GeneAnalytics: An Integrative Gene Set Analysis Tool for Next Generation Sequencing, RNAseq and Microarray Data

Elucidating immune-related gene transcriptional programs via factorization of large-scale RNA-profiles

Recent developments in immunotherapy, including immune checkpoint blockade (ICB) and adoptive cell therapy (ACT), have encountered challenges such as immune-related adverse events and resistance, especially in solid tumors. To advance the field, a deeper understanding of the molecular mechanisms behind treatment responses and resistance is essential. However, the lack of functionally characterized immune-related gene sets has limited data-driven immunological research. To address this gap, we adopted non-negative matrix factorization on 83 human bulk RNA sequencing (RNA-seq) datasets and constructed 28 immune-specific gene sets. After rigorous immunologist-led manual annotations and orthogonal validations across immunological contexts and functional omics data, we demonstrated that these gene sets can be applied to refine pan-cancer immune subtypes, improve ICB response prediction and functionally annotate spatial transcriptomic data. These functional gene sets, informing diverse immune states, will advance our understanding of immunology and cancer research.

Elucidating immune-related gene transcriptional programs via factorization of large-scale RNA-profiles

Recent developments in immunotherapy, including immune checkpoint blockade (ICB) and adoptive cell therapy, have encountered challenges such as immune-related adverse events and resistance, especially in solid tumors. To advance the field, a deeper understanding of the molecular mechanisms behind treatment responses and resistance is essential. However, the lack of functionally characterized immune-related gene sets has limited data-driven immunological research. To address this gap, we adopted non-negative matrix factorization on 83 human bulk RNA-seq datasets and constructed 28 immune-specific gene sets. After rigorous immunologist-led manual annotations and orthogonal validations across immunological contexts and functional omics data, we demonstrated that these gene sets can be applied to refine pan-cancer immune subtypes, improve ICB response prediction and functionally annotate spatial transcriptomic data. These functional gene sets, informing diverse immune states, will advance our understanding of immunology and cancer research.

VarPPUD: Variant post prioritization developed for undiagnosed genetic disorders

Rare and ultra-rare genetic conditions are estimated to impact nearly 1 in 17 people worldwide, yet accurately pinpointing the diagnostic variants underlying each of these conditions remains a formidable challenge. Because comprehensive, in vivo functional assessment of all possible genetic variants is infeasible, clinicians instead consider in silico variant pathogenicity predictions to distinguish plausibly disease-causing from benign variants across the genome. However, in the most difficult undiagnosed cases, such as those accepted to the Undiagnosed Diseases Network (UDN), existing pathogenicity predictions cannot reliably discern true etiological variant(s) from other deleterious candidate variants that were prioritized through N-of-1 efforts. Pinpointing the disease-causing variant from a pool of plausible candidates remains a largely manual effort requiring extensive clinical workups, functional and experimental assays, and eventual identification of genotype- and phenotype-matched individuals. Here, we introduce VarPPUD, a tool trained on prioritized variants from UDN cases, that leverages gene-, amino acid-, and nucleotide-level features to discern pathogenic variants from other deleterious variants that are unlikely to be confirmed as disease relevant. VarPPUD achieves a cross-validated accuracy of 79.3% and precision of 77.5% on a held-out subset of uniquely challenging UDN cases, respectively representing an average 18.6% and 23.4% improvement over nine traditional pathogenicity prediction approaches on this task. We validate VarPPUD's ability to discriminate likely from unlikely pathogenic variants on synthetic, GAN-generated candidate variants as well. Finally, we show how VarPPUD can be probed to evaluate each input feature's importance and contribution toward prediction-an essential step toward understanding the distinct characteristics of newly-uncovered disease-causing variants.

Significance Statement

Patients with chronic, undiagnosed and underdiagnosed genetic conditions often endure expensive and excruciating years-long diagnostic odysseys without clear results. In many instances, clinical genome sequencing of patients and their family members fails to reveal known disease-causing variants, although compelling variants of uncertain significance are frequently encountered. Existing computational tools struggle to reliably differentiate truly disease-causing variants from other plausible candidate variants within these prioritized sets. Consequently, the confirmation of disease-causing variants often necessitates extensive experimental follow-up, including studies in model organisms and identification of other similarly presenting genotype-matched individuals, a process that can extend for several years. Here, we present VarPPUD, a tool trained specifically to distinguish likely from unlikely to be confirmed pathogenic variants that were prioritized across cases in the Undiagnosed Diseases Network. By evaluating the importance and impact of different input feature values on prediction, we gain deeper insights into the distinctive attributes of difficult-to-identify diagnostic variants. For patients who remain undiagnosed following comprehensive whole genome sequencing, our new method VarPPUD may reveal pathogenic variants amid a pool of candidate variants, thereby advancing diagnostic efforts where progress has otherwise stalled.

Loss of EIF4G2 mediates aggressiveness in distinct human endometrial cancer subpopulations with poor survival outcome in patients

The non-canonical translation initiation factor EIF4G2 plays essential roles in cellular stress responses via translation of selective mRNA cohorts. Currently there is limited and conflicting information regarding its involvement in cancer development and progression. Here we assessed its role in endometrial cancer (EC), in a cohort of 280 EC patients across different types, grades, and stages, and found that low EIF4G2 expression highly correlated with poor overall- and recurrence-free survival in Grade 2 EC patients, monitored over a period of up to 12 years. To establish a causative connection between low EIF4G2 expression and cancer progression, we stably knocked-down EIF4G2 in two human EC cell lines in parallel. EIF4G2 depletion resulted in increased resistance to conventional therapies and increased the prevalence of molecular markers for aggressive cell subsets, altering their transcriptional and proteomic landscapes. Prominent among the proteins with decreased abundance were Kinesin-1 motor proteins, KIF5B and KLC1, 2, 3. Multiplexed imaging of the EC patient tumor cohort showed a correlation between decreased expression of the kinesin proteins, and poor survival in patients with tumors of certain grades and stages. These findings reveal potential novel biomarkers for Grade 2 EC with ramifications for patient stratification and therapeutic interventions.

Pharmacogenomic synthetic lethal screens reveal hidden vulnerabilities and new therapeutic approaches for treatment of NF1-associated tumors

Neurofibromatosis Type 1 (NF1) is a common cancer predisposition syndrome, caused by heterozygous loss of function mutations in the tumor suppressor gene NF1. Individuals with NF1 develop benign tumors of the peripheral nervous system (neurofibromas), originating from the Schwann cell linage after somatic loss of the wild type NF1 allele, some of which progress further to malignant peripheral nerve sheath tumors (MPNST). There is only one FDA approved targeted therapy for symptomatic plexiform neurofibromas and none approved for MPNST. The genetic basis of NF1 syndrome makes associated tumors ideal for using synthetic drug sensitivity approaches to uncover therapeutic vulnerabilities. We developed a drug discovery pipeline to identify therapeutics for NF1-related tumors using isogeneic pairs of NF1-proficient and deficient immortalized human Schwann cells. We utilized these in a large-scale high throughput screen (HTS) for drugs that preferentially kill NF1-deficient cells, through which we identified 23 compounds capable of killing NF1-deficient Schwann cells with selectivity. Multiple hits from this screen clustered into classes defined by method of action. Four clinically interesting drugs from these classes were tested in vivo using both a genetically engineered mouse model of high-grade peripheral nerve sheath tumors and human MPNST xenografts. All drugs tested showed single agent efficacy in these models as well as significant synergy when used in combination with the MEK inhibitor selumetinib. This HTS platform yielded novel therapeutically relevant compounds for the treatment of NF1-associated tumors and can serve as a tool to rapidly evaluate new compounds and combinations in the future.

Asynchronous Pattern of MAPKs' Activity during Aging of Different Tissues and of Distinct Types of Skeletal Muscle

The MAPK p38α was proposed to be a prominent promoter of skeletal muscle aging. The skeletal muscle tissue is composed of various muscle types, and it is not known if p38α is associated with aging in all of them. It is also not known if p38α is associated with aging of other tissues. JNK and ERK were also proposed to be associated with aging of several tissues. Nevertheless, the pattern of p38α, JNK, and ERK activity during aging was not documented. Here, we documented the levels of phosphorylated/active p38α, Erk1/2, and JNKs in several organs as well as the soleus, tibialis anterior, quadriceps, gastrocnemius, and EDL muscles of 1-, 3-, 6-, 13-, 18-, and 24-month-old mice. We report that in most tissues and skeletal muscles, the MAPKs' activity does not change in the course of aging. In most tissues and muscles, p38α is in fact active at younger ages. The quadriceps and the lungs are exceptions, where p38α is significantly active only in mice 13 months old or older. Curiously, levels of active JNK and ERKs are also elevated in aged lungs and quadriceps. RNA-seq analysis of the quadriceps during aging revealed downregulation of proteins related to the extra-cellular matrix (ECM) and ERK signaling. A panel of mRNAs encoding cell cycle inhibitors and senescence-associated proteins, considered to be aging markers, was not found to be elevated. It seems that the pattern of MAPKs' activation in aging, as well as expression of known 'aging' components, are tissue- and muscle type-specific, supporting a notion that the process of aging is tissue- and even cell-specific.

