A Mendelian randomization study: physical activities and chronic kidney disease

Increasing evidence has shown that physical activity is related to a lower risk of chronic kidney disease (CKD), thus indicating a potential target for prevention. However, the causality is not clear; specifically, physical activity may protect against CKD, and CKD may lead to a reduction in physical activity. Our study examined the potential bidirectional relationship between physical activity and CKD by using a genetically informed method. Genome-wide association studies from the UK Biobank baseline data were used for physical activity phenotypes and included 460,376 participants. For kidney function (estimated Glomerular Filtration Rate (eGFR) and CKD, with eGFR < 60 mL/min/1.73 m2), CKDGen Consortium data were used, which included 480,698 CKD participants of European ancestry. Mendelian randomization (MR) analysis was used to determine the causal relationship between physical activities and kidney function. Two-sample MR genetically predicted that heavy DIY (do it yourself) (e.g., weeding, lawn mowing, carpentry, and digging) decreased the risk of CKD (odds ratio [OR] = 0.287, 95% CI = 0.117-0.705, p = 0.0065) and improved the level of eGFR (β = 0.036, 95% CI = 0.005-0.067, p = 0.021). The bidirectional MR showed no reverse causality. It is worth noting that other physical activities, such as walking for pleasure, strenuous sports, light DIY (e.g., pruning and watering the lawn), and other exercises (e.g., swimming, cycling, keeping fit, and bowling), were not significantly correlated with CKD and eGFR. This study used genetic data to provide reliable and robust causal evidence that heavy physical activity (e.g., weeding, lawn mowing, carpentry, and digging) can protect kidney function and further lower the risk of CKD.

T4SEpp: A pipeline integrating protein language models to predict bacterial type IV secreted effectors

Many pathogenic bacteria use type IV secretion systems (T4SSs) to deliver effectors (T4SEs) into the cytoplasm of eukaryotic cells, causing diseases. The identification of effectors is a crucial step in understanding the mechanisms of bacterial pathogenicity, but this remains a major challenge. In this study, we used the full-length embedding features generated by six pre-trained protein language models to train classifiers predicting T4SEs and compared their performance. We integrated three modules into a model called T4SEpp. The first module searched for full-length homologs of known T4SEs, signal sequences, and effector domains; the second module fine-tuned a machine learning model using data for a signal sequence feature; and the third module used the three best-performing pre-trained protein language models. T4SEpp outperformed other state-of-the-art (SOTA) software tools, achieving ∼0.98 accuracy at a high specificity of ∼0.99, based on the assessment of an independent validation dataset. T4SEpp predicted 13 T4SEs from Helicobacter pylori, including the well-known CagA and 12 other potential ones, among which eleven could potentially interact with human proteins. This suggests that these potential T4SEs may be associated with the pathogenicity of H. pylori. Overall, T4SEpp provides a better solution to assist in the identification of bacterial T4SEs and facilitates studies of bacterial pathogenicity. T4SEpp is freely accessible at https://bis.zju.edu.cn/T4SEpp.

AIMER: A SNP-independent software for identifying imprinting-like allelic methylated regions from DNA methylome

Genomic imprinting is essential for mammalian growth and embryogenesis. High-throughput bisulfite sequencing accompanied with parental haplotype-specific information allows analysis of imprinted genes and imprinting control regions (ICRs) on a large scale. Currently, although several allelic methylated regions (AMRs) detection software were developed, methods for detecting imprinted AMRs is still limited. Here, we developed a SNP-independent statistical approach, AIMER, to detect imprinting-like AMRs. By using the mouse frontal cortex methylome as input, we demonstrated that AIMER performs very well in detecting known germline ICRs compared with other methods. Furthermore, we found the putative parental AMRs AIMER detected could be distinguished from sequence-dependent AMRs. Finally, we found a novel germline imprinting-like AMR using WGBS data from 17 distinct mouse tissue samples. The results indicate that AIMER is a good choice for detecting imprinting-like (parent-of-origin-dependent) AMRs. We hope this method will be helpful for future genomic imprinting studies. The Python source code for our project is now publicly available on both GitHub (https://github.com/ZhaoLab-TMU/AIMER) and Gitee (https://gitee.com/zhaolab_tmu/AIMER).

dbEBV: A database of Epstein-Barr virus variants and their correlations with human health

Since Epstein-Barr virus (EBV) was discovered in 1964, it has been reported to be associated with various malignancies as well as benign diseases, and the pathogenicity of EBV has been widely studied. Several databases have been established to provide comprehensive information on the virus and its relation to diseases and introduce convenient analysis tools. Although they have greatly facilitated the analysis of EBV at the genome, gene, protein, or epitope level, they did not provide enough insight into the genomic variants of EBV, which have been suggested as relevant to diseases by multiple studies. Here, we introduce dbEBV, a comprehensive database of EBV genomic variation landscape, which contains 942 EBV genomes with 109,893 variants from different tissues or cell lines in 24 countries. The database enables the visualization of information with varying global frequencies and their relationship with the human health of each variant. It also supports phylogenetic analysis at the genome or gene level in subgroups of different characteristics. Information of interest can easily be reached with functions such as searching, browsing, and filtering. In conclusion, dbEBV is a convenient resource for exploring EBV genomic variants, freely available at http://dbebv.omicsbio.info.

Computational modeling for deciphering tissue microenvironment heterogeneity from spatially resolved transcriptomics

Spatial transcriptomics techniques, while measuring gene expression, retain spatial location information, aiding in situ studies of organismal tissue architecture and the progression of pathological processes. These techniques generate vast amounts of omics data, necessitating the development of computational methods to reveal the underlying tissue microenvironment heterogeneity. The main directions in spatial transcriptomics data analysis are spatial domain detection and spatial deconvolution, which can identify spatial functional regions and parse the distribution of cell types in spatial transcriptomics data by integrating single-cell transcriptomics data. In these two research directions, many computational methods have been successively proposed. This article will categorize them into three types: machine learning-based methods, probabilistic models-based methods, and deep learning-based methods. It will list and discuss the representative algorithms of each type along with their advantages and disadvantages and describe the datasets and evaluation metrics used to assess these computational methods, facilitating researchers in selecting suitable computational methods according to their research needs. Finally, combining the latest technological developments and the advantages and disadvantages of current algorithms, this article will look forward to the future directions of computational method development.

Analysis of Haemonchus embryos at single cell resolution identifies two eukaryotic elongation factors as intervention target candidates

Advances in single cell technologies are allowing investigations of a wide range of biological processes and pathways in animals, such as the multicellular model organism Caenorhabditis elegans - a free-living nematode. However, there has been limited application of such technology to related parasitic nematodes which cause major diseases of humans and animals worldwide. With no vaccines against the vast majority of parasitic nematodes and treatment failures due to drug resistance or inefficacy, new intervention targets are urgently needed, preferably informed by a deep understanding of these nematodes' cellular and molecular biology - which is presently lacking for most worms. Here, we created the first single cell atlas for an early developmental stage of Haemonchus contortus - a highly pathogenic, C. elegans-related parasitic nematode. We obtained and curated RNA sequence (snRNA-seq) data from single nuclei from embryonating eggs of H. contortus (150,000 droplets), and selected high-quality transcriptomic data for > 14,000 single nuclei for analysis, and identified 19 distinct clusters of cells. Guided by comparative analyses with C. elegans, we were able to reproducibly assign seven cell clusters to body wall muscle, hypodermis, neuronal, intestinal or seam cells, and identified eight genes that were transcribed in all cell clusters/types, three of which were inferred to be essential in H. contortus. Two of these genes (i.e. Hc-eef-1A and Hc-eef1G), coding for eukaryotic elongation factors (called Hc-eEF1A and Hc-eEF1G), were also demonstrated to be transcribed and expressed in all key developmental stages of H. contortus. Together with these findings, sequence- and structure-based comparative analyses indicated the potential of Hc-eEF1A and/or Hc-eEF1G as intervention targets within the protein biosynthesis machinery of H. contortus. Future work will focus on single cell studies of all key developmental stages and tissues of H. contortus, and on evaluating the suitability of the two elongation factor proteins as drug targets in H. contortus and related nematodes, with a view to finding new nematocidal drug candidates.

