Causal association and shared genetics between telomere length and COVID-19 outcomes: New evidence from the latest large-scale summary statistics

Background

Observational studies suggested that leukocyte telomere length (LTL) is shortened in COVID-19 patients. However, the genetic association and causality remained unknown.

Methods

Based on the genome-wide association of LTL (N = 472,174) and COVID-19 phenotypes (N = 1086,211-2597,856), LDSC and SUPERGNOVA were used to estimate the genetic correlation. Cross-trait GWAS meta-analysis, colocalization, fine-mapping analysis, and transcriptome-wide association study were conducted to explore the shared genetic etiology. Mendelian randomization (MR) was utilized to infer the causality. Upstream and downstream two-step MR was performed to investigate the potential mediating effects.

Results

LDSC identified a significant genetic association between LTL and all COVID-19 phenotypes (rG < 0, p < 0.05). Six significant regions were observed for LTL and COVID-19 susceptibility and hospitalization, respectively. Colocalization analysis found rs144204502, rs34517439, and rs56255908 were shared causal variants between LTL and COVID-19 phenotypes. Numerous biological pathways associated with LTL and COVID-19 outcomes were identified, mainly involved in -immune-related pathways. MR showed that longer LTL was significantly associated with a lower risk of COVID-19 severity (OR [95% CI] = 0.81 [0.71-0.92], p = 1.24 ×10-3) and suggestively associated with lower risks of COVID-19 susceptibility (OR [95% CI] = 0.96 [0.92-1.00], p = 3.44 ×10-2) and COVID-19 hospitalization (OR [95% CI] = 0.89 [0.80-0.98], p = 1.89 ×10-2). LTL partially mediated the effects of BMI, smoking, and education on COVID-19 outcomes. Furthermore, six proteins partially mediated the causality of LTL on COVID-19 outcomes, including BNDF, QPCT, FAS, MPO, SFTPB, and APOF.

Conclusions

Our findings suggested that shorter LTL was genetically associated with a higher risk of COVID-19 phenotypes, with shared genetic etiology and potential causality.

The formation of aggregated chromatin/chromosomes in mouse oocytes treated with high concentration of IBMX as a model for a chromosome transfer in human

The presence of cyclic adenosine monophosphate (cAMP) has been considered to be a fundamental factor in ensuring meiotic arrest prior to ovulation. cAMP is regarded as a key molecule in the regulation of oocyte maturation. However, it has been reported that increased levels of intracellular cAMP can result in abnormal cytokinesis, with some MI oocytes leading to symmetrically cleaved 2-cell MII oocytes. Consequently, we aimed to investigate the effects of elevated intracellular cAMP levels on abnormal cytokinesis and oocyte maturation during the meiosis of mouse oocytes. This study found that a high concentration of isobutylmethylxanthine (IBMX) also caused chromatin/chromosomes aggregation (AC) after the first meiosis. The rates of AC increased the greater the concentration of IBMX. In addition, AC formation was found to be reversible, showing that the re-formation of the spindle chromosome complex was possible after the IBMX was removed. In human oocytes, the chromosomes aggregate after the germinal vesicle breakdown and following the first and second polar body extrusions (the AC phase), while mouse oocytes do not have this AC phase. The results of our current study may indicate that the AC phase in human oocytes could be related to elevated levels of intracytoplasmic cAMP.

The implications for urological malignancies of non-coding RNAs in the the tumor microenvironment

Urological malignancies are a major global health issue because of their complexity and the wide range of ways they affect patients. There's a growing need for in-depth research into these cancers, especially at the molecular level. Recent studies have highlighted the importance of non-coding RNAs (ncRNAs) – these don't code for proteins but are crucial in controlling genes – and the tumor microenvironment (TME), which is no longer seen as just a background factor but as an active player in cancer progression. Understanding how ncRNAs and the TME interact is key for finding new ways to diagnose and predict outcomes in urological cancers, and for developing new treatments. This article reviews the basic features of ncRNAs and goes into detail about their various roles in the TME, focusing specifically on how different ncRNAs function and act in urological malignancies.

Circle-seq based method for eccDNA synthesis and its application as a canonical promoter independent vector for robust microRNA overexpression

Extrachromosomal circular DNA (eccDNA) has recently gained increasing attention due to its significant role in cancer and other pathophysiologic states. The majority of circular DNAs detected by Circle-seq are small-size eccDNAs with enigmatic functions. One major technical hurdle is to synthesize eccDNA for functional identification. Here, we describe CAES (Circle-seq based Artificial EccDNA Synthesis), a promising and reliable method for artificial eccDNA synthesis. Eight eccDNAs carrying different microRNA genes (eccMIR) found in gastric cancer tissues, ranging from 329 bp to 2189 bp in size, were created utilizing the CAES method. Exonuclease V and single restriction-endonuclease digestion identified the circular structure of synthetic eccDNAs. The DNA circularization efficiency afforded by CAES ranged from 15.6% to 31.1%, which was negatively correlated with the eccDNA length. In addition, we demonstrated that CAES-synthesized eccMIRs can express both miRNA-3p and - 5p molecules efficiently independent of a canonical promoter in human cell lines. Further assays proved that these eccMIRs were functional as they were able to repress the luciferase gene containing a miRNA-target sequence in the 3'UTR as well as the endogenous mRNA targets. Finally, kinetics study revealed that eccDNA exhibited a decay rate similar to the standard plasmids and linear DNA in cultured cells. Together, this study offers a rapid and convenient method for Circle-seq users to synthesize artificial eccDNAs. It also demonstrates the promising potential of eccMIR as a bacterial DNA-free vector for safe and robust miRNA overexpression in both basic research and therapeutic applications.

A gap analysis of UK biobank publications reveals SNPs associated with intrinsic subtypes of breast cancer

Breast cancer is a multifaceted disease and a leading cause of cancer morbidity and mortality in females across the globe. In 2020 alone, 2.3 million women were diagnosed and 685,000 died of breast cancer worldwide. With the number of diagnoses projected to increase to 3 million per year by 2040 it is essential that new methods of detection and disease stratification are sought to decrease this global cancer burden. Although significant improvements have been made in breast cancer diagnosis and treatment, the prognosis of breast cancer remains poor in some patient groups (i.e. triple negative breast cancer), necessitating research into better patient stratification, diagnosis and drug discovery. The UK Biobank, a comprehensive biomedical and epidemiological database with a wide variety of multiomics data (genomics, proteomics, metabolomics) offers huge potential to uncover groundbreaking discoveries in breast cancer research leading to improved patient stratification. Combining genomic, proteomic, and metabolic profiles of breast cancer in combination with histological classification, can aid treatment decisions through accurate diagnosis and prognosis prediction of tumor behaviour. Here, we systematically reviewed PubMed publications reporting the analysis of UK Biobank data in breast cancer research. Our analysis of UK Biobank studies in the past five years identified 125 publications, of which 76 focussed on genomic data analysis. Interestingly, only two studies reported the analysis of metabolomics and proteomics data, with none performing multiomics analysis of breast cancer. A meta-analysis of the 76 publications identified 2870 genetic variants associated with breast cancer across 445 genes. Subtype analysis revealed differential genetic alteration in 13 of the 445 genes and the identification of 59 well-established breast cancer genes. in differential pathways. Pathway interaction analyses illuminated their involvement in general cancer biomolecular pathways (e.g. DNA damage repair, Gene expression). While our meta-analysis only measured genetic differences in breast cancer due to current usage of UK Biobank data, minimal multi-omics analyses have been performed and the potential for harnessing multi-omics strategies within the UK Biobank cohort holds promise for unravelling the biological signatures of distinct breast cancer subtypes further in the future.

Beyond mutations: Accounting for quantitative changes in the analysis of protein evolution

Molecular phylogenetic research has relied on the analysis of the coding sequences by genes or of the amino acid sequences by the encoded proteins. Enumerating the numbers of mismatches, being indicators of mutation, has been central to pertinent algorithms. Specific amino acids possess quantifiable characteristics that enable the conversion from "words" (strings of letters denoting amino acids or bases) to "waves" (strings of quantitative values representing the physico-chemical properties) or to matrices (coordinates representing the positions in a comprehensive property space). The application of such numerical representations to evolutionary analysis takes into account not only the occurrence of mutations but also their properties as influences that drive speciation, because selective pressures favor certain mutations over others, and this predilection is represented in the characteristics of the incorporated amino acids (it is not born out solely by the mismatches). Besides being more discriminating sources for tree-generating algorithms than match/mismatch, the number strings can be examined for overall similarity with average mutual information, autocorrelation, and fractal dimension. Bivariate wavelet analysis aids in distinguishing hypermutable versus conserved domains of the protein. The matrix depiction is readily subjected to comparisons of distances, and it allows the generation of heat maps or graphs. This analysis preserves the accepted taxa order where tree construction with standard approaches yields conflicting results (for the protein S100A6). It also aids hypothesis generation about the origin of mitochondrial proteins. These analytical algorithms have been automated in R and are applicable to various processes that are describable in matrix format.