Investigating the Potential Shared Molecular Mechanisms between COVID-19 and Alzheimer's Disease via Transcriptomic Analysis

SARS-CoV-2 caused the COVID-19 pandemic. COVID-19 may elevate the risk of cognitive impairment and even cause dementia in infected individuals; it may accelerate cognitive decline in elderly patients with dementia, possibly in Alzheimer's disease (AD) patients. However, the mechanisms underlying the interplay between AD and COVID-19 are still unclear. To investigate the underlying mechanisms and associations between AD progression and SARS-CoV-2 infection, we conducted a series of bioinformatics research into SARS-CoV-2-infected cells, COVID-19 patients, AD patients, and SARS-CoV-2-infected AD patients. We identified the common differentially expressed genes (DEGs) in COVID-19 patients, AD patients, and SARS-CoV-2-infected cells, and these DEGs are enriched in certain pathways, such as immune responses and cytokine storms. We constructed the gene interaction network with the signaling transduction module in the center and identified IRF7, STAT1, STAT2, and OAS1 as the hub genes. We also checked the correlations between several key transcription factors and the SARS-CoV-2 and COVID-19 pathway-related genes. We observed that ACE2 expression is positively correlated with IRF7 expression in AD and coronavirus infections, and interestingly, IRF7 is significantly upregulated in response to different RNA virus infections. Further snRNA-seq analysis indicates that NRGN neurons or endothelial cells may be responsible for the increase in ACE2 and IRF7 expression after SARS-CoV-2 infection. The positive correlation between ACE2 and IRF7 expressions is confirmed in the hippocampal formation (HF) of SARS-CoV-2-infected AD patients. Our findings could contribute to the investigation of the molecular mechanisms underlying the interplay between AD and COVID-19 and to the development of effective therapeutic strategies for AD patients with COVID-19.

Bi-allelic loss-of-function variants in WBP4, encoding a spliceosome protein, result in a variable neurodevelopmental syndrome

Over two dozen spliceosome proteins are involved in human diseases, also referred to as spliceosomopathies. WW domain-binding protein 4 (WBP4) is part of the early spliceosomal complex and has not been previously associated with human pathologies in the Online Mendelian Inheritance in Man (OMIM) database. Through GeneMatcher, we identified ten individuals from eight families with a severe neurodevelopmental syndrome featuring variable manifestations. Clinical manifestations included hypotonia, global developmental delay, severe intellectual disability, brain abnormalities, musculoskeletal, and gastrointestinal abnormalities. Genetic analysis revealed five different homozygous loss-of-function variants in WBP4. Immunoblotting on fibroblasts from two affected individuals with different genetic variants demonstrated a complete loss of protein, and RNA sequencing analysis uncovered shared abnormal splicing patterns, including in genes associated with abnormalities of the nervous system, potentially underlying the phenotypes of the probands. We conclude that bi-allelic variants in WBP4 cause a developmental disorder with variable presentations, adding to the growing list of human spliceosomopathies.

FAK family proteins regulate in vivo breast cancer metastasis via distinct mechanisms

Breast cancer is the most commonly diagnosed malignancy and the major leading cause of tumor-related deaths in women. It is estimated that the majority of breast tumor-related deaths are a consequence of metastasis, to which no cure exists at present. The FAK family proteins Proline-rich tyrosine kinase (PYK2) and focal adhesion kinase (FAK) are highly expressed in breast cancer, but the exact cellular and signaling mechanisms by which they regulate in vivo tumor cell invasiveness and consequent metastatic dissemination are mostly unknown. Using a PYK2 and FAK knockdown xenograft model we show here, for the first time, that ablation of either PYK2 or FAK decreases primary tumor size and significantly reduces Tumor MicroEnvironment of Metastasis (TMEM) doorway activation, leading to decreased intravasation and reduced spontaneous lung metastasis. Intravital imaging analysis further demonstrates that PYK2, but not FAK, regulates a motility phenotype switch between focal adhesion-mediated fast motility and invadopodia-dependent, ECM-degradation associated slow motility within the primary tumor. Furthermore, we validate our in vivo and intravital imaging results with integrated transcriptomic and proteomic data analysis from xenograft knockdown tumors and reveal new and distinct pathways by which these two homologous kinases regulate breast tumor cell invasiveness and consequent metastatic dissemination. Our findings identify PYK2 and FAK as novel mediators of mammary tumor progression and metastasis and as candidate therapeutic targets for breast cancer metastasis.

Exome sequencing to explore the possibility of predicting genetic susceptibility to the joint occurrence of polycystic ovary syndrome and Hashimoto's thyroiditis

A large body of evidence indicates that women with polycystic ovary syndrome (PCOS) have a higher risk of developing Hashimoto's thyroiditis (HT) than healthy individuals. Given the strong genetic impact on both diseases, common predisposing genetic factors are possibly involved but are not fully understood. Here, we performed whole-exome sequencing (WES) for 250 women with sporadic PCOS, HT, combined PCOS and HT (PCOS+HT), and healthy controls to explore the genetic background of the joint occurrence of PCOS and HT. Based on relevant comparative analyses, multivariate logistic regression prediction modeling, and the most informative feature selection using the Monte Carlo feature selection and interdependency discovery algorithm, 77 variants were selected for further validation by TaqMan genotyping in a group of 533 patients. In the allele frequency test, variants in RAB6A, GBP3, and FNDC7 genes were found to significantly (padjusted < 0.05) differentiated the PCOS+HT and PCOS groups, variant in HIF3A differentiated the PCOS+HT and HT groups, whereas variants in CDK20 and CCDC71 differentiated the PCOS+HT and both single disorder groups. TaqMan genotyping data were used to create final prediction models, which differentiated between PCOS+HT and PCOS or HT with a prediction accuracy of AUC = 0.78. Using a 70% cutoff of the prediction score improved the model parameters, increasing the AUC value to 0.87. In summary, we demonstrated the polygenic burden of both PCOS and HT, and many common and intersecting signaling pathways and biological processes whose disorders mutually predispose patients to the development of both diseases.

Rosavidin protects against PM2.5-induced lung toxicity via inhibition of NLRP3 inflammasome-mediated pyroptosis by activating the PI3K/AKT pathway

Fine particulate matter (PM2.5) contributes to adverse health effects through the promotion of inflammatory cytokine release. Rosavidin (Ro), a phenylpropanoid compound having multiple biological activities, is extracted from Rhodiola crenulata, a medicine and food homology plant. However, the protective role and mechanism of Ro in PM2.5-induced lung toxicity have not been previously studied. This study aimed to investigate the potential protective effect and mechanism of Ro in PM2.5-induced lung toxicity. A lung toxicity rat model was established through trachea drip of PM2.5 suspension after the different dose pretreatment of Ro (50 mg/kg and 100 mg/kg) to evaluate the effect of Ro on PM2.5 caused lung toxicity. The results showed that Ro attenuated the pathological changes, edema, and inflammation response in rats. The PI3K/AKT signaling pathway may be associated with the protective effect of Ro against pulmonary toxicity. Subsequently, we verified the role of PI3K/AKT in the PM2.5 exposure lung tissue. Moreover, expression levels of p-PI3K and p-AKT were lower, and those of NLRP3, ASC, cleaved caspase-1, cleaved IL-1β, and GSDMD-N were higher in PM2.5 group compared to those in control group. Whereas pre-administration of Ro reversed the expression trends of these proteins in lung tissue. Notably, those protective effects of Ro were not observed after pretreatment with a combination of Ro with nigericin or LY294002. These results indicate that Ro mitigates PM2.5-caused lung toxicity by inhibiting NLRP3 inflammasome-mediated pyroptosis through activation of the PI3K/AKT signaling pathway.