Enhancing prediction of short linear protein motifs with Wregex 3.0

Short linear motifs (SLiMs) play an important role in protein-protein interactions. However, SLiM patterns are intrinsically permissive and result into many matches that occur just by chance, specially when targeting large datasets. To prioritize these matches as candidates for functional testing, we developed Wregex (Weighted regular expression), which uses a position-specific scoring matrix (PSSM) to order a list of regular expression matches according to a PSSM-derived score. Here we present Wregex 3.0, an improved version with new functionalities such as the support for a second auxiliary motif to help refining prediction of a primary SLiM, and post-translational modifications (PTMs) enrichment taking into account that many regulatory SLiM-mediated interactions are modulated by one or more PTMs. This version also incorporates a number of new features such as a convenient use of subproteomes, showing UniProt annotations such as disordered regions, searching for all known motifs and generating decoy databases for enrichment analysis. We provide case studies to illustrate how these new Wregex functionalities enhance prediction of short linear protein motifs. The Wregex 3.0 server is freely accessible at https://ehubio.ehu.eus/wregex3/.

Genetic architecture of epigenetic cortical clock age in brain tissue from older individuals: alterations in CD46 and other loci

The cortical epigenetic clock was developed in brain tissue as a biomarker of brain aging. As one way to identify mechanisms underlying aging, we conducted a GWAS of cortical age. We leveraged postmortem cortex tissue and genotyping array data from 694 participants of the Rush Memory and Aging Project and Religious Orders Study (ROSMAP; 11000,000 SNPs), and meta-analysed ROSMAP with 522 participants of Brains for Dementia Research (5,000,000 overlapping SNPs). We confirmed results using eQTL (cortical bulk and single nucleus gene expression), cortical protein levels (ROSMAP), and phenome-wide association studies (clinical/neuropathologic phenotypes, ROSMAP). In the meta-analysis, the strongest association was rs4244620 (p = 1.29 × 10-7), which also exhibited FDR-significant cis-eQTL effects for CD46 in bulk and single nucleus (microglia, astrocyte, oligodendrocyte, neuron) cortical gene expression. Additionally, rs4244620 was nominally associated with lower cognition, faster slopes of cognitive decline, and greater Parkinsonian signs (n ~ 1700 ROSMAP with SNP/phenotypic data; all p ≤ 0.04). In ROSMAP alone, the top SNP was rs4721030 (p = 8.64 × 10-8) annotated to TMEM106B and THSD7A. Further, in ROSMAP (n = 849), TMEM106B and THSD7A protein levels in cortex were related to many phenotypes, including greater AD pathology and lower cognition (all p ≤ 0.0007). Overall, we identified converging evidence of CD46 and possibly TMEM106B/THSD7A for potential roles in cortical epigenetic clock age.

drexml: A command line tool and Python package for drug repurposing

We introduce drexml, a command line tool and Python package for rational data-driven drug repurposing. The package employs machine learning and mechanistic signal transduction modeling to identify drug targets capable of regulating a particular disease. In addition, it employs explainability tools to contextualize potential drug targets within the functional landscape of the disease. The methodology is validated in Fanconi Anemia and Familial Melanoma, two distinct rare diseases where there is a pressing need for solutions. In the Fanconi Anemia case, the model successfully predicts previously validated repurposed drugs, while in the Familial Melanoma case, it identifies a promising set of drugs for further investigation.

Imprinted gene alterations in the kidneys of growth restricted offspring may be mediated by a long non-coding RNA

Altered epigenetic mechanisms have been previously reported in growth restricted offspring whose mothers experienced environmental insults during pregnancy in both human and rodent studies. We previously reported changes in the expression of the DNA methyltransferase Dnmt3a and the imprinted genes Cdkn1c (Cyclin-dependent kinase inhibitor 1C) and Kcnq1 (Potassium voltage-gated channel subfamily Q member 1) in the kidney tissue of growth restricted rats whose mothers had uteroplacental insufficiency induced on day 18 of gestation, at both embryonic day 20 (E20) and postnatal day 1 (PN1). To determine the mechanisms responsible for changes in the expression of these imprinted genes, we investigated DNA methylation of KvDMR1, an imprinting control region (ICR) that includes the promoter of the antisense long non-coding RNA Kcnq1ot1 (Kcnq1 opposite strand/antisense transcript 1). Kcnq1ot1 expression decreased by 51% in growth restricted offspring compared to sham at PN1. Interestingly, there was a negative correlation between Kcnq1ot1 and Kcnq1 in the E20 growth restricted group (Spearman's ρ = 0.014). No correlation was observed between Kcnq1ot1 and Cdkn1c expression in either group at any time point. Additionally, there was a 11.25% decrease in the methylation level at one CpG site within KvDMR1 ICR. This study, together with others in the literature, supports that long non-coding RNAs may mediate changes seen in tissues of growth restricted offspring.

Mendelian randomization analysis revealed that albuminuria is the key factor affecting socioeconomic status in CKD patients

Previous studies indicate a strong correlation between the incidence of chronic kidney disease (CKD) and lower economic status. However, these studies often struggle to delineate a clear cause-effect relationship, leaving healthcare providers uncertain about how to manage kidney disease in a way that improves patients' financial outcomes. Our study aimed to explore and establish a causal relationship between CKD and socioeconomic status, identifying critical influencing factors. We utilized summary meta-analysis data from the CKDGen Consortium and UK Biobank. Genetic variants identified from these sources served as instrumental variables (IVs) to estimate the association between CKD and socioeconomic status. The presence or absence of CKD, estimated glomerular filtration rate (eGFR), and albuminuria were used as exposures, while income and regional deprivation were analyzed as outcomes. We employed the R packages 'TwoSampleMR' and 'Mendelianrandomization' to conduct both univariable and multivariable Mendelian randomization (MR) analyses, assessing for potential pleiotropy and heterogeneity. Our univariable MR analysis revealed a significant causal relationship between high levels of albuminuria and lower income (OR = 0.84, 95% CI: 0.73-0.96, p = 0.013), with no significant pleiotropy detected. In the multivariable MR analysis, both CKD (OR = 0.867, 95% CI: 0.786-0.957, p = 0.0045) and eGFR (OR = 0.065, 95% CI: 0.010-0.437, p = 0.0049) exhibited significant effects on income. This study underscores that higher albuminuria levels in CKD patients are associated with decreased income and emphasizes the importance of effective management and treatment of albuminuria in CKD patients to mitigate both social and personal economic burdens.

Resistance mechanism of Escherichia coli strains with different ampicillin resistance levels

Antibiotic resistance is an important problem that threatens medical treatment. Differences in the resistance levels of microorganisms cause great difficulties in understanding the mechanisms of antibiotic resistance. Therefore, the molecular reasons underlying the differences in the level of antibiotic resistance need to be clarified. For this purpose, genomic and transcriptomic analyses were performed on three Escherichia coli strains with varying degrees of adaptive resistance to ampicillin. Whole-genome sequencing of strains with different levels of resistance detected five mutations in strains with 10-fold resistance and two additional mutations in strains with 95-fold resistance. Overall, three of the seven mutations occurred as a single base change, while the other four occurred as insertions or deletions. While it was thought that 10-fold resistance was achieved by the effect of mutations in the ftsI, marAR, and rpoC genes, it was found that 95-fold resistance was achieved by the synergistic effect of five mutations and the ampC mutation. In addition, when the general transcriptomic profiles were examined, it was found that similar transcriptomic responses were elicited in strains with different levels of resistance. This study will improve our view of resistance mechanisms in bacteria with different levels of resistance and provide the basis for our understanding of the molecular mechanism of antibiotic resistance in ampicillin-resistant E. coli strains. KEY POINTS: •The mutation of the ampC promoter may act synergistically with other mutations and lead to higher resistance. •Similar transcriptomic responses to ampicillin are induced in strains with different levels of resistance. •Low antibiotic concentrations are the steps that allow rapid achievement of high antibiotic resistance.