WGBS of embryonic gonads revealed that long non-coding RNAs in the MHM region might be involved in cell autonomous sex identity and female gonadal development in chickens

DNA methylation plays a key role in sex determination and differentiation in vertebrates. However, there are few studies on DNA methylation involved in chicken gonad development, and most focused on male hypermethylated regions (MHM). It is unclear whether there are specific differentially methylated regions (DMRs) in chicken embryonic gonads regulating sex determination and differentiation. Here, the DNA methylation maps showed that the difference of DNA methylation level between sexes was much higher at embryonic day 10 (E10) than that at embryonic day 6 (E6), and the significant differentially methylated regions at both stages were mainly distributed on the Z chromosome, including MHM1 and MHM2. The results of bisulphite sequencing PCR (BSP) and qRT-PCR showed hypomethylation of female MHM and upregulation of long non-coding RNAs (lncRNAs) whose promoter in the MHM region was consistent with the sequencing results, and similar results were in brain and muscle. In female sex-reversed gonads, the methylation pattern of MHM remained unchanged, and the expression levels of the three candidate lncRNAs were significantly decreased compared with those in females, but were significantly increased compared to males. The fluorescence in situ hybridization (FISH) results also showed that these lncRNAs were highly expressed in female embryonic gonads. The results of methyltransferase inhibitor and dual-luciferase reporter assay suggest that lncRNA expression may be regulated by DNA methylation within their promoters. Therefore, we speculated that MHM may be involved in cell-autonomous sex identity in chickens, and that lncRNAs regulated by MHM may be involved in female sexual differentiation.

Within-host genomic evolution of methicillin-resistant Staphylococcus aureus in long-term carriers

Assessing the genomic evolution of Staphylococcus aureus can help us understand how the bacteria adapt to its environment. In this study, we aimed to assess the mutation rate within 144 methicillin-resistant Staphylococcus aureus (MRSA) carriers with a carriage time from 4 to 11 years, including some carriers who belonged to the same households. We found that 23 of the 144 individuals had completely different MRSA types over time and were therefore not long-term carriers of the same MRSA. From the remaining 121 individuals, we performed whole-genome sequencing (WGS) on 424 isolates and then compared these pairwise using core genome multilocus sequence typing (cgMLST) and single-nucleotide polymorphism (SNP) analyses. We found a median within-host mutation rate in long-term MRSA carriers of 4.9 (3.4-6.9) SNPs/genome/year and 2.7 (1.8-4.2) allelic differences/genome/year, when excluding presumed recombination. Furthermore, we stratified the cohort into subgroups and found no significant difference between the median mutation rate of members of households, individuals with presumed continued exposure, e.g., from travel and persons without known continued exposure. Finally, we found that SNPs occurred at random within the genes in our cohort. KEY POINTS: • Median mutation rate within long-term MRSA carriers of 4.9 (3.4-6.9) SNPs/genome/year • Similar median mutation rates in subgroups (households, travelers) • No hotspots for SNPs within the genome.

Predicting antimicrobial resistance in E. coli with discriminative position fused deep learning classifier

Escherichia coli (E. coli) has become a particular concern due to the increasing incidence of antimicrobial resistance (AMR) observed worldwide. Using machine learning (ML) to predict E. coli AMR is a more efficient method than traditional laboratory testing. However, further improvement in the predictive performance of existing models remains challenging. In this study, we collected 1937 high-quality whole genome sequencing (WGS) data from public databases with an antimicrobial resistance phenotype and modified the existing workflow by adding an attention mechanism to enable the modified workflow to focus more on core single nucleotide polymorphisms (SNPs) that may significantly lead to the development of AMR in E. coli. While comparing the model performance before and after adding the attention mechanism, we also performed a cross-comparison among the published models using random forest (RF), support vector machine (SVM), logistic regression (LR), and convolutional neural network (CNN). Our study demonstrates that the discriminative positional colors of Chaos Game Representation (CGR) images can selectively influence and highlight genome regions without prior knowledge, enhancing prediction accuracy. Furthermore, we developed an online tool (https://github.com/tjiaa/E.coli-ML/tree/main) for assisting clinicians in the rapid prediction of the AMR phenotype of E. coli and accelerating clinical decision-making.

Study of the genomics and transcriptomics profiles of male-infertility genes in human prostate cancer: an in silico analysis

The World Health Organization has considered the infertility as an international public health problem. Infertility affect nearly 1 in 7 couples and male component contributes to 50% of infertility cases. There is a clear link between male infertility and some cancers such as testicular germ cell, prostate and colon cancers. Two possibilities support this finding: 1) Cancer treatments can affect the fertility factors 2) Genetic profile of infertility genes have been altered in cancer patients. Although the previously published researches have mostly focused on the first factor, no article has yet confirmed the role of genetic factors. In this in silico study, we collected the large number of genes (n = 17703) involved in infertility. These genes were collected from NGS panel tests of male infertility and comprehensive literature review or online data base. The Prostate Adenocarcinoma genomic and transcriptomics raw data were downloaded from the cBioPortal Cancer dataset. This included with 494 patients of Prostate Cancer with 494 mutation data, 489 with CNA and 493 with RNA seqV2 data. TCGA RNA-Seq raw data was extracted in R using the cgdsr extension package with a threshold of ±2 relative to normal samples. The observed data showed that male infertility genes have been distributed through the human genome. Among the 17703 analyzed genes of this study, the genomic profile of three genes including OR9Q1, H4C6 and PSG7 were changed approximately in 100% of (n = 493) patients. In most of patients (>98%), genetic alteration was related to change in gene expression. In conclusion, this study showed that the genomic and transcriptomics patterns of some male-infertility genes are notably altered in patients of prostate cancer and suggested a possible role of genetic factors in occurrence of infertility in cancer patients. Our information can be used as a source for the design of genetic database of male-infertility.

Efficient inference of parent-of-origin effect using case-control mother-child genotype data

Parent-of-origin effect plays an important role in mammal development and disorder. Case-control mother-child pair genotype data can be used to detect parent-of-origin effect and is often convenient to collect in practice. Most existing methods for assessing parent-of-origin effect do not incorporate any covariates, which may be required to control for confounding factors. We propose to model the parent-of-origin effect through a logistic regression model, with predictors including maternal and child genotypes, parental origins, and covariates. The parental origins may not be fully inferred from genotypes of a target genetic marker, so we propose to use genotypes of markers tightly linked to the target marker to increase inference efficiency. A robust statistical inference procedure is developed based on a modified profile log-likelihood in a retrospective way. A computationally feasible expectation-maximization algorithm is devised to estimate all unknown parameters involved in the modified profile log-likelihood. This algorithm differs from the conventional expectation-maximization algorithm in the sense that it is based on a modified instead of the original profile log-likelihood function. The convergence of the algorithm is established under some mild regularity conditions. This expectation-maximization algorithm also allows convenient handling of missing child genotypes. Large sample properties, including weak consistency, asymptotic normality, and asymptotic efficiency, are established for the proposed estimator under some mild regularity conditions. Finite sample properties are evaluated through extensive simulation studies and the application to a real dataset.

Integrating bulk RNA-seq and scRNA-seq analyses revealed the function and clinical value of thrombospondins in colon cancer

Background

Acting as mediators in cell-matrix and cell-cell communication, matricellular proteins play a crucial role in cancer progression. Thrombospondins (TSPs), a type of matricellular glycoproteins, are key regulators in cancer biology with multifaceted roles. Although TSPs have been implicated in anti-tumor immunity and epithelial-mesenchymal transition (EMT) in several malignancies, their specific roles to colon cancer remain elusive. Addressing this knowledge gap is essential, as understanding the function of TSPs in colon cancer could identify new therapeutic targets and prognostic markers.

Methods

Analyzing 1981 samples from 10 high-throughput datasets, including six bulk RNA-seq, three scRNA-seq, and one spatial transcriptome dataset, our study investigated the prognostic relevance, risk stratification value, immune heterogeneity, and cellular origin of TSPs, as well as their influence on cancer-associated fibroblasts (CAFs). Utilizing survival analysis, unsupervised clustering, and functional enrichment, along with multiple correlation analyses of the tumor-microenvironment (TME) via Gene Set Variation Analysis (GSVA), spatial localization, Monocle2, and CellPhoneDB, we provided insights into the clinical and cellular implications of TSPs.