Biallelic loss of function variants in WBP4, encoding a spliceosome protein, result in a variable neurodevelopmental delay syndrome

Over two dozen spliceosome proteins are involved in human diseases, also referred to as spliceosomopathies. WBP4 (WW Domain Binding Protein 4) is part of the early spliceosomal complex, and was not described before in the context of human pathologies. Ascertained through GeneMatcher we identified eleven patients from eight families, with a severe neurodevelopmental syndrome with variable manifestations. Clinical manifestations included hypotonia, global developmental delay, severe intellectual disability, brain abnormalities, musculoskeletal and gastrointestinal abnormalities. Genetic analysis revealed overall five different homozygous loss-of-function variants in WBP4. Immunoblotting on fibroblasts from two affected individuals with different genetic variants demonstrated complete loss of protein, and RNA sequencing analysis uncovered shared abnormal splicing patterns, including enrichment for abnormalities of the nervous system and musculoskeletal system genes, suggesting that the overlapping differentially spliced genes are related to the common phenotypes of the probands. We conclude that biallelic variants in WBP4 cause a spliceosomopathy. Further functional studies are called for better understanding of the mechanism of pathogenicity.

Dynamic chromatin accessibility during nutritional iron overload reveals a BMP6-independent induction of cell cycle genes

Iron is essential to organism physiology as it participates in numerous biological processes including oxygen transport, respiration and erythropoiesis. Although iron is critical to physiology, excess iron is toxic to cells and tissues due to generation of reactive oxygen species. Therefore, well-kept iron homeostasis is a mainstay of proper cell and organ function. Iron overload disorders, caused by nutritional or genetic factors, contribute to many pathologies such as diabetes, non-alcoholic steatohepatitis and hepatocellular carcinoma. The liver is not only vulnerable to the effects of iron overload, it is also the major organ controlling iron homeostasis. During iron overload, Bone Morphogenic Protein (BMP) levels increase and initiate a hepatic response aimed at lowering iron levels. The transcriptional effects of iron overload are not well-characterized and the underlining enhancer regulation is uncharted. Here, we profiled the liver's transcriptome and chromatin accessibility following nutritional iron overload. We found marked changes in gene expression and enhancer accessibility following iron overload. Surprisingly, 16% of genes induced following iron overload participate in propagating the cell cycle. Induction of cell cycle genes was independent of BMP. Genome-wide enhancer landscape profiling revealed hundreds of enhancers with altered activity following iron overload. Characterization of transcription factor motifs and footprints in iron-regulated enhancers showed a role for the Activator Protein 1 (AP-1) transcription factor in promoting cell cycle-related transcription. In summary, we found that the transcriptional program at play during iron overload is bifurcated in which BMP signaling controls iron homeostasis genes while an AP-1-driven program controls cell cycle genes.

A pangenome reference of 36 Chinese populations

Human genomics is witnessing an ongoing paradigm shift from a single reference sequence to a pangenome form, but populations of Asian ancestry are underrepresented. Here we present data from the first phase of the Chinese Pangenome Consortium, including a collection of 116 high-quality and haplotype-phased de novo assemblies based on 58 core samples representing 36 minority Chinese ethnic groups. With an average 30.65× high-fidelity long-read sequence coverage, an average contiguity N50 of more than 35.63 megabases and an average total size of 3.01 gigabases, the CPC core assemblies add 189 million base pairs of euchromatic polymorphic sequences and 1,367 protein-coding gene duplications to GRCh38. We identified 15.9 million small variants and 78,072 structural variants, of which 5.9 million small variants and 34,223 structural variants were not reported in a recently released pangenome reference¹. The Chinese Pangenome Consortium data demonstrate a remarkable increase in the discovery of novel and missing sequences when individuals are included from underrepresented minority ethnic groups. The missing reference sequences were enriched with archaic-derived alleles and genes that confer essential functions related to keratinization, response to ultraviolet radiation, DNA repair, immunological responses and lifespan, implying great potential for shedding new light on human evolution and recovering missing heritability in complex disease mapping.

LIS1 RNA-binding orchestrates the mechanosensitive properties of embryonic stem cells in AGO2-dependent and independent ways

Lissencephaly-1 (LIS1) is associated with neurodevelopmental diseases and is known to regulate the molecular motor cytoplasmic dynein activity. Here we show that LIS1 is essential for the viability of mouse embryonic stem cells (mESCs), and it governs the physical properties of these cells. LIS1 dosage substantially affects gene expression, and we uncovered an unexpected interaction of LIS1 with RNA and RNA-binding proteins, most prominently the Argonaute complex. We demonstrate that LIS1 overexpression partially rescued the extracellular matrix (ECM) expression and mechanosensitive genes conferring stiffness to Argonaute null mESCs. Collectively, our data transforms the current perspective on the roles of LIS1 in post-transcriptional regulation underlying development and mechanosensitive processes.

Expression Signature of Immune-Related MicroRNAs in Autoimmune Skin Disease: Psoriasis and Vitiligo Insights

BACKGROUND

Psoriasis and vitiligo are both chronic, skin-specific diseases classified as autoimmune diseases due to the involvement of several biochemical pathways in their pathogenesis, similar to those altered in other autoimmune diseases. The role of miRNAs in regulating skin autoimmune function has yet to be fully characterized.

AIM

The aim of this study was to assess the expression profile of a panel of 11 circulating immune-related miRNAs in patients with autoimmune skin diseases, specifically psoriasis and vitiligo, and correlate their expression signature with the clinicopathological features of the diseases.

SUBJECTS AND METHODS

Relative gene expression quantification for 11 immune-related circulating miRNAs in plasma was done for 300 subjects-100 patients with psoriasis, 100 patients with vitiligo and 100 normal healthy volunteers-followed by different modalities of bioinformatics analysis for the results.

RESULTS

The expression levels of all the studied immune-related miRNAs were elevated in both autoimmune skin disorders, with much higher levels of expression in psoriasis than in vitiligo patients. There was a significant correlation between most of the studied miRNAs, suggesting shared target genes and/or pathways. Moreover, all the studied miRNAs showed significant results as biomarkers for autoimmune skin disease, with miRNA-145 being the best candidate. Regarding the clinicopathological data, miRNA-7, miRNA-9, miRNA-145, miRNA-148a, and miRNA-148b were positively correlated with age. All the miRNAs were inversely correlated with obesity and disease duration.

CONCLUSION

This study highlights the critical role of miRNAs in skin-specific autoimmune diseases that proved to be potential biomarkers for autoimmune skin disorders, warranting their exploration as therapeutic targets.

Multiple Forms of Neural Cell Death in the Cyclical Brain Degeneration of A Colonial Chordate

Human neuronal loss occurs through different cellular mechanisms, mainly studied in vitro. Here, we characterized neuronal death in B. schlosseri, a marine colonial tunicate that shares substantial genomic homology with mammals and has a life history in which controlled neurodegeneration happens simultaneously in the brains of adult zooids during a cyclical phase named takeover. Using an ultrastructural and transcriptomic approach, we described neuronal death forms in adult zooids before and during the takeover phase while comparing adult zooids in takeover with their buds where brains are refining their structure. At takeover, we found in neurons clear morphologic signs of apoptosis (i.e., chromatin condensation, lobed nuclei), necrosis (swollen cytoplasm) and autophagy (autophagosomes, autolysosomes and degradative multilamellar bodies). These results were confirmed by transcriptomic analyses that highlighted the specific genes involved in these cell death pathways. Moreover, the presence of tubulovesicular structures in the brain medulla alongside the over-expression of prion disease genes in late cycle suggested a cell-to-cell, prion-like propagation recalling the conformational disorders typical of some human neurodegenerative diseases. We suggest that improved understanding of how neuronal alterations are regulated in the repeated degeneration-regeneration program of B. schlosseri may yield mechanistic insights relevant to the study of human neurodegenerative diseases.

Computational network analysis of host genetic risk variants of severe COVID-19

BACKGROUND

Genome-wide association studies have identified numerous human host genetic risk variants that play a substantial role in the host immune response to SARS-CoV-2. Although these genetic risk variants significantly increase the severity of COVID-19, their influence on body systems is poorly understood. Therefore, we aim to interpret the biological mechanisms and pathways associated with the genetic risk factors and immune responses in severe COVID-19. We perform a deep analysis of previously identified risk variants and infer the hidden interactions between their molecular networks through disease mapping and the similarity of the molecular functions between constructed networks.

RESULTS

We designed a four-stage computational workflow for systematic genetic analysis of the risk variants. We integrated the molecular profiles of the risk factors with associated diseases, then constructed protein-protein interaction networks. We identified 24 protein-protein interaction networks with 939 interactions derived from 109 filtered risk variants in 60 risk genes and 56 proteins. The majority of molecular functions, interactions and pathways are involved in immune responses; several interactions and pathways are related to the metabolic and cardiovascular systems, which could lead to multi-organ complications and dysfunction.

CONCLUSIONS

This study highlights the importance of analyzing molecular interactions and pathways to understand the heterogeneous susceptibility of the host immune response to SARS-CoV-2. We propose new insights into pathogenicity analysis of infections by including genetic risk information as essential factors to predict future complications during and after infection. This approach may assist more precise clinical decisions and accurate treatment plans to reduce COVID-19 complications.