A review on trends in development and translation of omics signatures in cancer

The field of cancer genomics and transcriptomics has evolved from targeted profiling to swift sequencing of individual tumor genome and transcriptome. The steady growth in genome, epigenome, and transcriptome datasets on a genome-wide scale has significantly increased our capability in capturing signatures that represent both the intrinsic and extrinsic biological features of tumors. These biological differences can help in precise molecular subtyping of cancer, predicting tumor progression, metastatic potential, and resistance to therapeutic agents. In this review, we summarized the current development of genomic, methylomic, transcriptomic, proteomic and metabolic signatures in the field of cancer research and highlighted their potentials in clinical applications to improve diagnosis, prognosis, and treatment decision in cancer patients.

Methylation patterns associated with C-reactive protein in racially and ethnically diverse populations

Systemic low-grade inflammation is a feature of chronic disease. C-reactive protein (CRP) is a common biomarker of inflammation and used as an indicator of disease risk; however, the role of inflammation in disease is not completely understood. Methylation is an epigenetic modification in the DNA which plays a pivotal role in gene expression. In this study we evaluated differential DNA methylation patterns associated with blood CRP level to elucidate biological pathways and genetic regulatory mechanisms to improve the understanding of chronic inflammation. The racially and ethnically diverse participants in this study were included as 50% White, 41% Black or African American, 7% Hispanic or Latino/a, and 2% Native Hawaiian, Asian American, American Indian, or Alaska Native (total n = 13,433) individuals. We replicated 113 CpG sites from 87 unique loci, of which five were novel (CADM3, NALCN, NLRC5, ZNF792, and cg03282312), across a discovery set of 1,150 CpG sites associated with CRP level (p < 1.2E-7). The downstream pathways affected by DNA methylation included the identification of IFI16 and IRF7 CpG-gene transcript pairs which contributed to the innate immune response gene enrichment pathway along with NLRC5, NOD2, and AIM2. Gene enrichment analysis also identified the nuclear factor-kappaB transcription pathway. Using two-sample Mendelian randomization (MR) we inferred methylation at three CpG sites as causal for CRP levels using both White and Black or African American MR instrument variables. Overall, we identified novel CpG sites and gene transcripts that could be valuable in understanding the specific cellular processes and pathogenic mechanisms involved in inflammation.

Circulating interleukin-27 is associated with the risk of chronic periodontitis and allergic rhinitis: A Mendelian randomization analysis

BACKGROUND

Chronic periodontitis (CP) and allergic rhinitis (AR) have attracted wide attention as global public health problems with high incidence. Recent studies have shown that circulating interleukin-27 (IL-27) is associated with the risk of CP and AR. The aim of this study is to analyze the causal effect between them using Mendelian randomization (MR).

METHODS

Bidirectional MR analyses were performed with the use of publicly available genome-wide association study (GWAS) data. Summary data on circulating IL-27, CP, and AR published in genome-wide association studies were collected. Instrumental variables (IV) were extracted using assumptions of correlation, independence and exclusivity as criteria. Inverse variance weighting (IVW) was used as the main method, combined with weighted median method (WM) and MR-Egger and other MR Analysis methods for causal inference of exposure and outcome. Cochran's Q and MR-Egger intercept were used for sensitivity analysis.

RESULTS

The IVW study showed a causal effect between increased circulating IL-27 levels and increased risk of CP (OR = 1.14, 95%CI = 1.02-1.26, p = .020). Similarly, the increase of circulating IL-27 level had a causal effect on the decreased risk of AR (OR = 0.88, 95%CI = 0.80-0.97, p = .012). In addition, IVW study found that there was a causal between the increased risk of CP and circulating IL-27 level (OR = 1.05, 95%CI = 1.01-1.10, p = .016). However, there was no significant causal relationship between the risk of AR and circulating IL-27 levels (OR = 0.97, 95%CI = 0.91-1.02, p = .209). no significant heterogeneity or horizontal pleiotropy was found in sensitivity analysis.

CONCLUSIONS

There is a causal effect between circulating IL-27 level and CP, AR, which will help to find new ideas and methods for the diagnosis and treatment of CP and AR.

The effect of histo-blood group ABO system transferase (BGAT) on pregnancy related outcomes：A Mendelian randomization study

Protein level of Histo-Blood Group ABO System Transferase (BGAT) has been reported to be associated with cardiometabolic diseases. But its effect on pregnancy related outcomes still remains unclear. Here we conducted a two-sample Mendelian randomization (MR) study to ascertain the putative causal roles of protein levels of BGAT in pregnancy related outcomes. Cis-acting protein quantitative trait loci (pQTLs) robustly associated with protein level of BGAT (P < 5 ×10-8) were used as instruments to proxy the BGAT protein level (N = 35,559, data from deCODE), with two additional pQTL datasets from Fenland (N = 10,708) and INTERVAL (N = 3301) used as validation exposures. Ten pregnancy related diseases and complications were selected as outcomes. We observed that a higher protein level of BGAT showed a putative causal effect on venous complications and haemorrhoids in pregnancy (VH) (odds ratio [OR]=1.19, 95% confidence interval [95% CI]=1.12-1.27, colocalization probability=91%), which was validated by using pQTLs from Fenland and INTERVAL. The Mendelian randomization results further showed effects of the BGAT protein on gestational hypertension (GH) (OR=0.97, 95% CI=0.96-0.99), despite little colocalization evidence to support it. Sensitivity analyses, including proteome-wide Mendelian randomization of the cis-acting BGAT pQTLs, showed little evidence of horizontal pleiotropy. Correctively, our study prioritised BGAT as a putative causal protein for venous complications and haemorrhoids in pregnancy. Future epidemiology and clinical studies are needed to investigate whether BGAT can be considered as a drug target to prevent adverse pregnancy outcomes.

Single-cell 5' RNA sequencing of camelid peripheral B cells provides insights into cellular basis of heavy-chain antibody production

Camelids produce both conventional tetrameric antibodies (Abs) and dimeric heavy-chain antibodies (HCAbs). Although B cells that generate these two types of Abs exhibit distinct B cell receptors (BCRs), whether these two B cell populations differ in their phenotypes and developmental processes remains unclear. Here, we performed single-cell 5' RNA profiling of peripheral blood mononuclear cell samples from Bactrian camels before and after immunization. We characterized the functional subtypes and differentiation trajectories of circulating B cells in camels, and reconstructed single-cell BCR sequences. We found that in contrast to humans, the proportion of T-bet+ B cells was high among camelid peripheral B cells. Several marker genes of human B cell subtypes, including CD27 and IGHD, were expressed at low levels in the corresponding camel B cell subtypes. Camelid B cells expressing variable genes of HACbs (VHH) were widely present in various functional subtypes and showed highly overlapping differentiation trajectories with B cells expressing variable genes of conventional Abs (VH). After immunization, the transcriptional changes in VHH+ and VH+ B cells were largely consistent. Through structure modeling, we identified a variety of scaffold types among the reconstructed VHH sequences. Our study provides insights into the cellular context of HCAb production in camels and lays the foundation for developing single-B cell-based camelid single-domain Ab screening.

Advanced computational predictive models of miRNA-mRNA interaction efficiency

The modeling of miRNA-mRNA interactions holds significant implications for synthetic biology and human health. However, this research area presents specific challenges due to the multifaceted nature of mRNA downregulation by miRNAs, influenced by numerous factors including competition or synergism among miRNAs and mRNAs. In this study, we present an improved computational model for predicting miRNA-mRNA interactions, addressing aspects not previously modeled. Firstly, we integrated a novel set of features that significantly enhanced the predictor's performance. Secondly, we demonstrated the cell-specific nature of certain aspects of miRNA-mRNA interactions, highlighting the importance of designing models tailored to specific cell types for improved accuracy. Moreover, we introduce a miRNA binding site interaction model (miBSIM) that, for the first time, accounts for both the distribution of miRNA binding sites along the mRNA and their respective strengths in regulating mRNA stability. Our analysis suggests that distant miRNA sites often compete with each other, revealing the intricate interplay of binding site interactions. Overall, our new predictive model shows a significant improvement of up to 6.43% over previous models in the field. The code of our model is available at https://www.cs.tau.ac.il/~tamirtul/miBSIM.