Results

First, we observed significant upregulation of THBS2 and COMP in colon cancer, both of which displayed significant prognostic value. Additionally, we detected a significant positive correlation between TSPs and immune cells, as well as marker genes of EMT. Second, based on TSPs expression, patients were divided into two clusters with distinct prognoses: the high TSPs expression group (TSPs-H) was characterized by pronounced immune and stromal cell infiltration, and notably elevated T-cell exhaustion scores. Subsequently, we found that THBS2 and COMP may be associated with the differentiation of CAFs into pan-iCAFs and pan-dCAFs, which are known for their heightened matrix remodeling activities. Moreover, THBS2 enhanced CAFs communication with vascular endothelial cells and monocyte-macrophages. CAFs expressing THBS2 (THBS2+ CAFs) demonstrated higher scores across multiple signaling pathways, including angiogenic, EMT, Hedgehog, Notch, Wnt, and TGF-β, when compared to THBS2- CAFs. These observations suggest that THBS2 may be associated with stronger pro-carcinogenic activity in CAFs.

Conclusions

This study revealed the crucial role of TSPs and the significant correlation between THBS2 and CAFs interactions in colon cancer progression, providing valuable insights for targeting TSPs to mitigate cancer progression.

Sculpting nuclear envelope identity from the endoplasmic reticulum during the cell cycle

The nuclear envelope (NE) regulates nuclear functions, including transcription, nucleocytoplasmic transport, and protein quality control. While the outer membrane of the NE is directly continuous with the endoplasmic reticulum (ER), the NE has an overall distinct protein composition from the ER, which is crucial for its functions. During open mitosis in higher eukaryotes, the NE disassembles during mitotic entry and then reforms as a functional territory at the end of mitosis to reestablish nucleocytoplasmic compartmentalization. In this review, we examine the known mechanisms by which the functional NE reconstitutes from the mitotic ER in the continuous ER-NE endomembrane system during open mitosis. Furthermore, based on recent findings indicating that the NE possesses unique lipid metabolism and quality control mechanisms distinct from those of the ER, we explore the maintenance of NE identity and homeostasis during interphase. We also highlight the potential significance of membrane junctions between the ER and NE.

The sensor protein AaSho1 regulates infection structures differentiation, osmotic stress tolerance and virulence via MAPK module AaSte11-AaPbs2-AaHog1 in Alternaria alternata

The high-osmolarity-sensitive protein Sho1 functions as a key membrane receptor in phytopathogenic fungi, which can sense and respond to external stimuli or stresses, and synergistically regulate diverse fungal biological processes through cellular signaling pathways. In this study, we investigated the biological functions of AaSho1 in Alternaria alternata, the causal agent of pear black spot. Targeted gene deletion revealed that AaSho1 is essential for infection structure differentiation, response to external stresses and synthesis of secondary metabolites. Compared to the wild-type (WT), the ∆AaSho1 mutant strain showed no significant difference in colony growth, morphology, conidial production and biomass accumulation. However, the mutant strain exhibited significantly reduced levels of melanin production, cellulase (CL) and ploygalacturonase (PG) activities, virulence, resistance to various exogenous stresses. Moreover, the appressorium and infection hyphae formation rates of the ∆AaSho1 mutant strain were significantly inhibited. RNA-Seq results showed that there were four branches including pheromone, cell wall stress, high osmolarity and starvation in the Mitogen-activated Protein Kinase (MAPK) cascade pathway. Furthermore, yeast two-hybrid experiments showed that AaSho1 activates the MAPK pathway via AaSte11-AaPbs2-AaHog1. These results suggest that AaSho1 of A. alternata is essential for fungal development, pathogenesis and osmotic stress response by activating the MAPK cascade pathway via Sho1-Ste11-Pbs2-Hog1.

Context-dependent genomic locus effects on antibody production in recombinant Chinese hamster ovary cells generated through random integration

High-yield production of therapeutic protein using Chinese hamster ovary (CHO) cells requires stable cell line development (CLD). CLD typically uses random integration of transgenes; however, this results in clonal variation and subsequent laborious clone screening. Therefore, site-specific integration of a protein expression cassette into a desired chromosomal locus showing high transcriptional activity and stability, referred to as a hot spot, is emerging. Although positional effects are important for therapeutic protein expression, the sequence-specific mechanisms by which hotspots work are not well understood. In this study, we performed whole-genome sequencing (WGS) to locate randomly inserted vectors in the genome of recombinant CHO cells expressing high levels of monoclonal antibodies (mAbs) and experimentally validated these locations and vector compositions. The integration site was characterized by active histone marks and potential enhancer activities, and clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) mediated indel mutations in the region upstream of the integration site led to a significant reduction in specific antibody productivity by up to 30%. Notably, the integration site and its core region did not function equivalently outside the native genomic context, showing a minimal effect on the increase in exogenous protein expression in the host cell line. We also observed a superior production capacity of the mAb expressing cell line compared to that of the host cell line. Collectively, this study demonstrates that developing recombinant CHO cell lines to produce therapeutic proteins at high levels requires a balance of factors including transgene configuration, genomic locus landscape, and host cell properties.

Non-coding 886 (nc886/vtRNA2-1), the epigenetic odd duck - implications for future studies

Non-coding 886 (nc886, vtRNA2-1) is the only human polymorphically imprinted gene, in which the methylation status is not determined by genetics. Existing literature regarding the establishment, stability and consequences of the methylation pattern, as well as the nature and function of the nc886 RNAs transcribed from the locus, are contradictory. For example, the methylation status of the locus has been reported to be stable through life and across somatic tissues, but also susceptible to environmental effects. The nature of the produced nc886 RNA(s) has been redefined multiple times, and in carcinogenesis, these RNAs have been reported to have conflicting roles. In addition, due to the bimodal methylation pattern of the nc886 locus, traditional genome-wide methylation analyses can lead to false-positive results, especially in smaller datasets. Herein, we aim to summarize the existing literature regarding nc886, discuss how the characteristics of nc886 give rise to contradictory results, as well as to reinterpret, reanalyse and, where possible, replicate the results presented in the current literature. We also introduce novel findings on how the distribution of the nc886 methylation pattern is associated with the geographical origins of the population and describe the methylation changes in a large variety of human tumours. Through the example of this one peculiar genetic locus and RNA, we aim to highlight issues in the analysis of DNA methylation and non-coding RNAs in general and offer our suggestions for what should be taken into consideration in future analyses.

Optimal variable identification for accurate detection of causal expression Quantitative Trait Loci with applications in heart-related diseases

Gene expression plays a pivotal role in various diseases, contributing significantly to their mechanisms. Most GWAS risk loci are in non-coding regions, potentially affecting disease risk by altering gene expression in specific tissues. This expression is notably tissue-specific, with genetic variants substantially influencing it. However, accurately detecting the expression Quantitative Trait Loci (eQTL) is challenging due to limited heritability in gene expression, extensive linkage disequilibrium (LD), and multiple causal variants. The single variant association approach in eQTL analysis is limited by its susceptibility to capture the combined effects of multiple variants, and a bias towards common variants, underscoring the need for a more robust method to accurately identify causal eQTL variants. To address this, we developed an algorithm, CausalEQTL, which integrates L 0 +L 1 penalized regression with an ensemble approach to localize eQTL, thereby enhancing prediction performance precisely. Our results demonstrate that CausalEQTL outperforms traditional models, including LASSO, Elastic Net, Ridge, in terms of power and overall performance. Furthermore, analysis of heart tissue data from the GTEx project revealed that eQTL sites identified by our algorithm provide deeper insights into heart-related tissue eQTL detection. This advancement in eQTL mapping promises to improve our understanding of the genetic basis of tissue-specific gene expression and its implications in disease. The source code and identified causal eQTLs for CausalEQTL are available on GitHub: https://github.com/zhc-moushang/CausalEQTL.

Alteration of reactive oxygen species master transcription factor Nrf2 in keratinocytes exposed to monoclonal pathogenic antibody AK23 against desmoglein-3 in pemphigus vulgaris

Keratinocytes in mucosal and skin tissues maintain tissue integrity via desmosomes and desmoglein-3 (Dsg3). Pemphigus Vulgaris (PV) is a life-threatening autoimmune blistering disease characterized by autoantibodies against Dsg3, disrupting desmosomes. Nuclear factor erythroid 2-related factor 2 (Nrf2) regulates oxidative stress responses crucial for skin tissue protection. Although the pathogenesis of PV is known, the detailed molecular events remain unclear. This study investigates changes in Nrf2 expression in keratinocytes following pathogenic anti-Dsg3 antibody AK23 exposure, using dose- and time-dependent studies employing immunofluorescence analysis. N/TERT keratinocytes were cultured in keratinocytes serum-free medium and treated with AK23 at varying doses (5 µg/mL,40µg/mL,75µg/mL) and durations (2, 6, 24 h). Immunofluorescence staining was performed to assess the expression of Nrf2 and Dsg3. All fluorescent images were analyzed using ImageJ software. A dose-dependent increase in Dsg3 was noted following AK23 treatment, while Nrf2 expression and subcellular localization varied. Time-course analyses showed decreased Nrf2 at 24 h and increased Dsg3 levels. Early time-point (2 and 6 h) variations were evident in Nrf2 levels. This study highlights the impact of AK23 on Nrf2 expression, potentially disrupting Nrf2-mediated cytoprotection and implicating oxidative stress (ROS generation) in PV pathogenesis. Further investigation is necessary to validate the findings.