Introducing Circulating Vasculature-Related Transcripts as Biomarkers in Coronary Artery Disease

BACKGROUND

Atherosclerotic plaque is considered the hallmark of atherosclerotic lesions in coronary atherosclerosis (CAS), the primary pathogenesis in coronary artery disease (CAD), which develops and progresses through a complex interplay between immune cells, vascular cells, and endothelial shear stresses. Early diagnosis of CAS is critical for avoiding plaque rupture and sudden death. Therefore, identifying new CAD biomarkers linked to vessel wall functions, such as RNA molecules with their distinct signature, is a promising development for these patients. With this rationale, the present study investigated the expression level of the vascular-related RNA transcripts (lncRNA ANRIL, miRNA-126-5p, CDK4, CDK6, TGF-β, E-cadherin, and TNF-α) implicated in the cellular vascular function, proliferation, and inflammatory processes.

METHODS

A case-control study design with a total of 180 subjects classified participants into two groups; CAD and control groups. The relative expression levels of the seven transcripts under study-selected using online bioinformatics tools and current literature-were assessed in the plasma of all study participants using RT-qPCR. Their predictive significance testing, scoring of disease prioritization, enrichment analysis, and the miRNA-mRNA regulatory network was investigated.

RESULTS

The relative expression levels of all seven of the circulating vascular-related transcripts under study were statistically significant between CAD patients and controls. Receiver operating characteristic (ROC) analysis results indicated the statistical significance of all the transcripts under study with CDK4 showing the highest area under the curve (AUC) equivalent to 0.91, followed by E-cadherin (0.90), miRNA-126-5p (0.83), ANRIL (0.82), TNF-α (0.63), TGF-β (0.62), and CDK6 (0.59), in descending order. A strong association was detected between most of the transcripts studied in CAD patients with a significant Spearman's correlation coefficient with a two-tailed significance of p < 0.001. Network analysis revealed a strong relationship between the five circulating vasculature transcripts studied and their target miRNAs and miR-126-5p, but not for ANRIL.

CONCLUSION

The seven circulating vascular-related RNA transcripts under study could serve as potential CAD biomarkers, reflecting the cellular vascular function, proliferation, and inflammatory processes in CAD patients. Therefore, blood transcriptome analysis opens new frontiers for the non-invasive diagnosis of CAD.

Leveraging GWAS data derived from a large cooperative group trial to assess the risk of taxane-induced peripheral neuropathy (TIPN) in patients being treated for breast cancer: Part 2-functional implications of a SNP cluster associated with TIPN risk in patients being treated for breast cancer

INTRODUCTION

Using GWAS data derived from a large collaborative trial (ECOG-5103), we identified a cluster of 267 SNPs which predicted CIPN in treatment-naive patients as reported in Part 1 of this study. To assess the functional and pathological implications of this set, we identified collective gene signatures were and evaluated the informational value of those signatures in defining CIPN's pathogenesis.

METHODS

In Part 1, we analyzed GWAS data derived from ECOG-5103, first identifying those SNPs that were most strongly associated with CIPN using Fisher's ratio. After identifying those SNPs which differentiated CIPN-positive from CIPN-negative phenotypes, we ranked them in order of their discriminatory power to produce a cluster of SNPs which provided the highest predictive accuracy using leave-one-out cross validation (LOOCV). An uncertainty analysis was included. Using the best predictive SNP cluster, we performed gene attribution for each SNP using NCBI Phenotype Genotype Integrator and then assessed functionality by applying GeneAnalytics, Gene Set Enrichment Analysis, and PCViz.

RESULTS

Using aggregate data derived from the GWAS, we identified a 267 SNP cluster which was associated with a CIPN+ phenotype with an accuracy of 96.1%. We could attribute 173 genes to the 267 SNP cluster. Six long intergenic non-protein coding genes were excluded. Ultimately, the functional analysis was based on 138 genes. Of the 17 pathways identified by Gene Analytics (GA) software, the irinotecan pharmacokinetic pathway had the highest score. Highly matching gene ontology attributions included flavone metabolic process, flavonoid glucuronidation, xenobiotic glucuronidation, nervous system development, UDP glycosyltransferase activity, retinoic acid binding, protein kinase C binding, and glucoronosyl transferase activity. Gene Set Enrichment Analysis (GSEA) GO terms identified neuron-associated genes as most significant (p = 5.45e-10). Consistent with the GA's output, flavone, and flavonoid associated terms, glucuronidation were noted as were GO terms associated with neurogenesis.

CONCLUSION

The application of functional analyses to phenotype-associated SNP clusters provides an independent validation step in assessing the clinical meaningfulness of GWAS-derived data. Functional analyses following gene attribution of a CIPN-predictive SNP cluster identified pathways, gene ontology terms, and a network which were consistent with a neuropathic phenotype.

The hitchhikers' guide to RNA sequencing and functional analysis

DNA and RNA sequencing technologies have revolutionized biology and biomedical sciences, sequencing full genomes and transcriptomes at very high speeds and reasonably low costs. RNA sequencing (RNA-Seq) enables transcript identification and quantification, but once sequencing has concluded researchers can be easily overwhelmed with questions such as how to go from raw data to differential expression (DE), pathway analysis and interpretation. Several pipelines and procedures have been developed to this effect. Even though there is no unique way to perform RNA-Seq analysis, it usually follows these steps: 1) raw reads quality check, 2) alignment of reads to a reference genome, 3) aligned reads' summarization according to an annotation file, 4) DE analysis and 5) gene set analysis and/or functional enrichment analysis. Each step requires researchers to make decisions, and the wide variety of options and resulting large volumes of data often lead to interpretation challenges. There also seems to be insufficient guidance on how best to obtain relevant information and derive actionable knowledge from transcription experiments. In this paper, we explain RNA-Seq steps in detail and outline differences and similarities of different popular options, as well as advantages and disadvantages. We also discuss non-coding RNA analysis, multi-omics, meta-transcriptomics and the use of artificial intelligence methods complementing the arsenal of tools available to researchers. Lastly, we perform a complete analysis from raw reads to DE and functional enrichment analysis, visually illustrating how results are not absolute truths and how algorithmic decisions can greatly impact results and interpretation.

Study on the role of calcium channel protein TRPV4 in the inflammatory pathway of type 2 diabetic adipose tissue based on gene databases

BACKGROUND

Chronic inflammation of adipose tissue may be one of the key factors contributing to the development of insulin resistance in T2DM adipose tissue. Transient receptor potential vanilloid type 4 (TRPV4) can be involved in a variety of cellular inflammatory responses. In this study, we evaluated the role of TRPV4 channelin in the T2DM adipose tissue inflammatory pathway.

METHODS

Based on the gene expression profiling data of the public database, bioinformatics methods were used to screen the target gene population of the TRPV4 channel protein involved in the regulation of T2DM fat cells. A mature adipocyte model was constructed to verify the expression level of target genes and to evaluate the regulatory effect of TRPV4 channel inhibition on target genes of inflammation-related pathways.

RESULTS

In shTRPV4 adipocytes, 144 genes with downregulation expression were screened, a PPI network was constructed and a core module containing 15 genes was screened out, and the core genes were mainly enriched in the Toll-like receptor signaling pathway through enrichment analysis. Constructing a mature adipocyte model found that the TRPV4 inhibitor HC067047 inhibited the effect of upregulation of the expression level of the relevant gene in the signaling pathway.

CONCLUSIONS

Our findings suggest that the expression of highly expressed pro-inflammatory cytokines and chemokines in T2DM adipose tissue decreases after inhibiting the expression of TRPV4 in adipocytes, suggesting that TRPV4 may become a potential drug target for the treatment of T2DM.

Methylome-wide association study of different responses to risperidone in schizophrenia

Background: Accumulating evidence shows that DNA methylation plays a role in antipsychotic response. However, the mechanisms by which DNA methylation changes are associated with antipsychotic responses remain largely unknown. Methods: We performed a methylome-wide association study (MWAS) to evaluate the association between DNA methylation and the response to risperidone in schizophrenia. Genomic DNA methylation patterns were assessed using the Agilent Human DNA Methylation Microarray. Results: We identified numerous differentially methylated positions (DMPs) and regions (DMRs) associated with antipsychotic response. CYP46A1, SPATS2, and ATP6V1E1 had the most significant DMPs, with p values of 2.50 × 10^-6, 3.53 × 10^-6, and 5.71 × 10^-6, respectively. The top-ranked DMR was located on chromosome 7, corresponding to the PTPRN2 gene with a Šidák-corrected p-value of 9.04 × 10^-13. Additionally, a significant enrichment of synaptic function and neurotransmitters was found in the differentially methylated genes after gene ontology and pathway analysis. Conclusion: The identified DMP- and DMR-overlapping genes associated with antipsychotic response are related to synaptic function and neurotransmitters. These findings may improve understanding of the mechanisms underlying antipsychotic response and guide the choice of antipsychotic in schizophrenia.