Co-expression of immune checkpoints in glioblastoma revealed by single-nucleus RNA sequencing and spatial transcriptomics

Glioblastoma (GBM) is one of the most malignant tumors of the central nervous system. The pattern of immune checkpoint expression in GBM remains largely unknown. We performed snRNA-Seq and spatial transcriptomic (ST) analyses on untreated GBM samples. 8 major cell types were found in both tumor and adjacent normal tissues, with variations in infiltration grade. Neoplastic cells_6 was identified in malignant cells with high expression of invasion and proliferator-related genes, and analyzed its interactions with microglia, MDM cells and T cells. Significant alterations in ligand-receptor interactions were observed, particularly between Neoplastic cells_6 and microglia, and found prominent expression of VISTA/VSIG3, suggesting a potential mechanism for evading immune system attacks. High expression of TIM-3, VISTA, PSGL-1 and VSIG-3 with similar expression patterns in GBM, may have potential as therapeutic targets. The prognostic value of VISTA expression was cross-validated in 180 glioma patients, and it was observed that patients with high VISTA expression had a poorer prognosis. In addition, multimodal cross analysis integrated SnRNA-seq and ST, revealing complex intracellular communication and mapping the GBM tumor microenvironment. This study reveals novel molecular characteristics of GBM, co-expression of immune checkpoints, and potential therapeutic targets, contributing to improving the understanding and treatment of GBM.

Techniques for assessing telomere length: A methodological review

Telomeres are located at the ends of chromosomes and have specific sequences with a distinctive structure that safeguards genes. They possess capping structures that protect chromosome ends from fusion events and ensure chromosome stability. Telomeres shorten in length during each cycle of cell division. When this length reaches a certain threshold, it can lead to genomic instability, thus being implicated in various diseases, including cancer and neurodegenerative disorders. The possibility of telomeres serving as a biomarker for aging and age-related disease is being explored, and their significance is still under study. This is because post-mitotic cells, which are mature cells that do not undergo mitosis, do not experience telomere shortening due to age. Instead, other causes, for example, exposure to oxidative stress, can directly damage the telomeres, causing genomic instability. Nonetheless, a general agreement has been established that measuring telomere length offers valuable insights and forms a crucial foundation for analyzing gene expression and epigenetic data. Numerous approaches have been developed to accurately measure telomere lengths. In this review, we summarize various methods and their advantages and limitations for assessing telomere length.

A global view of altered ligand-receptor interactions in bone marrow aging based on single-cell sequencing

Altered cell-cell communication is a hallmark of aging, but its impact on bone marrow aging remains poorly understood. Based on a common and effective pipeline and single-cell transcriptome sequencing, we detected 384,124 interactions including 2575 ligand-receptor pairs and 16 non-adherent bone marrow cell types in old and young mouse and identified a total of 5560 significantly different interactions, which were then verified by flow cytometry and quantitative real-time PCR. These differential ligand-receptor interactions exhibited enrichment for the senescence-associated secretory phenotypes. Further validation demonstrated supplementing specific extracellular ligands could modify the senescent signs of hematopoietic stem cells derived from old mouse. Our work provides an effective procedure to detect the ligand-receptor interactions based on single-cell sequencing, which contributes to understand mechanisms and provides a potential strategy for intervention of bone marrow aging.

Genome-wide characterization of structure variations in the Xiang pig for genetic resistance to African swine fever

African swine fever (ASF) is a rapidly fatal viral haemorrhagic fever in Chinese domestic pigs. Although very high mortality is observed in pig farms after an ASF outbreak, clinically healthy and antibody-positive pigs are found in those farms, and viral detection is rare from these pigs. The ability of pigs to resist ASF viral infection may be modulated by host genetic variations. However, the genetic basis of the resistance of domestic pigs against ASF remains unclear. We generated a comprehensive set of structural variations (SVs) in a Chinese indigenous Xiang pig with ASF-resistant (Xiang-R) and ASF-susceptible (Xiang-S) phenotypes using whole-genome resequencing method. A total of 53,589 nonredundant SVs were identified, with an average of 25,656 SVs per individual in the Xiang pig genome, including insertion, deletion, inversion and duplication variations. The Xiang-R group harboured more SVs than the Xiang-S group. The F-statistics (FST) was carried out to reveal genetic differences between two populations using the resequencing data at each SV locus. We identified 2,414 population-stratified SVs and annotated 1,152 Ensembl genes (including 986 protein-coding genes), in which 1,326 SVs might disturb the structure and expression of the Ensembl genes. Those protein-coding genes were mainly enriched in the Wnt, Hippo, and calcium signalling pathways. Other important pathways associated with the ASF viral infection were also identified, such as the endocytosis, apoptosis, focal adhesion, Fc gamma R-mediated phagocytosis, junction, NOD-like receptor, PI3K-Akt, and c-type lectin receptor signalling pathways. Finally, we identified 135 candidate adaptive genes overlapping 166 SVs that were involved in the virus entry and virus-host cell interactions. The fact that some of population-stratified SVs regions detected as selective sweep signals gave another support for the genetic variations affecting pig resistance against ASF. The research indicates that SVs play an important role in the evolutionary processes of Xiang pig adaptation to ASF infection.

Causal effect of lipoprotein(a) level on chronic kidney disease of European ancestry: a two-sample Mendelian randomization study

INTRODUCTION

Chronic kidney disease is a growing health issue, and the options of prevention and therapy remain limited. Although a number of observational studies have linked higher Lp(a) [lipoprotein(a)] levels to the kidney impairment, the causal relationship remains to be determined. The purpose of this study was to assess the causal association between Lp(a) levels and CKD.

METHODS

We selected eight single-nucleotide polymorphisms (SNPs) significantly associated with Lp(a) levels as instrumental variables. Genome-wide association study (GWAS) from CKDGen consortium yielded the summary data information for CKD. We designed the bidirectional two-sample Mendelian randomization (MR) analyses. The estimates were computed using inverse-variance weighted (IVW), simple median, weighted median, and maximum likelihood. MR-Egger regression was used to detect pleiotropy.

RESULTS

Fixed-effect IVW analysis indicated that genetically predicted Lp(a) levels were associated with CKD significantly (odds ratio, 1.039; 95% CI, 1.009-1.069; p = 0.010). The SNPs showed no pleiotropy according to result of MR-Egger test. Results from sensitivity analyses were consistent. In the inverse MR analysis, random-effect IVW method showed CKD had no causal effect on the elevated Lp(a) (odds ratio, 1.154; 95% CI, 0.845-1.576; p = 0.367).

CONCLUSION

In this bidirectional two-sample MR analysis, the causal deteriorating effects of genetically predicted plasma Lp(a) levels on the risk of CKD were identified. On the contrary, there is no evidence to support a causal effect of CKD on Lp(a) levels.

Proteomics appending a complementary dimension to precision oncotherapy

Recent advances in high-throughput proteomic profiling technologies have facilitated the precise quantification of numerous proteins across multiple specimens concurrently. Researchers have the opportunity to comprehensively analyze the molecular signatures in plentiful medical specimens or disease pattern cell lines. Along with advances in data analysis and integration, proteomics data could be efficiently consolidated and employed to recognize precise elementary molecular mechanisms and decode individual biomarkers, guiding the precision treatment of tumors. Herein, we review a broad array of proteomics technologies and the progress and methods for the integration of proteomics data and further discuss how to better merge proteomics in precision medicine and clinical settings.