Animal and plant protein intake during infancy and childhood DNA methylation: a meta-analysis in the NutriPROGRAM consortium

BACKGROUND

Higher early-life animal protein intake is associated with a higher childhood obesity risk compared to plant protein intake. Differential DNA methylation may represent an underlying mechanism.

METHODS

We analysed associations of infant animal and plant protein intakes with DNA methylation in early (2-6 years, N = 579) and late (7̄-12 years, N = 604) childhood in two studies. Study-specific robust linear regression models adjusted for relevant confounders were run, and then meta-analysed using a fixed-effects model. We also performed sex-stratified meta-analyses. Follow-up analyses included pathway analysis and eQTM look-up.

RESULTS

Infant animal protein intake was not associated with DNA methylation in early childhood, but was associated with late-childhood DNA methylation at cg21300373 (P = 4.27 × 10¯8, MARCHF1) and cg10633363 (P = 1.09 × 10¯7, HOXB9) after FDR correction. Infant plant protein intake was associated with early-childhood DNA methylation at cg25973293 (P = 2.26 × 10-7, C1orf159) and cg15407373 (P = 2.13 × 10-7, MBP) after FDR correction. There was no overlap between the findings from the animal and plant protein analyses. We did not find enriched functional pathways at either time point using CpGs associated with animal and plant protein. These CpGs were not previously associated with childhood gene expression. Sex-stratified meta-analyses showed sex-specific DNA methylation associations for both animal and plant protein intake.

CONCLUSION

Infant animal protein intake was associated with DNA methylation at two CpGs in late childhood. Infant plant protein intake was associated with DNA methylation in early childhood at two CpGs. A potential mediating role of DNA methylation at these CpGs between infant protein intake and health outcomes requires further investigation.

The role of NLRP3 inflammasome in type 2 inflammation related diseases

Type 2 inflammation related diseases, such as atopic dermatitis, asthma, and allergic rhinitis, are diverse and affect multiple systems in the human body. It is common for individuals to have multiple co-existing type 2 inflammation related diseases, which can impose a significant financial and living burden on patients. However, the exact pathogenesis of these diseases is still unclear. The NLRP3 inflammasome is a protein complex composed of the NLRP3 protein, ASC, and Caspase-1, and is activated through various mechanisms, including the NF-κB pathway, ion channels, and lysosomal damage. The NLRP3 inflammasome plays a role in the immune response to pathogens and cellular damage. Recent studies have indicated a strong correlation between the abnormal activation of NLRP3 inflammasome and the onset of type 2 inflammation. Additionally, it has been demonstrated that suppressing NLRP3 expression effectively diminishes the inflammatory response, highlighting its promising therapeutic applications. Therefore, this article reviews the role of NLRP3 inflammasome in the development and therapy of multiple type 2 inflammation related diseases.

GLP1R boosts survival, migration and invasion of endometrial cancer cells and protects against ferroptotic cell death

BACKGROUND

Despite the strong evidence concerning carcinogenic roles of glucagon-like peptide 1 receptor (GLP1R), the role of this gene in endometrial cancer (EC) remains elusive. This study investigated the properties of GLP1R on EC in vitro.

METHODS

The expression of GLP1R in EC was detected by RT-qPCR, immunohistochemistry, and western blotting. Cell viability, cell cycle, apoptosis, migration, invasion and ferroptosis were assessed through CCK-8, flow cytometry, wound healing, transwell, DCFH-DA and western blotting, respectively.

RESULTS

We found that GLP1R was up-regulated in EC than normal specimens. It had the highest expression in AN3CA cells. Cell viability, migration and invasion were significantly reduced, while cell cycle arrest and apoptosis were induced following GLP1R knockdown. The malignant biological behaviours of AN3CA cells were investigated when treated with exendin-4 (GLP1R agonist). Moreover, GLP1R lowered intracellular ROS level and expression of SLC7A11, and FTH1, but mitigated GPX4 expression in AN3CA cells.

CONCLUSION

In a word, GLP1R was up-regulated in EC and its up-regulation facilitated the proliferative and metastatic potentials, and protected cells from ferroptosis, thereby accelerating EC progression. These data emphasised the potency of GLP1R as a therapeutic agent against EC.

The genome in space and time comes of age

DNA sequencing is not enough to grasp the complexity of genome organization and function. The four-dimensional (three in space, one in time) configuration of the eukaryotic nucleus varies with cell types, during development and in diseased tissues, and has to be taken into account to decipher genome function. To study, discuss, and advance in such direction, the International Nucleome Consortium COST Action, funded by the European Union, held its concluding symposium 'The Genome in Space and Time' at the Ionian University in Corfu, Greece, on September 10-13, 2023.

Using methylation data to improve transcription factor binding prediction

Modelling the regulatory mechanisms that determine cell fate, response to external perturbation, and disease state depends on measuring many factors, a task made more difficult by the plasticity of the epigenome. Scanning the genome for the sequence patterns defined by Position Weight Matrices (PWM) can be used to estimate transcription factor (TF) binding locations. However, this approach does not incorporate information regarding the epigenetic context necessary for TF binding. CpG methylation is an epigenetic mark influenced by environmental factors that is commonly assayed in human cohort studies. We developed a framework to score inferred TF binding locations using methylation data. We intersected motif locations identified using PWMs with methylation information captured in both whole-genome bisulfite sequencing and Illumina EPIC array data for six cell lines, scored motif locations based on these data, and compared with experimental data characterizing TF binding (ChIP-seq). We found that for most TFs, binding prediction improves using methylation-based scoring compared to standard PWM-scores. We also illustrate that our approach can be generalized to infer TF binding when methylation information is only proximally available, i.e. measured for nearby CpGs that do not directly overlap with a motif location. Overall, our approach provides a framework for inferring context-specific TF binding using methylation data. Importantly, the availability of DNA methylation data in existing patient populations provides an opportunity to use our approach to understand the impact of methylation on gene regulatory processes in the context of human disease.

scQA: A dual-perspective cell type identification model for single cell transcriptome data

Single-cell RNA sequencing technologies have been pivotal in advancing the development of algorithms for clustering heterogeneous cell populations. Existing methods for utilizing scRNA-seq data to identify cell types tend to neglect the beneficial impact of dropout events and perform clustering focusing solely on quantitative perspective. Here, we introduce a novel method named scQA, notable for its ability to concurrently identify cell types and cell type-specific key genes from both qualitative and quantitative perspectives. In contrast to other methods, scQA not only identifies cell types but also extracts key genes associated with these cell types, enabling bidirectional clustering for scRNA-seq data. Through an iterative process, our approach aims to minimize the number of landmarks to approximately a dozen while maximizing the inclusion of quasi-trend-preserved genes with dropouts both qualitatively and quantitatively. It then clusters cells by employing an ingenious label propagation strategy, obviating the requirement for a predetermined number of cell types. Validated on 20 publicly available scRNA-seq datasets, scQA consistently outperforms other salient tools. Furthermore, we confirm the effectiveness and potential biological significance of the identified key genes through both external and internal validation. In conclusion, scQA emerges as a valuable tool for investigating cell heterogeneity due to its distinctive fusion of qualitative and quantitative facets, along with bidirectional clustering capabilities. Furthermore, it can be seamlessly integrated into border scRNA-seq analyses. The source codes are publicly available at https://github.com/LD-Lyndee/scQA.

Identification of common and specific fibrosis-related genes in three common chronic kidney diseases

BACKGROUND

Kidney fibrosis is the common final pathway of virtually all advanced forms of chronic kidney disease (CKD) including diabetic nephropathy (DN), IgA nephropathy (IgAN) and membranous nephropathy (MN), with complex mechanism. Comparative gene expression analysis among these types of CKD may shed light on its pathogenesis. Therefore, we conducted this study aiming at exploring the common and specific fibrosis-related genes involved in different types of CKD.

METHODS

Kidney biopsy specimens from patients with different types of CKD and normal control subjects were analyzed using the NanoString nCounter® Human Fibrosis V2 Panel. Genes differentially expressed in all fibrotic DN, IgAN and MN tissues compared to the normal controls were regarded as the common fibrosis-related genes in CKD, whereas genes exclusively differentially expressed in fibrotic DN, IgAN or MN samples were considered to be the specific genes related to fibrosis in DN, IgAN and MN respectively. Quantitative real-time PCR (qRT-PCR) was performed to validate the expression of the selected genes.