A seven-transmembrane protein-TM7SF3, resides in nuclear speckles and regulates alternative splicing

The seven-transmembrane superfamily member 3 protein (TM7SF3) is a p53-regulated homeostatic factor that attenuates cellular stress and the unfolded protein response. Here we show that TM7SF3 localizes to nuclear speckles; eukaryotic nuclear bodies enriched in splicing factors. This unexpected location for a trans -membranal protein enables formation of stable complexes between TM7SF3 and pre-mRNA splicing factors including DHX15, LARP7, HNRNPU, RBM14, and HNRNPK. Indeed, TM7SF3 regulates alternative splicing of >330 genes, mainly at the 3'end of introns by directly modulating the activity of splicing factors such as HNRNPK. These effects are observed both in cell lines and primary human pancreatic islets. Accordingly, silencing of TM7SF3 results in differential expression of 1465 genes (about 7% of the human genome); with 844 and 621 genes being up- or down-regulated, respectively. Our findings implicate TM7SF3, as a resident protein of nuclear speckles and suggest a role for seven-transmembrane proteins as regulators of alternative splicing.

Biological and disease hallmarks of Alzheimer’s disease defined by Alzheimer’s disease genes

An increasing number of genes associated with Alzheimer’s disease (AD genes) have been reported. However, there is a lack of an overview of the genetic relationship between AD and age-related comorbidities, such as hypertension, myocardial infarction, and diabetes, among others. Previously, we used Reactome analysis in conjunction with the AD genes to identify both the biological pathways and the neurological diseases. Here we provide systematic updates on the genetic and disease hallmarks defined by AD genes. The analysis identified 50 pathways (defined as biological hallmarks). Of them, we have successfully compiled them into a total of 11 biological hallmarks, including 6 existing hallmarks and 5 newly updated hallmarks. The AD genes further identified 20 diverse diseases (defined as disease hallmarks), summarized into three major categories: (1) existing hallmarks, including neurological diseases; (2) newly identified hallmarks, including common age-related diseases such as diabetes, hypertension, other cardiovascular diseases, and cancers; (3) and other health conditions; note that cancers reportedly have an inverse relation with AD. We previously suggested that a single gene is associated with multiple neurological diseases, and we are further extending the finding that AD genes are associated with common age-related comorbidities and others. This study indicates that the heterogeneity of Alzheimer’s disease predicts complex clinical presentations in people living with AD. Taken together, the genes define AD as a part of age-related comorbidities with shared biological mechanisms and may raise awareness of a healthy lifestyle as potential prevention and treatment of the comorbidities.

Circulating microRNA203 and its target genes' role in psoriasis pathogenesis

Numerous microRNAs (miRNAs) have been found to have an aberrant expression in the peripheral blood or psoriasis patients' lesions. Psoriasis was shown to have the abnormal expression of microRNA-203 (miR-203). It is a skin-specific signal that governs cellular proliferation in a protein kinase C-dependent manner and is mostly generated by keratinocytes. This work evaluated the expression levels of the circulating miR-203 target genes SOCS3, SOCS6, TP63, TNF-, IL8, and IL24 in psoriasis patients. Using a relative quantitation PCR technique, we determined the expression levels of miR-203 and its target genes (SOCS3, SOCS6, TP63, TNF-, IL8, and IL24) in the plasma of 120 psoriatic patients and matched healthy controls. The disease characteristics of the patients were then correlated with the expression results. We also conducted numerous enrichment analyses for the diseases, functions, and pathways connected to the under-researched biomarkers. Compared to healthy controls, psoriatic patients had significantly increased levels of miR-203 expression; 7.1 (4.4–9.9). In contrast, psoriatic patients had significantly lower expression of all the examined genes compared to healthy controls. Regarding all the study biomarkers, the receiver operating characteristic (ROC) curve analysis demonstrated significant sensitivity and specificity for differentiating between psoriatic patients and healthy controls. According to the results of the disease matching score generated by miR-203 and its target genes, psoriasis was ranked first with a score of 4.45. The third-place finisher with a value of 3.98, it also demonstrated that miR-203 and its target genes are connected to various skin disorders. Our results show that miR-203 contributes to psoriasis pathogenesis not only locally in skin lesions but also in circulation, indicating that it may contribute to the systemic symptoms of the illness. MiR-203 overexpression in psoriasis suggests that miR-203 may be involved in an anti-inflammatory response because it targets both SOCS gene family members and pro-inflammatory cytokines.

In vivo and in vitro genome editing to explore GNE functions

GNE myopathy is an adult onset neuromuscular disorder characterized by slowly progressive distal and proximal muscle weakness, caused by missense recessive mutations in the GNE gene. Although the encoded bifunctional enzyme is well known as the limiting factor in the biosynthesis of sialic acid, no clear mechanisms have been recognized to account for the muscle atrophic pathology, and novel functions for GNE have been hypothesized. Two major issues impair studies on this protein. First, the expression of the GNE protein is minimal in human and mice muscles and there is no reliable antibody to follow up endogenous expression. Second, no reliable animal model is available for the disease and cellular models from GNE myopathy patients’ muscle cells (expressing the mutated protein) are less informative than expected. In order to broaden our knowledge on GNE functions in muscle, we have taken advantage of the CRISPR/Cas9 method for genome editing to first, add a tag to the endogenous Gne gene in mouse, allowing the determination of the spatiotemporal expression of the protein in the organism, using well established and reliable antibodies against the specific tag. In addition we have generated a Gne knock out murine muscle cell lineage to identify the events resulting from the total lack of the protein. A thorough multi-omics analysis of both cellular systems including transcriptomics, proteomics, phosphoproteomics and ubiquitination, unraveled novel pathways for Gne, in particular its involvement in cell cycle control and in the DNA damage/repair pathways. The elucidation of fundamental mechanisms of Gne in normal muscle may contribute to the identification of the disrupted functions in GNE myopathy, thus, to the definition of novel biomarkers and possible therapeutic targets for this disease.

RNA-seq and ChIP-seq Identification of Unique and Overlapping Targets of GLI Transcription Factors in Melanoma Cell Lines

BACKGROUND

Despite significant progress in therapy, melanoma still has a rising incidence worldwide, and novel treatment strategies are needed. Recently, researchers have recognized the involvement of the Hedgehog-GLI (HH-GLI) signaling pathway in melanoma and its consistent crosstalk with the MAPK pathway. In order to further investigate the link between the two pathways and to find new target genes that could be considered for combination therapy, we set out to find transcriptional targets of all three GLI proteins in melanoma.

METHODS

We performed RNA sequencing on three melanoma cell lines (CHL-1, A375, and MEL224) with overexpressed GLI1, GLI2, and GLI3 and combined them with the results of ChIP-sequencing on endogenous GLI1, GLI2, and GLI3 proteins. After combining these results, 21 targets were selected for validation by qPCR.

RESULTS

RNA-seq revealed a total of 808 differentially expressed genes (DEGs) for GLI1, 941 DEGs for GLI2, and 58 DEGs for GLI3. ChIP-seq identified 527 genes that contained GLI1 binding sites in their promoters, 1103 for GLI2 and 553 for GLI3. A total of 15 of these targets were validated in the tested cell lines, 6 of which were detected by both RNA-seq and ChIP-seq.

CONCLUSIONS

Our study provides insight into the unique and overlapping transcriptional output of the GLI proteins in melanoma. We suggest that our findings could provide new potential targets to consider while designing melanoma-targeted therapy.

Lung adenocarcinoma-related target gene prediction and drug repositioning

Lung cancer is the leading cause of cancer deaths globally, and lung adenocarcinoma (LUAD) is the most common type of lung cancer. Gene dysregulation plays an essential role in the development of LUAD. Drug repositioning based on associations between drug target genes and LUAD target genes are useful to discover potential new drugs for the treatment of LUAD, while also reducing the monetary and time costs of new drug discovery and development. Here, we developed a pipeline based on machine learning to predict potential LUAD-related target genes through established graph attention networks (GATs). We then predicted potential drugs for the treatment of LUAD through gene coincidence-based and gene network distance-based methods. Using data from 535 LUAD tissue samples and 59 precancerous tissue samples from The Cancer Genome Atlas, 48,597 genes were identified and used for the prediction model building of the GAT. The GAT model achieved good predictive performance, with an area under the receiver operating characteristic curve of 0.90. 1,597 potential LUAD-related genes were identified from the GAT model. These LUAD-related genes were then used for drug repositioning. The gene overlap and network distance with the target genes were calculated for 3,070 drugs and 672 preclinical compounds approved by the US Food and Drug Administration. At which, bromoethylamine was predicted as a novel potential preclinical compound for the treatment of LUAD, and cimetidine and benzbromarone were predicted as potential therapeutic drugs for LUAD. The pipeline established in this study presents new approach for developing targeted therapies for LUAD.