Large language models assisted multi-effect variants mining on cerebral cavernous malformation familial whole genome sequencing

Cerebral cavernous malformation (CCM) is a polygenic disease with intricate genetic interactions contributing to quantitative pathogenesis across multiple factors. The principal pathogenic genes of CCM, specifically KRIT1, CCM2, and PDCD10, have been reported, accompanied by a growing wealth of genetic data related to mutations. Furthermore, numerous other molecules associated with CCM have been unearthed. However, tackling such massive volumes of unstructured data remains challenging until the advent of advanced large language models. In this study, we developed an automated analytical pipeline specialized in single nucleotide variants (SNVs) related biomedical text analysis called BRLM. To facilitate this, BioBERT was employed to vectorize the rich information of SNVs, while a deep residue network was used to discriminate the classes of the SNVs. BRLM was initially constructed on mutations from 12 different types of TCGA cancers, achieving an accuracy exceeding 99%. It was further examined for CCM mutations in familial sequencing data analysis, highlighting an upstream master regulator gene fibroblast growth factor 1 (FGF1). With multi-omics characterization and validation in biological function, FGF1 demonstrated to play a significant role in the development of CCMs, which proved the effectiveness of our model. The BRLM web server is available at http://1.117.230.196.

Thousands of oscillating LncRNAs in the mouse testis

The long noncoding RNAs (lncRNAs) are involved in numerous fundamental biological processes, including circadian regulation. Although recent studies have revealed insights into the functions of lncRNAs, how the lncRNAs regulate circadian rhythms still requires a deeper investigation. In this study, we generate two datasets of RNA-seq profiles of the mouse (Mus musculus) testis under light-dark (LD) cycle. The first dataset included 18,613 unannotated transcripts measured at 12 time points, each with duplicate samples, under LD conditions; while the second dataset included 21,414 unannotated transcripts measured at six time points, each with three replicates, under desynchronized and control conditions. We identified 5964 testicular lncRNAs in each dataset by BLASTing these transcripts against the known mouse lncRNAs from the NONCODE database. MetaCycle analyses were performed to identify 519, 475, and 494 rhythmically expressed mouse testicular lncRNAs in the 12-time-point dataset, the six-time-point control dataset, and the six-time-point desynchronized dataset, respectively. A comparison of the expression profiles of the lncRNAs under desynchronized and control conditions revealed that 427 rhythmically expressed lncRNAs from the control condition became arrhythmic under the desynchronized condition, suggesting a possible loss of rhythmicity. In contrast, 446 arrhythmic lncRNAs from the control condition became rhythmic under the desynchronized condition, suggesting a possible gain of rhythmicity. Interestingly, 48 lncRNAs were rhythmically expressed under both desynchronized and control conditions. These oscillating lncRNAs were divided into morning lncRNAs, evening lncRNAs, and night lncRNAs based on their time-course expression patterns. We interrogated the promoter regions of these rhythmically expressed mouse testicular lncRNAs to predict their possible regulation by the E-box, D-box, or RORE promoter motifs. GO and KEGG analyses were performed to identify the possible biological functions of these rhythmically expressed mouse testicular lncRNAs. Further, we conducted conservation analyses of the rhythmically expressed mouse testicular lncRNAs with lncRNAs from humans, rats, and zebrafish, and uncovered three mouse testicular lncRNAs conserved across these four species. Finally, we computationally predicted the conserved lncRNA-encoded peptides and their 3D structures from each of the four species. Taken together, our study revealed thousands of rhythmically expressed lncRNAs in the mouse testis, setting the stage for further computational and experimental validations.

Biomaterial engineering strategies for modeling the Bruch's membrane in age-related macular degeneration

Age-related macular degeneration, a multifactorial inflammatory degenerative retinal disease, ranks as the leading cause of blindness in the elderly. Strikingly, there is a scarcity of curative therapies, especially for the atrophic advanced form of age-related macular degeneration, likely due to the lack of models able to fully recapitulate the native structure of the outer blood retinal barrier, the prime target tissue of age-related macular degeneration. Standard in vitro systems rely on 2D monocultures unable to adequately reproduce the structure and function of the outer blood retinal barrier, integrated by the dynamic interaction of the retinal pigment epithelium, the Bruch's membrane, and the underlying choriocapillaris. The Bruch's membrane provides structural and mechanical support and regulates the molecular trafficking in the outer blood retinal barrier, and therefore adequate Bruch's membrane-mimics are key for the development of physiologically relevant models of the outer blood retinal barrier. In the last years, advances in the field of biomaterial engineering have provided novel approaches to mimic the Bruch's membrane from a variety of materials. This review provides a discussion of the integrated properties and function of outer blood retinal barrier components in healthy and age-related macular degeneration status to understand the requirements to adequately fabricate Bruch's membrane biomimetic systems. Then, we discuss novel materials and techniques to fabricate Bruch's membrane-like scaffolds for age-related macular degeneration in vitro modeling, discussing their advantages and challenges with a special focus on the potential of Bruch's membrane-like mimics based on decellularized tissue.

Association between the gut microbiota and diabetic nephropathy: a two-sample Mendelian randomization study

Numerous studies have revealed a correlation between the risk of developing diabetic nephropathy (DN) and the gut microbiota (GM) composition. However, it remains uncertain whether the GM composition causes DN. We aimed to explore any potential causal links between the GM composition and the risk of developing DN. A meta-analysis conducted by the MiBioGen consortium of the largest genome-wide association study (GWAS) provided aggregated data on the GM. DN data were obtained from the IEU database. The inverse-variance weighting (IVW) method was employed as the primary analytical approach. The IVW analysis indicated that genus Dialister (OR = 0.51, 95% CI: 0.34-0.77, p = 0.00118) was protective against DN. In addition, class Gammaproteobacteria (OR = 0.47, 95% CI: 0.27-0.83, p = 0.0096), class Lentisphaeria (OR =0.76, 95% CI: 0.68-0.99, p = 0.04), order Victivallales (OR = 0.76, 95% CI: 0.58-0.99, p = 0.04), and phylum Proteobacteria (OR = 0.53, 95% CI: 0.33-0.85, p = 0.00872) were negatively associated with the risk of developing DN. Genus LachnospiraceaeUCG008 (OR =1.45, 95% CI: 1.08-1.95, p = 0.01), order Bacteroidales (OR = 1.59, 95% CI: 1.02-2.49, p = 0.04), and genus Terrisporobacter (OR = 1.98, 95% CI: 1.14-3.45, p = 0.015) were positively associated with the risk of developing DN. In this study, we established a causal relationship between the genus Dialister and the risk of developing DN. Further trials are required to confirm the protective effects of probiotics on DN and to elucidate the precise protective mechanisms involving genus Dialister and DN.

Down-regulation of A20 mRNA expression in peripheral blood mononuclear cells from MDS patients

Myelodysplastic syndrome (MDS) is characterized by activated inflammatory signaling and affects prognosis. Targeting inflammatory signaling may provide a way to treat the disease. We were curious whether there were changes in A20 in peripheral blood mononuclear cells (PBMC) of MDS patients. Therefore, we conducted a study with 60 clinical samples, including 30 MDS patients and 30 healthy controls. All patients with MDS were diagnosed and classified according to the criteria of the 2016 World Health Organization. The study was performed in accordance with the guidelines of the Declaration of Helsinki. Using Quantitative Real-Time RT-PCR, we discovered that A20 mRNA expression in PBMC of the MDS group was significantly lower than that in the control group (P < 0.001). Additionally, using Luminex Liquid Suspension Chip, we observed elevated plasma levels of pro-inflammatory IL-8 and TNF-α in the MDS group compared to the healthy control group (P < 0.001). We did not find a significant correlation between A20 mRNA and clinical characteristics (age, sex, concentration of hemoglobin, neutrophils count, platelets count, percent of blasts, and WHO classification) of the patients, nor between A20 mRNA and plasma cytokines (data not shown). Our study found down-regulated of A20 and increased levels of pro-inflammatory cytokines in the peripheral blood of MDS patients, providing further evidence for the activation of inflammatory signals in MDS.