RESULTS

Protein tyrosine phosphatase receptor type C (PTPRC), intercellular cell adhesion molecule-1 (ICAM1), vascular cell adhesion molecule-1 (VCAM1), interleukin 10 receptor alpha (IL10RA) and CC chemokine receptor 2 (CCR2) were identified as the potential common genes for kidney fibrosis in different types of CKD, while peroxisome proliferator-activated receptor alpha (PPARA), lactate oxidase (LOX), secreted phosphoprotein 1 (SPP1) were identified as the specific fibrosis-associated genes for DN, IgAN and MN respectively. qRT-PCR demonstrated that the expression levels of these selected genes were consistent with the NanoString analysis.

CONCLUSIONS

There were both commonalities and differences in the mechanisms of fibrosis in different types of CKD, the commonalities might be used as the common therapeutic targets for kidney fibrosis in CKD, while the differences might be used as the diagnostic markers for DN, IgAN and MN respectively. Inflammation was highly relevant to the pathogenesis of fibrosis. This study provides further insight into the pathophysiology and treatment of fibrotic kidney disease.

Association between circulating unsaturated fatty acid and preeclampsia: a two-sample Mendelian randomization study

OBJECTIVE

In recent years, several studies have reported an association between unsaturated fatty acids (UFAs) and the risk of developing preeclampsia; however, its exact causal effect is unclear. This study assessed the causal association between circulating UFAs and preeclampsia.

METHODS

A two-sample Mendelian randomization (MR) study using publicly available genome-wide association study (GWAS) summary data for circulating UFA s (N = 114,999) and preeclampsia (N = 118,291) was performed. Single nucleotide polymorphisms (SNPs) significantly associated with exposure was selected as instrumental variables (IVs). The inverse variance weighted (IVW) test was used as the primary method for estimating causality in MR analysis, while MR pleiotropy residual sum and outlier (MR-PRESSO) and MR-Egger regression methods were used to assess horizontal pleiotropy. Cochran's Q test was used to evaluate heterogeneity among SNPs, and leave-one-out sensitivity analysis was used to determine the effect of individual SNPs on the results of the MR analysis. Bonferroni correction was used as a correction for multiple corrections.

RESULTS

Two-sample MR analysis suggested that the ratio of monounsaturated fatty acids (MUFAs) to total fatty acids (OR 1.150, 95% CI 1.006-1.315, p = 0.041), the ratio of polyunsaturated fatty acids (PUFAs) to total fatty acids (OR 0.805, 95% CI 0.658-0.986, p = 0.036) and the ratio of PUFAs to MUFAs (OR 0.807, 95% CI 0.694-0.938, p = 0.005) were causally associated with preeclampsia. After Bonferroni correction, the causal association between the ratio of polyunsaturated to MUFAs and preeclampsia remained statistically different.

CONCLUSIONS

This MR analysis provides evidence for a genetic causal association between circulating UFAs and preeclampsia.

Causal relationship between affect disorders and endometrial cancer: a Mendelian randomisation study

BACKGROUND

The aim was to assess the causal relationship between depression and anxiety disorders and endometrial cancer.

METHOD

We performed two-sample Mendelian randomisation analysis using summary statistics from genome-wide association studies to assess associations of major depressive disorder, anxiety and stress-related disorders with endometrial cancer. The genome-wide association studies(GWASs) data were derived from participants of predominantly European ancestry included in the Genome-wide Association Research Collaboration. Inverse variance-weighted, MR-Egger and weighted median MR analyses were performed, together with a range of sensitivity analyses.

RESULTS

Mendelian randomisation analysis showed no statistically significant genetic responsibility effect of anxiety and stress-related disorders on any pathological type of endometrial cancer. Only the effect of major depressive disorder under the inverse variance weighting method increasing the risk of endometrial endometrial cancer (effect 0.004 p = 0.047) and the effect of major depressive disorder under the MR-Egger method decreasing endometrial cancer of all pathology types (effect -0.691 p = 0.015) were statistically significant. Other Mendelian randomisation analyses did not show a statistically significant effect.

CONCLUSION

Major depressive disorder(MDD), anxiety and stress-related disorders(ASRD) are not genetically responsible for endometrial cancer. We consider that emotional disorders may affect endometrial cancer indirectly by affecting body mass index. This study provides us with new insights to better understand the aetiology of endometrial cancer and inform prevention strategies.

Critical evaluation of the reliability of DNA methylation probes on the Illumina MethylationEPIC v1.0 BeadChip microarrays

DNA methylation (DNAm) plays a crucial role in a number of complex diseases. However, the reliability of DNAm levels measured using Illumina arrays varies across different probes. Previous research primarily assessed probe reliability by comparing duplicate samples between the 450k-450k or 450k-EPIC platforms, with limited investigations on Illumina EPIC v1.0 arrays. We conducted a comprehensive assessment of the EPIC v1.0 array probe reliability using 69 blood DNA samples, each measured twice, generated by the Alzheimer's Disease Neuroimaging Initiative study. We observed higher reliability in probes with average methylation beta values of 0.2 to 0.8, and lower reliability in type I probes or those within the promoter and CpG island regions. Importantly, we found that probe reliability has significant implications in the analyses of Epigenome-wide Association Studies (EWAS). Higher reliability is associated with more consistent effect sizes in different studies, the identification of differentially methylated regions (DMRs) and methylation quantitative trait locus (mQTLs), and significant correlations with downstream gene expression. Moreover, blood DNAm measurements obtained from probes with higher reliability are more likely to show concordance with brain DNAm measurements. Our findings, which provide crucial reliability information for probes on the EPIC v1.0 array, will serve as a valuable resource for future DNAm studies.

Study on chromatin regulation patterns of expression vectors in the PhiC31 integration site

The PhiC31 integration system allows for targeted and efficient transgene integration and expression by recognizing pseudo attP sites in mammalian cells and integrating the exogenous genes into the open chromatin regions of active chromatin. In order to investigate the regulatory patterns of efficient gene expression in the open chromatin region of PhiC31 integration, this study utilized Ubiquitous Chromatin Opening Element (UCOE) and activating RNA (saRNA) to modulate the chromatin structure in the promoter region of the PhiC31 integration vector. The study analysed the effects of DNA methylation and nucleosome occupancy changes in the integrated promoter on gene expression levels. The results showed that for the OCT4 promoter with moderate CG density, DNA methylation had a smaller impact on expression compared to changes in nucleosome positioning near the transcription start site, which was crucial for enhancing downstream gene expression. On the other hand, for the SOX2 promoter with high CG density, increased methylation in the CpG island upstream of the transcription start site played a key role in affecting high expression, but the positioning and clustering of nucleosomes also had an important influence. In conclusion, analysing the DNA methylation patterns, nucleosome positioning, and quantity distribution of different promoters can determine whether the PhiC31 integration site possesses the potential to further enhance expression or overcome transgene silencing effects by utilizing chromatin regulatory elements.

Running the gauntlet: challenges to genome integrity in spermiogenesis

Species' continuity depends on gametogenesis to produce the only cell types that can transmit genetic information across generations. Spermiogenesis, which encompasses post-meiotic, haploid stages of male gametogenesis, is a process that leads to the formation of sperm cells well-known for their motility. Spermiogenesis faces three major challenges. First, after two rounds of meiotic divisions, the genome lacks repair templates (no sister chromatids, no homologous chromosomes), making it incredibly vulnerable to any genomic insults over an extended time (typically days-weeks). Second, the sperm genome becomes transcriptionally silent, making it difficult to respond to new perturbations as spermiogenesis progresses. Third, the histone-to-protamine transition, which is essential to package the sperm genome, counterintuitively involves DNA break formation. How spermiogenesis handles these challenges remains poorly understood. In this review, we discuss each challenge and their intersection with the biology of protamines. Finally, we discuss the implication of protamines in the process of evolution.

GETdb: A comprehensive database for genetic and evolutionary features of drug targets

The development of an innovative drug is complex and time-consuming, and the drug target identification is one of the critical steps in drug discovery process. Effective and accurate identification of drug targets can accelerate the drug development process. According to previous research, evolutionary and genetic information of genes has been found to facilitate the identification of approved drug targets. In addition, allosteric proteins have great potential as targets due to their structural diversity. However, this information that could facilitate target identification has not been collated in existing drug target databases. Here, we construct a comprehensive drug target database named Genetic and Evolutionary features of drug Targets database (GETdb, http://zhanglab.hzau.edu.cn/GETdb/page/index.jsp). This database not only integrates and standardizes data from dozens of commonly used drug and target databases, but also innovatively includes the genetic and evolutionary information of targets. Moreover, this database features an effective allosteric protein prediction model. GETdb contains approximately 4000 targets and over 29,000 drugs, and is a user-friendly database for searching, browsing and downloading data to facilitate the development of novel targets.