Transcriptome changes in DM1 patients’ tissues are governed by the RNA interference pathway

Myotonic dystrophy type 1 (DM1) is a multisystemic disease caused by pathogenic expansions of CTG repeats. The expanded repeats are transcribed to long RNA and induce cellular toxicity. Recent studies suggest that the CUG repeats are processed by the RNA interference (RNAi) pathway to generate small interfering repeated RNA (siRNA). However, the effects of the CTG repeat-derived siRNAs remain unclear. We hypothesize that the RNAi machinery in DM1 patients generates distinct gene expression patterns that determine the disease phenotype in the individual patient. The abundance of genes with complementary repeats that are targeted by siRNAs in each tissue determines the way that the tissue is affected in DM1. We integrated and analyzed published transcriptome data from muscle, heart, and brain biopsies of DM1 patients, and revealed shared, characteristic changes that correlated with disease phenotype. These signatures are overrepresented by genes and transcription factors bearing endogenous CTG/CAG repeats and are governed by aberrant activity of the RNAi machinery, miRNAs, and a specific gain-of-function of the CTG repeats. Computational analysis of the DM1 transcriptome enhances our understanding of the complex pathophysiology of the disease and may reveal a path for cure.

Investigating melanogenesis-related microRNAs as disease biomarkers in vitiligo

Vitiligo is considered a disabling disease that affects physical, social, psychological, and occupational aspects of an individual's quality of life. The search for non-invasive and reliable biomarkers for vitiligo's early diagnosis, prognosis, and treatment prediction is under intensive investigation. There is currently an emerging interest in employing miRNAs as biomarkers to predict vitiligo diagnosis and prognosis, inspired by the well-preserved nature of miRNAs in serum or plasma. In the current study, we assessed a panel of 20 melanogenesis pathway-related microRNAs (miRNAs) using quantitative real-time PCR technique in 85 non-segmental vitiligo (NSV) patients compared to 85 normal controls followed by function and pathway enrichment analysis for the miRNAs with significant results. Twelve out of the 20 circulating miRNAs showed significantly higher expression levels in vitiligo patients relative to controls where miR-423 show the highest expression level followed by miR-182, miR-106a, miR-23b, miR-9, miR-124, miR-130a, miR-203a, miR-181, miR-152, and miR-320a. While six miRNAs (miR-224, miR-148a, miR-137, and miR-7, miR-148b, miR-145, miR-374b, and miR-196b) didn’t show significant expression level. The analysis of the receiver operating curve indicated that miR-423, miR-106a, and miR-182 were outstanding biomarkers with the highest areas under the curve in vitiligo. This study is the first Egyptian study to investigate a panel of miRNAs expression profile in the plasma of patients with NSV. Our results suggest that specific circulating miRNAs signature might be implicated in vitiligo pathogenesis and could potentially be used as biomarkers in vitiligo.

Game-theoretic link relevance indexing on genome-wide expression dataset identifies putative salient genes with potential etiological and diapeutics role in colorectal cancer

Diapeutics gene markers in colorectal cancer (CRC) can help manage mortality caused by the disease. We applied a game-theoretic link relevance Index (LRI) scoring on the high-throughput whole-genome transcriptome dataset to identify salient genes in CRC and obtained 126 salient genes with LRI score greater than zero. The biomarkers database lacks preliminary information on the salient genes as biomarkers for all the available cancer cell types. The salient genes revealed eleven, one and six overrepresentations for major Biological Processes, Molecular Function, and Cellular components. However, no enrichment with respect to chromosome location was found for the salient genes. Significantly high enrichments were observed for several KEGG, Reactome and PPI terms. The survival analysis of top protein-coding salient genes exhibited superior prognostic characteristics for CRC. MIR143HG, AMOTL1, ACTG2 and other salient genes lack sufficient information regarding their etiological role in CRC. Further investigation in LRI methodology and salient genes to augment the existing knowledge base may create new milestones in CRC diapeutics.

ExAgBov: A public database of annotated variations from hundreds of bovine whole-exome sequencing samples

Large reference datasets of annotated genetic variations from genome-scale sequencing are essential for interpreting identified variants, their functional impact, and their possible contribution to diseases and traits. However, to date, no such database of annotated variation from broad cattle populations is publicly available. To overcome this gap and advance bovine NGS-driven variant discovery and interpretation, we obtained and analyzed raw data deposited in the SRA public repository. Short reads from 262 whole-exome sequencing samples of Bos Taurus were mapped to the Bos Taurus ARS-UCD1.2 reference genome. The GATK best practice workflow was applied for variant calling. Comprehensive annotation of all recorded variants was done using the Ensembl Variant Effect Predictor (VEP). An in-depth analysis of the population structure revealed the breeds comprising the database. The Exomes Aggregate of Bovine- ExAgBov is a comprehensively annotated dataset of more than 20 million short variants, of which ~2% are located within open reading frames, splice regions, and UTRs, and more than 60,000 variants are predicted to be deleterious.

Heterogeneous nuclear ribonucleoprotein U (HNRNPU) safeguards the developing mouse cortex

HNRNPU encodes the heterogeneous nuclear ribonucleoprotein U, which participates in RNA splicing and chromatin organization. Microdeletions in the 1q44 locus encompassing HNRNPU and other genes and point mutations in HNRNPU cause brain disorders, including early-onset seizures and severe intellectual disability. We aimed to understand HNRNPU’s roles in the developing brain. Our work revealed that HNRNPU loss of function leads to rapid cell death of both postmitotic neurons and neural progenitors, with an apparent higher sensitivity of the latter. Further, expression and alternative splicing of multiple genes involved in cell survival, cell motility, and synapse formation are affected following Hnrnpu’s conditional truncation. Finally, we identified pharmaceutical and genetic agents that can partially reverse the loss of cortical structures in Hnrnpu mutated embryonic brains, ameliorate radial neuronal migration defects and rescue cultured neural progenitors’ cell death.

HNRNPU is an RNA splicing protein associated with brain disorders such as early onset seizures. Here they show that HNRNPU functions to maintain neural progenitors and their progeny by regulating splicing of key neuronal genes.

Two distinct evolutionary conserved neural degeneration pathways characterized in a colonial chordate

Colonial tunicates are marine organisms that possess multiple brains simultaneously during their colonial phase. While the cyclical processes of neurogenesis and neurodegeneration characterizing their life cycle have been documented previously, the cellular and molecular changes associated with such processes and their relationship with variation in brain morphology and individual (zooid) behavior throughout adult life remains unknown. Here, we introduce Botryllus schlosseri as an invertebrate model for neurogenesis, neural degeneration, and evolutionary neuroscience. Our analysis reveals that during the weekly colony budding (i.e., asexual reproduction), prior to programmed cell death and removal by phagocytes, decreases in the number of neurons in the adult brain are associated with reduced behavioral response and significant change in the expression of 73 mammalian homologous genes associated with neurodegenerative disease. Similarly, when comparing young colonies (1 to 2 y of age) to those reared in a laboratory for ∼20 y, we found that older colonies contained significantly fewer neurons and exhibited reduced behavioral response alongside changes in the expression of 148 such genes (35 of which were differentially expressed across both timescales). The existence of two distinct yet apparently related neurodegenerative pathways represents a novel platform to study the gene products governing the relationship between aging, neural regeneration and degeneration, and loss of nervous system function. Indeed, as a member of an evolutionary clade considered to be a sister group of vertebrates, this organism may be a fundamental resource in understanding how evolution has shaped these processes across phylogeny and obtaining mechanistic insight.

The lncRNA PRINS-miRNA-mRNA Axis Gene Expression Profile as a Circulating Biomarker Panel in Psoriasis

BACKGROUND

The interaction between genes and the environment in psoriasis is firmly coupled by epigenetic modification. Epigenetic modifications are inherited variations in gene expression devoid of DNA sequence alterations. Non-coding RNAs are regarded as one of the epigenetic modifications that lead eventually to enduring heritable variations in gene expression. In the present study, we chose the lncRNA, Psoriasis-susceptibility-Related RNA Gene Induced by Stress (PRINS) known to have a regulatory role in psoriasis and deduced its axis of lncRNA-miRNA-mRNA through an in silico data analysis. We aimed to assess the expression levels of this lncRNA-miRNA-mRNA in patients with psoriasis to elucidate their possible roles in psoriasis management.