PML Nuclear bodies: the cancer connection and beyond

Promyelocytic leukemia (PML) nuclear bodies, membrane-less organelles in the nucleus, play a crucial role in cellular homeostasis. These dynamic structures result from the assembly of scaffolding PML proteins and various partners. Recent crystal structure analyses revealed essential self-interacting domains, while liquid-liquid phase separation contributes to their formation. PML bodies orchestrate post-translational modifications, particularly stress-induced SUMOylation, impacting target protein functions. Serving as hubs in multiple signaling pathways, they influence cellular processes like senescence. Dysregulation of PML expression contributes to diseases, including cancer, highlighting their significance. Therapeutically, PML bodies are promising targets, exemplified by successful acute promyelocytic leukemia treatment with arsenic trioxide and retinoic acid restoring PML bodies. Understanding their functions illuminates both normal and pathological cellular physiology, guiding potential therapies. This review explores recent advancements in PML body biogenesis, biochemical activity, and their evolving biological roles.

Sensing the squeeze: nuclear mechanotransduction in health and disease

The nucleus not only is a repository for DNA but also a center of cellular and nuclear mechanotransduction. From nuclear deformation to the interplay between mechanosensing components and genetic control, the nucleus is poised at the nexus of mechanical forces and cellular function. Understanding the stresses acting on the nucleus, its mechanical properties, and their effects on gene expression is therefore crucial to appreciate its mechanosensitive function. In this review, we examine many elements of nuclear mechanotransduction, and discuss the repercussions on the health of cells and states of illness. By describing the processes that underlie nuclear mechanosensation and analyzing its effects on gene regulation, the review endeavors to open new avenues for studying nuclear mechanics in physiology and diseases.

A Copernican revolution of multigenic analysis: A retrospective study on clinical exome sequencing in unclear genetic disorders

Despite the inevitable shift in medical practice towards a deeper understanding of disease etiology and progression through multigenic analysis, the profound historical impact of Mendelian diseases cannot be overlooked. These diseases, such as cystic fibrosis and thalassemia, are characterized by a single variant in a single gene leading to clinical conditions, and have significantly shaped our medical knowledge and treatments. In this respect, the monogenic approach inevitably results in the underutilization of Next-Generation Sequencing (NGS) data. Herein, a retrospective study was performed to assess the diagnostic value of the clinical exome in 32 probands with specific phenotypic characteristics (patients with autoinflammation and immunological dysregulation, N = 20; patients diagnosed with Hemolytic uremic syndrome N = 9; and patients with Waldenström macroglobulinemia, N = 3). A gene enrichment analysis was performed using the *. VCF file generated by SOPHiA-DDM-v4. This analysis selected a subset of genes containing pathogenic or likely pathogenic variants with autosomal dominant (AD) inheritance. In addition, all variants of uncertain significance (VUS) were included, filtered by AD inheritance mode, the presence of compound heterozygotes, and a minor allele frequency (MAF) cutoff of 0.05 %. The aim of the pipeline described here is based on a perspective shift that focuses on analyzing patients' gene assets, offering new light on the complex interplay between genetics and disease presentation. Integrating this approach into clinical practices could significantly enhance the management of patients with rare genetic disorders.

Application of multi-omics techniques to androgenetic alopecia: Current status and perspectives

The rapid advancement of sequencing technologies has enabled the generation of vast datasets, allowing for the in-depth analysis of sequencing data. This analysis has facilitated the validation of novel pathogenesis hypotheses for understanding and treating diseases through ex vivo and in vivo experiments. Androgenetic alopecia (AGA), a common hair loss disorder, has been a key focus of investigators attempting to uncover its underlying mechanisms. Abnormal changes in mRNA, proteins, and metabolites have been identified in individuals with AGA, and future developments in sequencing technologies may reveal new biomarkers for AGA. By integrating multiple omics analysis datasets such as genomics, transcriptomics, proteomics, and metabolomics-along with clinical phenotype data-we can achieve a comprehensive understanding of the molecular underpinnings of AGA. This review summarizes the data-mining studies conducted on various omics analysis datasets as related to AGA that have been adopted to interpret the biological data obtained from different omics layers. We herein discuss the challenges of integrative omics analyses, and suggest that collaborative multi-omics studies can enhance the understanding of the complete pathomechanism(s) of AGA by focusing on the interaction networks comprising DNA, RNA, proteins, and metabolites.

MTHFD2-mediated redox homeostasis promotes gastric cancer progression under hypoxic conditions

OBJECTIVES

Cancer cells undergo metabolic reprogramming to adapt to high oxidative stress, but little is known about how metabolic remodeling enables gastric cancer cells to survive stress associated with aberrant reactive oxygen species (ROS) production. Here, we aimed to identify the key metabolic enzymes that protect gastric cancer (GC) cells from oxidative stress.

METHODS

ROS level was detected by DCFH-DA probes. Multiple cell biological studies were performed to identify the underlying mechanisms. Furthermore, cell-based xenograft and patient-derived xenograft (PDX) model were performed to evaluate the role of MTHFD2 in vivo.

RESULTS

We found that overexpression of MTHFD2, but not MTHFD1, is associated with reduced overall and disease-free survival in gastric cancer. In addition, MTHFD2 knockdown reduces the cellular NADPH/NADP+ ratio, colony formation and mitochondrial function, increases cellular ROS and cleaved PARP levels and induces in cell death under hypoxia, a hallmark of solid cancers and a common inducer of oxidative stress. Moreover, genetic or pharmacological inhibition of MTHFD2 reduces tumor burden in both tumor cell lines and patient-derived xenograft-based models.

DISCUSSION

our study highlights the crucial role of MTHFD2 in redox regulation and tumor progression, demonstrating the therapeutic potential of targeting MTHFD2.

Causal relationship between 731 immune cells and the risk of diabetic nephropathy: a two‑sample bidirectional Mendelian randomization study

OBJECTIVE

Previous observational studies have indicated associations between various immune cells and diabetic nephropathy (DN). However, the causality remains unclear. We aimed to further evaluate the causal association between immune cells and DN using bidirectional two-sample Mendelian randomization (MR) analysis.

METHOD

The DN data were retrieved from the IEU OpenGWAS Project database, while the data for 731 immune cells were sourced from GWAS summary statistics by Orru ̀ et al. The investigation into the causal relationship between immune cells and DN employed the inverse variance weighted (IVW), weighted median (WME), and MR-Egger methods. The stability and reliability of the findings underwent evaluation through Cochran's Q test, MR-Egger intercept's P-value, MR-PRESSO, and Leave-One-Out (LOO) method.

RESULT

The IVW estimates suggested a positive causal effect of CD25 on IgD-CD38dim B cell, CD25 on naive-mature B cell, CD127 on granulocyte, SSC-A on HLA DR + Natural Killer, HLA DR on plasmacytoid Dendritic Cell, and HLA DR on Dendritic Cell on DN. Conversely, the abundance of Myeloid Dendritic Cell, CD62L- Dendritic Cell %Dendritic Cell, CD86+ myeloid Dendritic Cell %Dendritic Cell, CD14- CD16-, CX3CR1 on CD14- CD16-, and SSC-A on CD4+ T cell had negative causal effects on DN. However, after correcting the P value for significant causality results using the FDR method, it was concluded that only Myeloid Dendritic Cells had a causal relationship with DN (FDR-p = 0.041), while the other immune cells showed no significant association with DN, so their relationship was suggestive. The results were stable with no observed horizontal pleiotropy and heterogeneity. Reverse MR analysis indicated no causal relationship between DN and the increased risk of positively identified immune cells.