The transcription factor HMGB2 indirectly regulates APRIL expression and Gd-IgA1 production in patients with IgA nephropathy

BACKGROUND

IgA nephropathy (IgAN) is the most common primary glomerulonephritis worldwide. Proliferation-inducing ligand (APRIL) was identified as an important cause of glycosylation deficiency of IgA1 (Gd-IgA1), which can 'trigger' IgAN. Our previous study indicated that high migration group protein B2 (HMGB2) in peripheral blood mononuclear cells from patients with IgAN was associated with disease severity, but the underlying mechanism remains unclear.

MATERIALS AND METHODS

The location of HMGB2 was identified by immunofluorescence. qRT-PCR and Western blotting were used to measure HMGB2, HMGA1, and APRIL expression. Gd-IgA1 levels were detected by enzyme-linked immunosorbent assay (ELISA). In addition, we used DNA pull-down, protein profiling, and transcription factor prediction software to identify proteins bound to the promoter region of the APRIL gene. RNA interference and coimmunoprecipitation (Co-IP) were used to verify the relationships among HMGB2, high mobility group AT-hook protein 1 (HMGA1), and APRIL.

RESULTS

HMGB2 expression was greater in IgAN patients than in HCs and was positively associated with APRIL expression in B cells. DNA pull-down and protein profiling revealed that HMGB2 and HMGA1 bound to the promoter region of the APRIL gene. The expression levels of HMGA1, APRIL, and Gd-IgA1 were downregulated after HMGB2 knockdown. Co-IP indicated that HMGB2 binds to HMGA1. The Gd-IgA1 concentration in the supernatant was reduced after HMGA1 knockdown. HMGA1 binding sites were predicted in the promoter region of the APRIL gene.

CONCLUSION

HMGB2 expression is greater in IgAN patients than in healthy controls; it promotes APRIL expression by interacting with HMGA1, thereby inducing Gd-IgA1 overexpression and leading to IgAN.

Recent advances in the application of Mendelian randomization to chronic kidney disease

OBJECTIVE

Chronic kidney disease (CKD) is a condition influenced by both genetic and environmental factors and has been a focus of extensive research. Utilizing Mendelian randomization, researchers have begun to untangle the complex causal relationships underlying CKD. This review delves into the advances and challenges in the application of MR in the field of nephrology, shifting from a mere summary of its principles and limitations to a more nuanced exploration of its contributions to our understanding of CKD.

METHODS

Key findings from recent studies have been pivotal in reshaping our comprehension of CKD. Notably, evidence indicates that elevated testosterone levels may impair renal function, while higher sex hormone-binding globulin (SHBG) levels appear to be protective, predominantly in men. Surprisingly, variations in plasma glucose and glycated hemoglobin levels seem unaffected by genetically induced changes in the estimated glomerular filtration rate (eGFR), suggesting an independent pathway for renal function impairment.

RESULTS

Furthermore, lifestyle factors such as physical activity and socioeconomic status emerge as significant influencers of CKD risk and kidney health. The relationship between sleep duration and CKD is nuanced; short sleep duration is linked to increased risk, while long sleep duration does not exhibit a clear causal effect. Additionally, lifestyle factors, including diet, exercise, and mental wellness activities, play a crucial role in kidney health. New insights also reveal a substantial causal connection between both central and general obesity and CKD onset, while no significant links were found between genetically modified LDL cholesterol or triglyceride levels and kidney function.

CONCLUSION

This review not only presents the recent achievements of MR in CKD research but also illuminates the path forwards, underscoring critical unanswered questions and proposing future research directions in this dynamic field.

Elucidating the role of MICAL1 in pan-cancer using integrated bioinformatics and experimental approaches

Molecule interacting with CasL 1 (MICAL1) is a crucial protein involved in cell motility, axon guidance, cytoskeletal dynamics, and gene transcription. This pan-cancer study analyzed MICAL1 across 33 cancer types using bioinformatics and experiments. Dysregulated expression, diagnostic potential, and prognostic value were assessed. Associations with tumor characteristics, immune factors, and drug sensitivity were explored. Enrichment analysis revealed MICAL1's involvement in metastasis, angiogenesis, metabolism, and immune pathways. Functional experiments demonstrated its impact on renal carcinoma cells. These findings position MICAL1 as a potential biomarker and therapeutic target in specific cancers, warranting further investigation into its role in cancer pathogenesis.

Benchmarking feature selection and feature extraction methods to improve the performances of machine-learning algorithms for patient classification using metabolomics biomedical data

Objective

Classification tasks are an open challenge in the field of biomedicine. While several machine-learning techniques exist to accomplish this objective, several peculiarities associated with biomedical data, especially when it comes to omics measurements, prevent their use or good performance achievements. Omics approaches aim to understand a complex biological system through systematic analysis of its content at the molecular level. On the other hand, omics data are heterogeneous, sparse and affected by the classical "curse of dimensionality" problem, i.e. having much fewer observation, samples (n) than omics features (p). Furthermore, a major problem with multi-omics data is the imbalance either at the class or feature level. The objective of this work is to study whether feature extraction and/or feature selection techniques can improve the performances of classification machine-learning algorithms on omics measurements.

Methods

Among all omics, metabolomics has emerged as a powerful tool in cancer research, facilitating a deeper understanding of the complex metabolic landscape associated with tumorigenesis and tumor progression. Thus, we selected three publicly available metabolomics datasets, and we applied several feature extraction techniques both linear and non-linear, coupled or not with feature selection methods, and evaluated the performances regarding patient classification in the different configurations for the three datasets.

Results

We provide general workflow and guidelines on when to use those techniques depending on the characteristics of the data available. To further test the extension of our approach to other omics data, we have included a transcriptomics and a proteomics data. Overall, for all datasets, we showed that applying supervised feature selection improves the performances of feature extraction methods for classification purposes. Scripts used to perform all analyses are available at: https://github.com/Plant-Net/Metabolomic_project/.

In silico and in vivo analysis reveal impact of c-Myc tag in FMC63 scFv-CD19 protein interface and CAR-T cell efficacy

Anti-CD19 CAR-T cell therapy represents a breakthrough in the treatment of B-cell malignancies, and it is expected that this therapy modality will soon cover a range of solid tumors as well. Therefore, a universal cheap and sensitive method to detect CAR expression is of foremost importance. One possibility is the use of epitope tags such as c-Myc, HA or FLAG tags attached to the CAR extracellular domain, however, it is important to determine whether these tags can influence binding of the CAR with its target molecule. Here, we conducted in-silico structural modelling of an FMC63-based anti-CD19 single-chain variable fragment (scFv) with and without a c-Myc peptide tag added to the N-terminus portion and performed molecular dynamics simulation of the scFv with the CD19 target. We show that the c-Myc tag presence in the N-terminus portion does not affect the scFv's structural equilibrium and grants more stability to the scFv. However, intermolecular interaction potential (IIP) analysis reveals that the tag can approximate the complementarity-determining regions (CDRs) present in the scFv and cause steric impediment, potentially disturbing interaction with the CD19 protein. We then tested this possibility with CAR-T cells generated from human donors in a Nalm-6 leukemia model, showing that CAR-T cells with the c-Myc tag have overall worse antitumor activity, which was also observed when the tag was added to the C-terminus position. Ultimately, our results suggest that tag addition is an important aspect of CAR design and can influence CAR-T cell function, therefore its use should be carefully considered.

"Outlaw" mutations in quasispecies of SARS-CoV-2 inhibit replication

The evolution of SARS-CoV-2, the agent of COVID-19, has been remarkable for its high mutation potential, leading to the appearance of variants. Some mutations have never appeared in the published genomes, which represent consensus, or bona fide genomes. Here we tested the hypothesis that mutations that did not appear in consensus genomes were, in fact, as frequent as the mutations that appeared during the various epidemic episodes, but were not expressed because lethal. To identify these mutations, we analysed the genomes of 90 nasopharyngeal samples and the quasispecies determined by next-generation sequencing. Mutations observed in the quasispecies and not in the consensus genomes were considered to be lethal, what we called "outlaw" mutations. Among these mutations, we analysed the 21 most frequent. Eight of these "outlaws" were in the RNA polymerase and we were able to use a structural biology model and molecular dynamics simulations to demonstrate the functional incapacity of these mutated RNA polymerases. Three other mutations affected the spike, a major protein involved in the pathogenesis of COVID-19. Overall, by analysing the SARS-CoV-2 quasispecies obtained during sequencing, this method made it possible to identify "outlaws," showing areas that could potentially become the target of treatments.

PNPLA3 I148 M genetic variant in autoimmune hepatitis characterises advanced disease at diagnosis and reduced survival free of cirrhotic events and liver-related mortality

Background

Autoimmune hepatitis (AIH) is a relatively rare autoimmune disease with a strong genetic background. The patatin-like phospholipase domain-containing protein 3 (PNPLA3) I148 M (rs738409 C/G) variant has been associated with hepatic inflammation and fibrosis in chronic hepatic diseases beyond metabolic dysfunction-associated steatotic liver disease (MASLD).