METHODS

We investigated the lncRNA-PRINS and its target microRNAs (miRNA124-3p, miRNA203a-5p, miRNA129-5p, miRNA146a-5p, miRNA9-5p) and partner genes (NPM, G1P3) expression levels in the plasma of 120 patients with psoriasis compared to 120 healthy volunteers using quantitative real-time polymerase chain reaction and correlated the results with the patients' clinicopathological data. Finally, we performed a function, disease, and pathway enrichment analysis for the LncRNA-miRNA-mRNA axis under study.

RESULTS

The lncRNA PRINS, G1P3, and NPM genes showed significantly under-expressed levels while all miRNAs included in the study showed significant over-expression in patients with psoriasis relative to controls. The lncRNA PRINS, G1P3, and NPM genes showed a significant direct correlation with each other and inverse significant correlations with all miRNAs under study. All the study biomarkers showed significant results for discriminating between patients with psoriasis and controls using a receiver operating curve analysis with sensitivity over 90% except for PRINS, which was 74.2%. The G1P3 gene showed a direct significant correlation with body mass index in patients with psoriasis (p = 0.009) and an inverse significant correlation with age (p = 0.034). The NPM gene showed a significant correlation with body mass index in patients with psoriasis (p = 0.002).

CONCLUSIONS

Based on our results, we suggest that restoring the altered PRINS-miRNA-mRNA axis gene expression levels might represent a tool to prevent psoriasis worsening, along with standard therapy. Thus, on the clinical practice level, the PRINS-miRNA-mRNA axis expression profile can be utilized in designing specific targeted therapy aimed at applying a personalized medicine approach among patients with psoriasis.

Proteomic characterization of four subtypes of M2 macrophages derived from human THP-1 cells

Macrophages are widely distributed immune cells that contribute to tissue homeostasis. Human THP-1 cells have been widely used in various macrophage-associated studies, especially those involving pro-inflammatory M1 and anti-inflammatory M2 phenotypes. However, the molecular characterization of four M2 subtypes (M2a, M2b, M2c, and M2d) derived from THP-1 has not been fully investigated. In this study, we systematically analyzed the protein expression profiles of human THP-1-derived macrophages (M0, M1, M2a, M2b, M2c, and M2d) using quantitative proteomics approaches. The commonly and specially regulated proteins of the four M2 subtypes and their potential biological functions were further investigated. The results showed that M2a and M2b, and M2c and M2d have very similar protein expression profiles. These data could serve as an important resource for studies of macrophages using THP-1 cells, and provide a reference to distinguish different M2 subtypes in macrophage-associated diseases for subsequent clinical research.

Hormone-controlled cooperative binding of transcription factors drives synergistic induction of fasting-regulated genes

During fasting, hepatocytes produce glucose in response to hormonal signals. Glucagon and glucocorticoids are principal fasting hormones that cooperate in regulating glucose production via gluconeogenesis. However, how these hormone signals are integrated and interpreted to a biological output is unknown. Here, we use genome-wide profiling of gene expression, enhancer dynamics and transcription factor (TF) binding in primary mouse hepatocytes to uncover the mode of cooperation between glucagon and glucocorticoids. We found that compared to a single treatment with each hormone, a dual treatment directs hepatocytes to a pro-gluconeogenic gene program by synergistically inducing gluconeogenic genes. The cooperative mechanism driving synergistic gene expression is based on ‘assisted loading’ whereby a glucagon-activated TF (cAMP responsive element binding protein; CREB) leads to enhancer activation which facilitates binding of the glucocorticoid receptor (GR) upon glucocorticoid stimulation. Glucagon does not only activate single enhancers but also activates enhancer clusters, thereby assisting the loading of GR also across enhancer units within the cluster. In summary, we show that cells integrate extracellular signals by an enhancer-specific mechanism: one hormone-activated TF activates enhancers, thereby assisting the loading of a TF stimulated by a second hormone, leading to synergistic gene induction and a tailored transcriptional response to fasting.

Uncovering Novel Pre-Treatment Molecular Biomarkers for Anti-TNF Therapeutic Response in Patients with Crohn’s Disease

Neutralising monoclonal antibodies for tumour necrosis factor (TNF) has been widely used to treat Crohn’s disease (CD) in clinical practice. However, differential individual response necessitates a therapeutic response assessment of anti-TNF agents in CD patients for optimizing therapeutic strategy. We aimed to predict anti-TNF therapy response in CD patients using transcriptome analyses. Transcriptome analyses were performed using data from the Gene Expression Omnibus, GeneCards, and Human Protein Atlas databases. The significantly mitigated biological functions associated with anti-TNF therapy resistance in CD patients encompassed immune pathways, including Interleukin-17 (IL-17) signaling, cytokine-cytokine receptor interaction, and rheumatoid arthritis. The scores of immune cell markers, including neutrophils, monocytes, and macrophages/monocytes were also significantly decreased in non-responders compared with that measured in anti-TNF therapy responders. The KAT2B gene, associated with IL-17 cytokine mediated neutrophil mobilization and activation, was significantly under-expressed in both tissue and peripheral blood mononuclear cells (PBMCs) in anti-TNF therapy-resistant CD patients. The reduced expression of several pro-inflammatory cytokines due to down-regulated IL-17 signaling, is suggestive of the primary non-response to anti-TNF agents in CD patients. Furthermore, the PBMC KAT2B gene signature may be a promising pre-treatment prognostic biomarker for anti-TNF drug response in CD patients.

Deciphering the link between Diabetes mellitus and SARS-CoV-2 infection through differential targeting of microRNAs in the human pancreas

PURPOSE

Coronavirus Disease 2019 (COVID-19) severity and Diabetes mellitus affect each other bidirectionally. However, the cause of severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) infection on the incidence of diabetes is unclear. In the SARS-CoV-2-infected cells, host microRNAs (miRNAs) may target the native gene transcripts as well as the viral genomic and subgenomic RNAs. Here, we investigated the role of miRNAs in linking Diabetes to SARS-CoV-2 infection in the human pancreas.

METHODS

Differential gene expression and disease enrichment analyses were performed on an RNA-Seq dataset of human embryonic stem cell-derived (hESC) mock-infected and SARS-CoV-2-infected pancreatic organoids to obtain the dysregulated Diabetes-associated genes. The miRNA target prediction for the Diabetes-associated gene transcripts and the SARS-CoV-2 RNAs has been made to determine the common miRNAs targeting them. Minimum Free Energy (MFE) analysis was done to identify the miRNAs, preferably targeting SARS-CoV-2 RNAs over the Diabetes-associated gene transcripts.

RESULTS

The gene expression and disease enrichment analyses of the RNA-Seq data have revealed five biomarker genes, i.e., CP, SOCS3, AGT, PSMB8 and CFB that are associated with Diabetes and get significantly upregulated in the pancreas following SARS-CoV-2-infection. Four miRNAs, i.e., hsa-miR-298, hsa-miR-3925-5p, hsa-miR-4691-3p and hsa-miR-5196-5p, showed preferential targeting of the SARS-CoV-2 genome over the cell's Diabetes-associated messenger RNAs (mRNAs) in the human pancreas.

CONCLUSION

Our study proposes that the differential targeting of the Diabetes-associated host genes by the miRNAs may lead to diabetic complications or new-onset Diabetes that can worsen the condition of COVID-19 patients.

Maternal effect genes: Update and review of evidence for a link with birth defects

Maternal effect genes (MEGs) encode factors (e.g., RNA) that are present in the oocyte and required for early embryonic development. Hence, while these genes and gene products are of maternal origin, their phenotypic consequences result from effects on the embryo. The first mammalian MEGs were identified in the mouse in 2000 and were associated with early embryonic loss in the offspring of homozygous null females. In humans, the first MEG was identified in 2006, in women who had experienced a range of adverse reproductive outcomes, including hydatidiform moles, spontaneous abortions, and stillbirths. Over 80 mammalian MEGs have subsequently been identified, including several that have been associated with phenotypes in humans. In general, pathogenic variants in MEGs or the absence of MEG products are associated with a spectrum of adverse outcomes, which in humans range from zygotic cleavage failure to offspring with multi-locus imprinting disorders. Although less established, there is also evidence that MEGs are associated with structural birth defects (e.g., craniofacial malformations, congenital heart defects). This review provides an updated summary of mammalian MEGs reported in the literature through early 2021, as well as an overview of the evidence for a link between MEGs and structural birth defects.