CONCLUSION

This study provides an initial insight into the genetic perspective of the causal relationship between immune cells and DN. It establishes a crucial theoretical foundation for future endeavors in precision medicine and individualized treatment.

scBlood: A comprehensive single-cell accessible chromatin database of blood cells

The advent of single cell transposase-accessible chromatin sequencing (scATAC-seq) technology enables us to explore the genomic characteristics and chromatin accessibility of blood cells at the single-cell level. To fully make sense of the roles and regulatory complexities of blood cells, it is critical to collect and analyze these rapidly accumulating scATAC-seq datasets at a system level. Here, we present scBlood (https://bio.liclab.net/scBlood/), a comprehensive single-cell accessible chromatin database of blood cells. The current version of scBlood catalogs 770,907 blood cells and 452,247 non-blood cells from ∼400 high-quality scATAC-seq samples covering 30 tissues and 21 disease types. All data hosted on scBlood have undergone preprocessing from raw fastq files and multiple standards of quality control. Furthermore, we conducted comprehensive downstream analyses, including multi-sample integration analysis, cell clustering and annotation, differential chromatin accessibility analysis, functional enrichment analysis, co-accessibility analysis, gene activity score calculation, and transcription factor (TF) enrichment analysis. In summary, scBlood provides a user-friendly interface for searching, browsing, analyzing, visualizing, and downloading scATAC-seq data of interest. This platform facilitates insights into the functions and regulatory mechanisms of blood cells, as well as their involvement in blood-related diseases.

Human lncRNAs harbor conserved modules embedded in different sequence contexts

We analyzed the structure of human long non-coding RNA (lncRNAs) genes to investigate whether the non-coding transcriptome is organized in modular domains, as is the case for protein-coding genes. To this aim, we compared all known human lncRNA exons and identified 340 pairs of exons with high sequence and/or secondary structure similarity but embedded in a dissimilar sequence context. We grouped these pairs in 106 clusters based on their reciprocal similarities. These shared modules are highly conserved between humans and the four great ape species, display evidence of purifying selection and likely arose as a result of recent segmental duplications. Our analysis contributes to the understanding of the mechanisms driving the evolution of the non-coding genome and suggests additional strategies towards deciphering the functional complexity of this class of molecules.

Causal role of immune cells in IgA nephropathy: a mendelian randomization study

BACKGROUND

Previous observational studies have shown that immune cells play an important role in IgA nephropathy. However, the specific causal relationship between the two is inconsistent.

METHODS

We used a two-sample mendelian randomization(MR) analysis to investigate the causal association between 731 immune cell signatures and IgA nephropathy in this study. Based on published GWAS data, immune cells were characterized by four immune types absolute cell (AC) counts, median fluorescence intensity (MFI), morphological parameters (MP), relative cell (RC) counts. Meanwhile, heterogeneity test, horizontal pleiotropy and sensitivity test were used to evaluate the robustness and reliability of the results.

RESULTS

An important causal association was achieved for 14 RC traits/IgA nephropathy, 3 AC traits/IgA nephropathy, 10 MFI traits/IgA nephropathy, and 1 MP trait/IgA nephropathy. However, after false discovery rate (FDR) correction, only one immunophenotype was found to be protective against IgA nephropathy. The OR of herpesvirus entry mediator (HVEM) on terminally differentiated CD4+ T cell (maturation stages of T-cell panel) on IgA nephropathy risk was estimated to be 0.727 (95%CI: 0.624-0.847, p = 4.20e - 05, PFDR = 0.023) according to inverse variance weighting (IVW) method, and the weighted-median method yielded similar results (OR = 0.743, 95% CI: 0.596-0.927, p = 0.008). Although not statistically significant, the association was consistent with MR-Egger, simple mode and weighted mode.

CONCLUSIONS

Our study further confirmed that immune cells play a complex and important role in the pathogenesis of IgA nephropathy, providing evidence for clinical research.

DNA methylation heterogeneity attributable to a complex tumor immune microenvironment prompts prognostic risk in glioma

Gliomas are malignant tumours of the human nervous system with different World Health Organization (WHO) classifications, glioblastoma (GBM) with higher grade and are more malignant than lower-grade glioma (LGG). To dissect how the DNA methylation heterogeneity in gliomas is influenced by the complex cellular composition of the tumour immune microenvironment, we first compared the DNA methylation profiles of purified human immune cells and bulk glioma tissue, stratifying three tumour immune microenvironmental subtypes for GBM and LGG samples from The Cancer Genome Atlas (TCGA). We found that more intermediate methylation sites were enriched in glioma tumour tissues, and used the Proportion of sites with Intermediate Methylation (PIM) to compare intertumoral DNA methylation heterogeneity. A larger PIM score reflected stronger DNA methylation heterogeneity. Enhanced DNA methylation heterogeneity was associated with stronger immune cell infiltration, better survival rates, and slower tumour progression in glioma patients. We then created a Cell-type-associated DNA Methylation Heterogeneity Contribution (CMHC) score to explore the impact of different immune cell types on heterogeneous CpG site (CpGct) in glioma tissues. We identified eight prognosis-related CpGct to construct a risk score: the Cell-type-associated DNA Methylation Heterogeneity Risk (CMHR) score. CMHR was positively correlated with cytotoxic T-lymphocyte infiltration (CTL), and showed better predictive performance for IDH status (AUC = 0.96) and glioma histological phenotype (AUC = 0.81). Furthermore, DNA methylation alterations of eight CpGct might be related to drug treatments of gliomas. In conclusion, we indicated that DNA methylation heterogeneity is associated with a complex tumour immune microenvironment, glioma phenotype, and patient's prognosis.

Recent advances on the structure and the function relationships of the TRPV4 ion channel

The members of the superfamily of Transient Receptor Potential (TRP) ion channels are physiologically important molecules that have been studied for many years and are still being intensively researched. Among the vanilloid TRP subfamily, the TRPV4 ion channel is an interesting protein due to its involvement in several essential physiological processes and in the development of various diseases. As in other proteins, changes in its function that lead to the development of pathological states, have been closely associated with modification of its regulation by different molecules, but also by the appearance of mutations which affect the structure and gating of the channel. In the last few years, some structures for the TRPV4 channel have been solved. Due to the importance of this protein in physiology, here we discuss the recent progress in determining the structure of the TRPV4 channel, which has been achieved in three species of animals (Xenopus tropicalis, Mus musculus, and Homo sapiens), highlighting conserved features as well as key differences among them and emphasizing the binding sites for some ligands that play crucial roles in its regulation.

DeepCORE: An interpretable multi-view deep neural network model to detect co-operative regulatory elements

Gene transcription is an essential process involved in all aspects of cellular functions with significant impact on biological traits and diseases. This process is tightly regulated by multiple elements that co-operate to jointly modulate the transcription levels of target genes. To decipher the complicated regulatory network, we present a novel multi-view attention-based deep neural network that models the relationship between genetic, epigenetic, and transcriptional patterns and identifies co-operative regulatory elements (COREs). We applied this new method, named DeepCORE, to predict transcriptomes in various tissues and cell lines, which outperformed the state-of-the-art algorithms. Furthermore, DeepCORE contains an interpreter that extracts the attention values embedded in the deep neural network, maps the attended regions to putative regulatory elements, and infers COREs based on correlated attentions. The identified COREs are significantly enriched with known promoters and enhancers. Novel regulatory elements discovered by DeepCORE showed epigenetic signatures consistent with the status of histone modification marks.

Calling the question: what is mammalian transgenerational epigenetic inheritance?

While transgenerational epigenetic inheritance has been extensively documented in plants, nematodes, and fruit flies, its existence in mammals remains controversial. Several factors have contributed to this debate, including the lack of a clear distinction between intergenerational and transgenerational epigenetic inheritance (TEI), the inconsistency of some studies, the potential confounding effects of in-utero vs. epigenetic factors, and, most importantly, the biological challenge of epigenetic reprogramming. Two waves of epigenetic reprogramming occur: in the primordial germ cells and the developing embryo after fertilization, characterized by global erasure of DNA methylation and remodelling of histone modifications. Consequently, TEI can only occur if specific genetic regions evade this reprogramming and persist through embryonic development. These challenges have revived the long-standing debate about the possibility of inheriting acquired traits, which has been strongly contested since the Lamarckian and Darwinian eras. As a result, coupled with the absence of universally accepted criteria for transgenerational epigenetic studies, a vast body of literature has emerged claiming evidence of TEI. Therefore, the goal of this study is to advocate for establishing fundamental criteria that must be met for a study to qualify as evidence of TEI. We identified five criteria based on the consensus of studies that critically evaluated TEI. To assess whether published original research papers adhere to these criteria, we examined 80 studies that either claimed or were cited as supporting TEI. The findings of this analysis underscore the widespread confusion in this field and highlight the urgent need for a unified scientific consensus on TEI requirements.

