altered gene in AD compared to both MCI and HC, and has been linked to cognitive function. The greatest change in gene expression of all DEGs occurred between AD and MCI. Gene pathway analysis revealed defects in multiple cellular processes with aging, intellectual deficiency and alternative splicing being the most significantly dysregulated in AD ONS cells. Our results demonstrate that ONS cells can provide a cellular model for AD that recapitulates disease-associated differences. We have revealed potential novel genes, including AKAP6 that may have a role in AD, particularly MCI to AD transition, and should be further examined.

Maternal Dietary Glycemic Index and Glycemic Load in Pregnancy and Offspring Cord Blood DNA Methylation

OBJECTIVE

Suboptimal nutrition in pregnancy is associated with worse offspring cardiometabolic health. DNA methylation may be an underlying mechanism. We meta-analyzed epigenome-wide association studies (EWAS) of maternal dietary glycemic index and load with cord blood DNA methylation.

RESEARCH DESIGN AND METHODS

We calculated maternal glycemic index and load from food frequency questionnaires and ran EWAS on cord blood DNA methylation in 2,003 mother-offspring pairs from three cohorts. Analyses were additionally stratified by maternal BMI categories. We looked-up the findings in EWAS of maternal glycemic traits and BMI as well as in EWAS of birth weight and child BMI. We examined associations with gene expression in child blood in the online Human Early Life Exposome eQTM catalog and in 223 adipose tissue samples.

RESULTS

Maternal glycemic index and load were associated with cord blood DNA methylation at 41 cytosine-phosphate-guanine sites (CpGs, P < 1.17 × 10-7), mostly in mothers with overweight/obesity. We did not observe overlap with CpGs associated with maternal glycemic traits, BMI, or child birth weight or BMI. Only DNA methylation at cg24458009 and cg23347399 was associated with expression of PCED1B and PCDHG, respectively, in child blood, and DNA methylation at cg27193519 was associated with expression of TFAP4, ZNF500, PPL, and ANKS3 in child subcutaneous adipose tissue.

CONCLUSIONS

We observed multiple associations of maternal glycemic index and load during pregnancy with cord blood DNA methylation, mostly in mothers with overweight/obesity; some of these CpGs were associated with gene expression. Additional studies are required to further explore functionality, uncover causality, and study pathways to offspring health.

Zebrafish Is a Powerful Tool for Precision Medicine Approaches to Neurological Disorders

Personalized medicine is currently one of the most promising tools which give hope to patients with no suitable or no available treatment. Patient-specific approaches are particularly needed for common diseases with a broad phenotypic spectrum as well as for rare and yet-undiagnosed disorders. In both cases, there is a need to understand the underlying mechanisms and how to counteract them. Even though, during recent years, we have been observing the blossom of novel therapeutic techniques, there is still a gap to fill between bench and bedside in a patient-specific fashion. In particular, the complexity of genotype-to-phenotype correlations in the context of neurological disorders has dampened the development of successful disease-modifying therapeutics. Animal modeling of human diseases is instrumental in the development of therapies. Currently, zebrafish has emerged as a powerful and convenient model organism for modeling and investigating various neurological disorders. This model has been broadly described as a valuable tool for understanding developmental processes and disease mechanisms, behavioral studies, toxicity, and drug screening. The translatability of findings obtained from zebrafish studies and the broad prospect of human disease modeling paves the way for developing tailored therapeutic strategies. In this review, we will discuss the predictive power of zebrafish in the discovery of novel, precise therapeutic approaches in neurosciences. We will shed light on the advantages and abilities of this in vivo model to develop tailored medicinal strategies. We will also investigate the newest accomplishments and current challenges in the field and future perspectives.

An Epithelial-Mesenchymal Transition (EMT) Preoperative Nomogram for Prediction of Lymph Node Metastasis in Bladder Cancer (BLCA)

Lymph node (LN) metastasis is a lethal independent risk factor for patients with bladder cancer (BLCA). Accurate evaluation of LN metastasis is of vital importance for disease staging, treatment selection, and prognosis prediction. Several histopathologic parameters are available to predict LN metastasis postoperatively. To date, medical imaging techniques have made a great contribution to preoperatively diagnosis of LN metastasis, but it also exhibits substantial false positives. Therefore, a reliable and robust method to preoperatively predict LN metastasis is urgently needed. Here, we selected 19 candidate genes related to epithelial-mesenchymal transition (EMT) across the LN metastasis samples, which was previously reported to be responsible for the subtype transition and correlation with malignancy and prognosis of BLCA, to establish an EMT-LN signature through LASSO logistic regression analysis. The EMT-LN signature could significantly predict LN metastasis with high accuracy in the TCGA-BLCA cohort, as well as several independent cohorts. As integrating with C3orf70 mutation, we developed an individualized prediction nomogram based on the EMT-LN signature. The nomogram exhibited good discrimination on LN metastasis status, with AUC of 71.7% and 75.9% in training and testing datasets of the TCGA-BLCA cohort. Moreover, the EMT-LN nomogram displayed good calibration with p > 0.05 in the Hosmer-Lemeshow goodness of fit test. Decision curve analysis (DCA) revealed that the EMT-LN nomogram was of high potential for clinical utility. In summary, we established an EMT-LN nomogram integrating an EMT-LN signature and C3orf70 mutation status, which acted as an easy-to-use tool to facilitate preoperative prediction of LN metastasis in BLCA individuals.

CRISPR Meets Zebrafish: Accelerating the Discovery of New Therapeutic Targets

Bringing a new drug to the market costs an average of US$2.6 billion and takes more than 10 years from discovery to regulatory approval. Despite the need to reduce cost and time to increase productivity, pharma companies tend to crowd their efforts in the same indications and drug targets. This results in the commercialization of drugs that share the same mechanism of action (MoA) and, in many cases, equivalent efficacies among them-an outcome that helps neither patients nor the balance sheet of the companies trying to bring therapeutics to the same patient population. Indeed, the discovery of new therapeutic targets, based on a deeper understanding of the disease biology, would likely provide more innovative MoAs and potentially greater drug efficacies. It would also bring better chances for identifying appropriate treatments according to the patient's genetic stratification. Nowadays, we count with an enormous amount of unprocessed information on potential disease targets that could be extracted from omics data obtained from patient samples. In addition, hundreds of pharmacological and genetic screenings have been performed to identify innovative drug targets. Traditionally, rodents have been the animal models of choice to perform functional genomic studies. The high experimental cost, combined with the low throughput provided by those models, however, is a bottleneck for discovering and validating novel genetic disease associations. To overcome these limitations, we propose that zebrafish, in conjunction with the use of CRISPR/Cas9 genome-editing tools, could streamline functional genomic processes to bring biologically relevant knowledge on innovative disease targets in a shorter time frame.