Systems biology analysis of human genomes points to key pathways conferring spina bifida risk

Genetic investigations of most structural birth defects, including spina bifida (SB), congenital heart disease, and craniofacial anomalies, have been underpowered for genome-wide association studies because of their rarity, genetic heterogeneity, incomplete penetrance, and environmental influences. Our systems biology strategy to investigate SB predisposition controls for population stratification and avoids much of the bias inherent in candidate gene searches that are pervasive in the field. We examine both protein coding and noncoding regions of whole genomes to analyze sequence variants, collapsed by gene or regulatory region, and apply machine learning, gene enrichment, and pathway analyses to elucidate molecular pathways and genes contributing to human SB.

Spina bifida (SB) is a debilitating birth defect caused by multiple gene and environment interactions. Though SB shows non-Mendelian inheritance, genetic factors contribute to an estimated 70% of cases. Nevertheless, identifying human mutations conferring SB risk is challenging due to its relative rarity, genetic heterogeneity, incomplete penetrance, and environmental influences that hamper genome-wide association studies approaches to untargeted discovery. Thus, SB genetic studies may suffer from population substructure and/or selection bias introduced by typical candidate gene searches. We report a population based, ancestry-matched whole-genome sequence analysis of SB genetic predisposition using a systems biology strategy to interrogate 298 case-control subject genomes (149 pairs). Genes that were enriched in likely gene disrupting (LGD), rare protein-coding variants were subjected to machine learning analysis to identify genes in which LGD variants occur with a different frequency in cases versus controls and so discriminate between these groups. Those genes with high discriminatory potential for SB significantly enriched pathways pertaining to carbon metabolism, inflammation, innate immunity, cytoskeletal regulation, and essential transcriptional regulation consistent with their having impact on the pathogenesis of human SB. Additionally, an interrogation of conserved noncoding sequences identified robust variant enrichment in regulatory regions of several transcription factors critical to embryonic development. This genome-wide perspective offers an effective approach to the interrogation of coding and noncoding sequence variant contributions to rare complex genetic disorders.

Triiodothyronine and dexamethasone alter potassium channel expression and promote electrophysiological maturation of human-induced pluripotent stem cell-derived cardiomyocytes

BACKGROUND

Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have emerged as a promising tool for disease modeling and drug development. However, hiPSC-CMs remain functionally immature, which hinders their utility as a model of human cardiomyocytes.

OBJECTIVE

To improve the electrophysiological maturation of hiPSC-CMs.

METHODS AND RESULTS

On day 16 of cardiac differentiation, hiPSC-CMs were treated with 100 nmol/L triiodothyronine (T3) and 1 μmol/L Dexamethasone (Dex) or vehicle for 14 days. On day 30, vehicle- and T3 + Dex-treated hiPSC-CMs were dissociated and replated either as cell sheets or single cells. Optical mapping and patch-clamp technique were used to examine the electrophysiological properties of vehicle- and T3 + Dex-treated hiPSC-CMs. Compared to vehicle, T3 + Dex-treated hiPSC-CMs had a slower spontaneous beating rate, more hyperpolarized resting membrane potential, faster maximal upstroke velocity, and shorter action potential duration. Changes in spontaneous activity and action potential were mediated by decreased hyperpolarization-activated current (I_f) and increased inward rectifier potassium currents (I_K1), sodium currents (I_Na), and the rapidly and slowly activating delayed rectifier potassium currents (I_Kr and I_Ks, respectively). Furthermore, T3 + Dex-treated hiPSC-CM cell sheets (hiPSC-CCSs) exhibited a faster conduction velocity and shorter action potential duration than the vehicle. Inhibition of I_K1 by 100 μM BaCl₂ significantly slowed conduction velocity and prolonged action potential duration in T3 + Dex-treated hiPSC-CCSs but had no effect in the vehicle group, demonstrating the importance of I_K1 for conduction velocity and action potential duration.

CONCLUSION

T3 + Dex treatment is an effective approach to rapidly enhance electrophysiological maturation of hiPSC-CMs.

POPBic: Pathway-Based Order Preserving Biclustering Algorithm Towards the Analysis of Gene Expression Data

To understand the underlying biological mechanisms of gene expression data, it is important to discover the groups of genes that have similar expression patterns under certain subsets of conditions. Biclustering algorithms have been effective in analyzing large-scale gene expression data. Recently, traditional biclustering has been improved by introducing biological knowledge along with the expression data during the biclustering process. In this paper, we propose the Pathway-based Order Preserving Biclustering (POPBic) algorithm by incorporating Kyoto Encyclopedia of Genes and Genomes (KEGG) based on the hypothesis that two genes sharing similar pathways are likely to be similar. The basic principle of the POPBic approach is to apply the concept of Longest Common Subsequence between a pair of genes which have a high number of common pathways. The algorithm identifies the expression patterns from data using two major steps: (i) selection of significant seed genes and (ii) extraction of biclusters. We performe exhaustive experimentation with the POPBic algorithm using synthetic dataset to evaluate the bicluster model, finding its robustness in the presence of noise and identifying overlapping biclusters. We demonstrate that POPBic is able to discover biologically significant biclusters for four cancer microarray gene expression datasets. POPBic has been found to perform consistently well in comparison to its closest competitors.

Effect of Tension on Human Periodontal Ligament Cells: Systematic Review and Network Analysis

Orthodontic tooth movement is based on the remodeling of tooth-surrounding tissues in response to mechanical stimuli. During this process, human periodontal ligament cells (hPDLCs) play a central role in mechanosensing and mechanotransduction. Various in vitro models have been introduced to investigate the effect of tension on hPDLCs. They provide a valuable body of knowledge on how tension influences relevant genes, proteins, and metabolites. However, no systematic review summarizing these findings has been conducted so far. Aim of this systematic review was to identify all related in vitro studies reporting tension application on hPDLCs and summarize their findings regarding force parameters, including magnitude, frequency and duration. Expression data of genes, proteins, and metabolites was extracted and summarized. Studies' risk of bias was assessed using tailored risk of bias tools. Signaling pathways were identified by protein-protein interaction (PPI) networks using STRING and GeneAnalytics. According to our results, Flexcell Strain Unit^® and other silicone-plate or elastic membrane-based apparatuses were mainly adopted. Frequencies of 0.1 and 0.5 Hz were predominantly applied for dynamic equibiaxial and uniaxial tension, respectively. Magnitudes of 10 and 12% were mostly employed for dynamic tension and 2.5% for static tension. The 10 most commonly investigated genes, proteins and metabolites identified, were mainly involved in osteogenesis, osteoclastogenesis or inflammation. Gene-set enrichment analysis and PPI networks gave deeper insight into the involved signaling pathways. This review represents a brief summary of the massive body of knowledge in this field, and will also provide suggestions for future researches on this topic.

Expanding the MECP2 network using comparative genomics reveals potential therapeutic targets for Rett syndrome

Inactivating mutations in the Methyl-CpG Binding Protein 2 (MECP2) gene are the main cause of Rett syndrome (RTT). Despite extensive research into MECP2 function, no treatments for RTT are currently available. Here, we used an evolutionary genomics approach to construct an unbiased MECP2 gene network, using 1028 eukaryotic genomes to prioritize proteins with strong co-evolutionary signatures with MECP2. Focusing on proteins targeted by FDA-approved drugs led to three promising targets, two of which were previously linked to MECP2 function (IRAK, KEAP1) and one that was not (EPOR). The drugs targeting these three proteins (Pacritinib, DMF, and EPO) were able to rescue different phenotypes of MECP2 inactivation in cultured human neural cell types, and appeared to converge on Nuclear Factor Kappa B (NF-κB) signaling in inflammation. This study highlights the potential of comparative genomics to accelerate drug discovery, and yields potential new avenues for the treatment of RTT.

PAX8 plays an essential antiapoptotic role in uterine serous papillary cancer

Endometrial carcinoma (EC) is the fourth-most common cancer in women in the United States, and generally carries a favorable prognosis. However, about 10% of EC patients have a rare and aggressive form, uterine serous papillary carcinoma (USPC), which carries a much higher mortality rate. The developmental transcription factor PAX8 is expressed in nearly 100% of USPCs. We show that PAX8 plays a critical antiapoptotic role in USPC and this role is established via transcriptional activation of two aberrant signaling pathways. First, PAX8 positively regulates mutated p53, and missense p53 mutations have an oncogenic gain of function effect. Second, PAX8 directly transcriptionally regulates p21, in a p53-independent manner, and p21 acquires a growth promoting role that is mediated via cytoplasmic localization of the protein. We propose that mutated p53 and cytoplasmic p21 can independently mediate the pro-proliferative role of PAX8 in USPC. In addition, we performed a genome-wide transcriptome analysis to detect pathways that are regulated by PAX8, and propose that metabolism and HIF-1alpha -related pathways are potential candidates for mediating the role of PAX8 in USPC. Taken together our findings demonstrate for the first time that PAX8 is an essential lineage marker in USPC, and suggest its mechanism of action.