Aim

Our aim was to investigate the significance of PNPLA3 I148 M variant in AIH.

Method

Two hundred AIH patients, followed in our centre, were evaluated while 100 healthy subjects served as controls. Genotyping was performed with allelic discrimination end-point polymerase chain reaction (PCR).

Results

The I148 M variant was present in 95/200 (47.5 %) AIH patients compared to 47/100 (47 %) healthy controls (p = 1.000). Patients with GG/CG genotypes were more likely to present with decompensated cirrhosis at diagnosis (GG/CG 6.3 % vs. CC 1 %, p = 0.039). Comorbidity with cardiometabolic risk factors and concurrence of MASLD was similar across genotypes. Simple steatosis was present in 37/186 (19.9 %) and steatohepatitis in 14/186 (7.5 %) patients with available liver biopsy without correlation with PNPLA3 genotype. Fibrosis stage and grade of inflammation were not correlated with any genotype. Response to treatment was also independent of the presence of the I148 M variant, even though a longer time was needed to achieve complete biochemical response in those carrying the GG/CG genotypes (p = 0.07). On Kaplan Meier analysis homozygosity for the G allele corelated with reduced survival free of decompensation (p = 0.006), cirrhotic events (decompensation, liver transplantation, hepatocellular carcinoma; p = 0.001) and liver-related death or liver transplantation (p = 0.011) in treated patients.

Conclusions

The PNPLA3 I148 M variant in AIH patients is associated with increased risk of advanced disease at diagnosis and reduced survival free of cirrhotic events and liver-related death or liver transplantation, regardless of the presence of MASLD. This signifies a potential role for the PNPLA3 I148 M variant as a new AIH biomarker allowing to identify patients at increased risk of disease progression.

From molecular mechanisms of prostate cancer to translational applications: based on multi-omics fusion analysis and intelligent medicine

Prostate cancer is the most common cancer in men worldwide and has a high mortality rate. The complex and heterogeneous development of prostate cancer has become a core obstacle in the treatment of prostate cancer. Simultaneously, the issues of overtreatment in early-stage diagnosis, oligometastasis and dormant tumor recognition, as well as personalized drug utilization, are also specific concerns that require attention in the clinical management of prostate cancer. Some typical genetic mutations have been proved to be associated with prostate cancer's initiation and progression. However, single-omic studies usually are not able to explain the causal relationship between molecular alterations and clinical phenotypes. Exploration from a systems genetics perspective is also lacking in this field, that is, the impact of gene network, the environmental factors, and even lifestyle behaviors on disease progression. At the meantime, current trend emphasizes the utilization of artificial intelligence (AI) and machine learning techniques to process extensive multidimensional data, including multi-omics. These technologies unveil the potential patterns, correlations, and insights related to diseases, thereby aiding the interpretable clinical decision making and applications, namely intelligent medicine. Therefore, there is a pressing need to integrate multidimensional data for identification of molecular subtypes, prediction of cancer progression and aggressiveness, along with perosonalized treatment performing. In this review, we systematically elaborated the landscape from molecular mechanism discovery of prostate cancer to clinical translational applications. We discussed the molecular profiles and clinical manifestations of prostate cancer heterogeneity, the identification of different states of prostate cancer, as well as corresponding precision medicine practices. Taking multi-omics fusion, systems genetics, and intelligence medicine as the main perspectives, the current research results and knowledge-driven research path of prostate cancer were summarized.

Interplay between JAK/STAT pathway and non-coding RNAs in different cancers

Progress in the identification of core multi-protein modules within JAK/STAT pathway has enabled researchers to develop a better understanding of the linchpin role of deregulated signaling cascade in carcinogenesis and metastasis. More excitingly, complex interplay between JAK/STAT pathway and non-coding RNAs has been shown to reprogramme the outcome of signaling cascade and modulate immunological responses within tumor microenvironment. Wealth of information has comprehensively illustrated that most of this complexity regulates the re-shaping of the immunological responses. Increasingly sophisticated mechanistic insights have illuminated fundamental role of STAT-signaling in polarization of macrophages to M2 phenotype that promotes disease aggressiveness. Overall, JAK/STAT signaling drives different stages of cancer ranging from cancer metastasis to the reshaping of the tumor microenvironment. JAK/STAT signaling has also been found to play role in the regulation of infiltration and activity of natural killer cells and CD4/CD8 cells by PD-L1/PD-1 signaling. In this review, we have attempted to set spotlight on regulation of JAK/STAT pathway by microRNAs, long non-coding RNAs and circular RNAs in primary tumors and metastasizing tumors. Therefore, existing knowledge gaps need to be addressed to propel this fledgling field of research to the forefront and bring lncRNAs and circRNAs to the frontline of clinical practice. Leveraging the growing momentum will enable interdisciplinary researchers to gain transition from segmented view to a fairly detailed conceptual continuum.

Identification the role of necroptosis in rheumatoid arthritis by WGCNA network

Rheumatoid arthritis (RA) is the predominant manifestation of inflammatory arthritis, distinguished by an increasing burden of morbidity and mortality. The intricate interplay of genes and signalling pathways involved in synovial inflammation in patients with RA remains inadequately comprehended. This study aimed to ascertain the role of necroptosis in RA, as along with their associations with immune cell infiltration. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were employed to identify central genes for RA. In this study, identified total of 28 differentially expressed genes (DEGs) were identified in RA. Utilising WGCNA, two co-expression modules were generated, with one module demonstrating the strongest correlation with RA. Through the integration of differential gene expression analysis, a total of 5 intersecting genes were discovered. These 5 hub genes, namely fused in sarcoma (FUS), transformer 2 beta homolog (TRA2B), eukaryotic translation elongation factor 2 (EEF2), cleavage and polyadenylation specific factor 6 (CPSF6) and signal transducer and activator of transcription 3 (STAT3) were found to possess significant diagnostic value as determined by receiver operating characteristic (ROC) curve analysis. The close association between the concentrations of various immune cells is anticipated to contribute to the diagnosis and treatment of RA. Furthermore, the infiltration of immune cells mentioned earlier is likely to exert a substantial influence on the initiation of this disease.

TET1 inhibits the migration and invasion of cervical cancer cells by regulating autophagy

Methylation modifications play pertinent roles in regulating gene expression and various biological processes. The silencing of the demethylase enzyme TET1 can affect the expressions of key oncogenes or tumour suppressor genes, thus contributing to tumour formation. Nonetheless, how TET1 affects the progression of cervical cancer is yet to be elucidated. In this study, we found that the expression of TET1 was significantly downregulated in cervical cancer tissues. Functionally, TET1 knockdown in cervical cancer cells can promote cell proliferation, migration, invasion, cervical xenograft tumour formation and EMT. On the contrary, its overexpression can reverse the aforementioned processes. Moreover, the autophagy level of cervical cancer cells can be enhanced after TET1 knockdown. Mechanistically, methylated DNA immunoprecipitation (MeDIP)-sequencing and MeDIP quantitative real-time PCR revealed that TET1 mediates the methylation of autophagy promoter regions. These findings suggest that TET1 affects the autophagy of cervical cancer cells by altering the methylation levels of NKRF or HIST1H2AK, but the specific mechanism needs to be investigated further.

Nomogram models predicting prognosis for patients with t(8;21) acute myeloid leukemia: a SEER-based study

BACKGROUND

Acute myeloid leukemia (AML) with t(8;21) manifests as a diverse hematological malignancy. Although it was categorized into a favorable subtype, 30-40% of patients experience relapse. The objective of this research was to devise a nomogram for the accurate anticipation of both overall survival (OS) and cancer-specific survival (CSS) in t(8;21) AML.

METHODS

From the Surveillance, Epidemiology, and End Results (SEER) database, individuals diagnosed with t(8;21) AML from 2000 to 2018 were selected. Prognostic factors for t(8;21) AML were identified using Cox regression analysis and Akaike Information Criterion (AIC), forming the basis for constructing prognostic nomograms.

RESULTS

Key variables, including first primary tumor, age group, race, and chemotherapy, were identified and integrated into the nomogram. The C-index values for the nomograms predicting OS and CSS were 0.753 (validation: 0.765) and 0.764 (validation: 0.757), respectively. Ultimately, based on nomogram scores, patients were stratified into high-risk and low-risk groups, revealing significant disparities in both OS and CSS between these groups (P < 0.001).

CONCLUSION

This study innovatively crafted nomograms, incorporating clinical and therapeutic variables, to forecast the 1-, 3-, and 5-year survival rates for individuals with t(8;21) AML.

Resource: A curated database of brain-related functional gene sets (Brain.GMT)

Transcriptional profiling has become a common tool for investigating the nervous system. During analysis, differential expression results are often compared to functional ontology databases, which contain curated gene sets representing well-studied pathways. This dependence can cause neuroscience studies to be interpreted in terms of functional pathways documented in better studied tissues (e.g., liver) and topics (e.g., cancer), and systematically emphasizes well-studied genes, leaving other findings in the obscurity of the brain "ignorome". To address this issue, we compiled a curated database of 918 gene sets related to nervous system function, tissue, and cell types ("Brain.GMT") that can be used within common analysis pipelines (GSEA, limma, edgeR) to interpret results from three species (rat, mouse, human). Brain.GMT includes brain-related gene sets curated from the Molecular Signatures Database (MSigDB) and extracted from public databases (GeneWeaver, Gemma, DropViz, BrainInABlender, HippoSeq) and published studies containing differential expression results. Although Brain.GMT is still undergoing development and currently only represents a fraction of available brain gene sets, "brain ignorome" genes are already better represented than in traditional Gene Ontology databases. Moreover, Brain.GMT substantially improves the quantity and quality of gene sets identified as enriched with differential expression in neuroscience studies, enhancing interpretation. •We compiled a curated database of 918 gene sets related to nervous system function, tissue, and cell types ("Brain.GMT").•Brain.GMT can be used within common analysis pipelines (GSEA, limma, edgeR) to interpret neuroscience transcriptional profiling results from three species (rat, mouse, human).•Although Brain.GMT is still undergoing development, it substantially improved the interpretation of differential expression results within our initial use cases.

Impact of folic acid supplementation on the epigenetic profile in healthy unfortified individuals - a randomized intervention trial

Folate is an essential mediator in one-carbon metabolism, which provides methyl groups for DNA synthesis and methylation. The availability of active methyl groups can be influenced by the uptake of folic acid. We conducted a randomized intervention trial to test the influence of folic acid supplementation on DNA methylation in an unfortified population in Germany. A total of 16 healthy male volunteers (age range 23-61 y) were randomized to receive either 400 μg (n = 9) or 800 μg (n = 7) folic acid supplements daily for 8 weeks. Infinium Human Methylation 450K BeadChip Microarrays were used to assay site-specific DNA methylation across the genome. Microarray analyses were conducted on PBL DNA. We estimated several epigenetic clocks and mean DNA methylation across all autosomal probes on the array. AgeAccel was estimated as the residual variation in each metric. In virtually all participants, both serum and red blood cell (RBC) folate increased successively throughout the trial period. Participants with a larger increase in RBC folate had a larger increase in DNAmAge AgeAccel (Spearman Rho: 0.56, p-value = 0.03). No notable changes in the methylome resulting from the folic acid supplementation emerged. In this population with adequate folate levels derived from diet, an increase in RBC folate had a modest impact on the epigenetic clock predicting chronologic age.

Personalized analysis of human cancer multi-omics for precision oncology

Multi-omics technologies, encompassing genomics, proteomics, and transcriptomics, provide profound insights into cancer biology. A fundamental computational approach for analyzing multi-omics data is differential analysis, which identifies molecular distinctions between cancerous and normal tissues. Traditional methods, however, often fail to address the distinct heterogeneity of individual tumors, thereby neglecting crucial patient-specific molecular traits. This shortcoming underscores the necessity for tailored differential analysis algorithms, which focus on particular patient variations. Such approaches offer a more nuanced understanding of cancer biology and are instrumental in pinpointing personalized therapeutic strategies. In this review, we summarize the principles of current individualized techniques. We also review their efficacy in analyzing cancer multi-omics data and discuss their potential applications in clinical practice.

Extracellular vesicles from virulent P. brasiliensis induce TLR4 and dectin-1 expression in innate cells and promote enhanced Th1/Th17 response

Extracellular vesicles (EVs) are membrane-enclosed nanoparticles that transport several biomolecules and are involved in important mechanisms and functions related to the pathophysiology of fungal diseases. EVs from Paracoccidioides brasiliensis, the main causative agent of Paracoccidioidomycosis (PCM), modulate the immune response of macrophages. In this study, we assessed the EVs proteome from a virulent P. brasiliensis isolated from granulomatous lesions and compared their immunomodulatory ability with EVs isolated from the fungus before the animal passage (control EVs) when challenging macrophages and dendritic cells (DCs). Proteome showed that virulent EVs have a higher abundance of virulence factors such as GP43, protein 14-3-3, GAPDH, as well as virulence factors never described in PCM, such as aspartyl aminopeptidase and a SidJ analogue compared with control EVs. Virulent extracellular vesicles induced higher expression of TLR4 and Dectin-1 than control EVs in macrophages and dendritic cells (DCs). In opposition, a lower TLR2 expression was induced by virulent EVs. Additionally, virulent EVs induced lower expression of CD80, CD86 and TNF-α, but promoted a higher expression of IL-6 and IL-10, suggesting that EVs isolated from virulent P. brasiliensis-yeast promote a milder DCs and macrophage maturation. Herein, we showed that EVs from virulent fungi stimulated a higher frequency of Th1/Tc1, Th17, and Treg cells, which gives new insights into fungal extracellular vesicles. Taken together, our results suggest that P. brasiliensis utilizes its EVs as virulence bags that manipulate the immune system in its favour, creating a milder immune response and helping with fungal evasion from the immune system.

A multi-omic single-cell landscape of cellular diversification in the developing human cerebral cortex

The vast neuronal diversity in the human neocortex is vital for high-order brain functions, necessitating elucidation of the regulatory mechanisms underlying such unparalleled diversity. However, recent studies have yet to comprehensively reveal the diversity of neurons and the molecular logic of neocortical origin in humans at single-cell resolution through profiling transcriptomic or epigenomic landscapes, owing to the application of unimodal data alone to depict exceedingly heterogeneous populations of neurons. In this study, we generated a comprehensive compendium of the developing human neocortex by simultaneously profiling gene expression and open chromatin from the same cell. We computationally reconstructed the differentiation trajectories of excitatory projection neurons of cortical origin and inferred the regulatory logic governing lineage bifurcation decisions for neuronal diversification. We demonstrated that neuronal diversity arises from progenitor cell lineage specificity and postmitotic differentiation at distinct stages. Our data paves the way for understanding the primarily coordinated regulatory logic for neuronal diversification in the neocortex.

Transmission of reduced levels of miR-34/449 from sperm to preimplantation embryos is a key step in the transgenerational epigenetic inheritance of the effects of paternal chronic social instability stress

The transgenerational effects of exposing male mice to chronic social instability (CSI) stress are associated with decreased sperm levels of multiple members of the miR-34/449 family that persist after their mating through preimplantation embryo (PIE) development. Here we demonstrate the importance of these miRNA changes by showing that restoring miR-34c levels in PIEs derived from CSI stressed males prevents elevated anxiety and defective sociability normally found specifically in their adult female offspring. It also restores, at least partially, levels of sperm miR-34/449 normally reduced in their male offspring who transmit these sex-specific traits to their offspring. Strikingly, these experiments also revealed that inducing miR-34c levels in PIEs enhances the expression of its own gene and that of miR-449 in these cells. The same induction of embryo miR-34/449 gene expression likely occurs after sperm-derived miR-34c is introduced into oocytes upon fertilization. Thus, suppression of this miRNA amplification system when sperm miR-34c levels are reduced in CSI stressed mice can explain how a comparable fold-suppression of miR-34/449 levels can be found in PIEs derived from them, despite sperm containing ~50-fold lower levels of these miRNAs than those already present in PIEs. We previously found that men exposed to early life trauma also display reduced sperm levels of miR-34/449. And here we show that miR-34c can also increase the expression of its own gene, and that of miR-449 in human embryonic stem cells, suggesting that human PIEs derived from men with low sperm miR-34/449 levels may also contain this potentially harmful defect.

Benchmarking tools for transcription factor prioritization

Spatiotemporal regulation of gene expression is controlled by transcription factor (TF) binding to regulatory elements, resulting in a plethora of cell types and cell states from the same genetic information. Due to the importance of regulatory elements, various sequencing methods have been developed to localise them in genomes, for example using ChIP-seq profiling of the histone mark H3K27ac that marks active regulatory regions. Moreover, multiple tools have been developed to predict TF binding to these regulatory elements based on DNA sequence. As altered gene expression is a hallmark of disease phenotypes, identifying TFs driving such gene expression programs is critical for the identification of novel drug targets. In this study, we curated 84 chromatin profiling experiments (H3K27ac ChIP-seq) where TFs were perturbed through e.g., genetic knockout or overexpression. We ran nine published tools to prioritize TFs using these real-world datasets and evaluated the performance of the methods in identifying the perturbed TFs. This allowed the nomination of three frontrunner tools, namely RcisTarget, MEIRLOP and monaLisa. Our analyses revealed opportunities and commonalities of tools that will help to guide further improvements and developments in the field.