Prediction of additional hospital days in patients undergoing cervical spine surgery with machine learning methods

BACKGROUND

Machine learning (ML), a subset of artificial intelligence (AI), uses algorithms to analyze data and predict outcomes without extensive human intervention. In healthcare, ML is gaining attention for enhancing patient outcomes. This study focuses on predicting additional hospital days (AHD) for patients with cervical spondylosis (CS), a condition affecting the cervical spine. The research aims to develop an ML-based nomogram model analyzing clinical and demographic factors to estimate hospital length of stay (LOS). Accurate AHD predictions enable efficient resource allocation, improved patient care, and potential cost reduction in healthcare.

METHODS

The study selected CS patients undergoing cervical spine surgery and investigated their medical data. A total of 945 patients were recruited, with 570 males and 375 females. The mean number of LOS calculated for the total sample was 8.64 ± 3.7 days. A LOS equal to or <8.64 days was categorized as the AHD-negative group (n = 539), and a LOS > 8.64 days comprised the AHD-positive group (n = 406). The collected data was randomly divided into training and validation cohorts using a 7:3 ratio. The parameters included their general conditions, chronic diseases, preoperative clinical scores, and preoperative radiographic data including ossification of the anterior longitudinal ligament (OALL), ossification of the posterior longitudinal ligament (OPLL), cervical instability and magnetic resonance imaging T2-weighted imaging high signal (MRI T2WIHS), operative indicators and complications. ML-based models like Lasso regression, random forest (RF), and support vector machine (SVM) recursive feature elimination (SVM-RFE) were developed for predicting AHD-related risk factors. The intersections of the variables screened by the aforementioned algorithms were utilized to construct a nomogram model for predicting AHD in patients. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve and C-index were used to evaluate the performance of the nomogram. Calibration curve and decision curve analysis (DCA) were performed to test the calibration performance and clinical utility.

RESULTS

For these participants, 25 statistically significant parameters were identified as risk factors for AHD. Among these, nine factors were obtained as the intersection factors of these three ML algorithms and were used to develop a nomogram model. These factors were gender, age, body mass index (BMI), American Spinal Injury Association (ASIA) scores, magnetic resonance imaging T2-weighted imaging high signal (MRI T2WIHS), operated segment, intraoperative bleeding volume, the volume of drainage, and diabetes. After model validation, the AUC was 0.753 in the training cohort and 0.777 in the validation cohort. The calibration curve exhibited a satisfactory agreement between the nomogram predictions and actual probabilities. The C-index was 0.788 (95% confidence interval: 0.73214-0.84386). On the decision curve analysis (DCA), the threshold probability of the nomogram ranged from 1 to 99% (training cohort) and 1 to 75% (validation cohort).

CONCLUSION

We successfully developed an ML model for predicting AHD in patients undergoing cervical spine surgery, showcasing its potential to support clinicians in AHD identification and enhance perioperative treatment strategies.

Long non-coding RNAs: roles in cellular stress responses and epigenetic mechanisms regulating chromatin

Most of the genome is transcribed into RNA but only 2% of the sequence codes for proteins. Non-coding RNA transcripts include a very large number of long noncoding RNAs (lncRNAs). A growing number of identified lncRNAs operate in cellular stress responses, for example in response to hypoxia, genotoxic stress, and oxidative stress. Additionally, lncRNA plays important roles in epigenetic mechanisms operating at chromatin and in maintaining chromatin architecture. Here, we address three lncRNA topics that have had significant recent advances. The first is an emerging role for many lncRNAs in cellular stress responses. The second is the development of high throughput screening assays to develop causal relationships between lncRNAs across the genome with cellular functions. Finally, we turn to recent advances in understanding the role of lncRNAs in regulating chromatin architecture and epigenetics, advances that build on some of the earliest work linking RNA to chromatin architecture.

Deciphering lung granulomas in HIV & TB co-infection: unveiling macrophages aggregation with IL6R/STAT3 activation

Tuberculosis (TB) remains a leading cause of mortality among individuals coinfected with HIV, characterized by progressive pulmonary inflammation. Despite TB's hallmark being focal granulomatous lung lesions, our understanding of the histopathological features and regulation of inflammation in HIV & TB coinfection remains incomplete. In this study, we aimed to elucidate these histopathological features through an immunohistochemistry analysis of HIV & TB co-infected and TB patients, revealing marked differences. Notably, HIV & TB granulomas exhibited aggregation of CD68 + macrophage (Mφ), while TB lesions predominantly featured aggregation of CD20+ B cells, highlighting distinct immune responses in coinfection. Spatial transcriptome profiling further elucidated CD68+ Mφ aggregation in HIV & TB, accompanied by activation of IL6 pathway, potentially exacerbating inflammation. Through multiplex immunostaining, we validated two granuloma types in HIV & TB versus three in TB, distinguished by cell architecture. Remarkably, in the two types of HIV & TB granulomas, CD68 + Mφ highly co-expressed IL6R/pSTAT3, contrasting TB granulomas' high IFNGRA/SOCS3 expression, indicating different signaling pathways at play. Thus, activation of IL6 pathway may intensify inflammation in HIV & TB-lungs, while SOCS3-enriched immune microenvironment suppresses IL6-induced over-inflammation in TB. These findings provide crucial insights into HIV & TB granuloma formation, shedding light on potential therapeutic targets, particularly for granulomatous pulmonary under HIV & TB co-infection. Our study emphasizes the importance of a comprehensive understanding of the immunopathogenesis of HIV & TB coinfection and suggests potential avenues for targeting IL6 signaling with SOCS3 activators or anti-IL6R agents to mitigate lung inflammation in HIV & TB coinfected individuals.

Identification of a human type XVII collagen fragment with high capacity for maintaining skin health

Collagen XVII (COL17) is a transmembrane protein that mediates skin homeostasis. Due to expression of full length collagen was hard to achieve in microorganisms, arising the needs for selection of collagen fragments with desired functions for microbial biosynthesis. Here, COL17 fragments (27-33 amino acids) were extracted and replicated 16 times for recombinant expression in Escherichia coli. Five variants were soluble expressed, with the highest yield of 223 mg/L. The fusion tag was removed for biochemical and biophysical characterization. Circular dichroism results suggested one variant (sample-1707) with a triple-helix structure at >37 °C. Sample-1707 can assemble into nanofiber (width, 5.6 nm) and form hydrogel at 3 mg/mL. Sample-1707 was shown to induce blood clotting and promote osteoblast differentiation. Furthermore, sample-1707 exhibited high capacity to induce mouse hair follicle stem cells differentiation and osteoblast migration, demonstrating a high capacity to induce skin cell regeneration and promote wound healing. A strong hydrogel was prepared from a chitosan and sample-1707 complex with a swelling rate of >30 % higher than simply using chitosan. Fed-batch fermentation of sample-1707 with a 5-L bioreactor obtained a yield of 600 mg/L. These results support the large-scale production of sample-1707 as a biomaterial for use in the skin care industry.

SOX6 AU controls myogenesis by cis-modulation of SOX6 in cattle

Long non-coding RNAs (lncRNAs) have been shown to be involved in the regulation of skeletal muscle development through multiple mechanisms. The present study revealed that the lncRNA SOX6 AU (SRY-box transcription factor 6 antisense upstream) is reverse transcribed from upstream of the bovine sex-determining region Y (SRY)-related high-mobility-group box 6 (SOX6) gene. SOX6 AU was significantly differentially expressed in muscle tissue among different developmental stages in Xianan cattle. Subsequently, knockdown and overexpression experiments discovered that SOX6 AU promoted primary skeletal muscle cells proliferation, apoptosis, and differentiation in bovine. The overexpression of SOX6 AU in bovine primary skeletal muscle cells resulted in 483 differentially expressed genes (DEGs), including 224 upregulated DEGs and 259 downregulated DEGs. GO functional annotation analysis showed that muscle development-related biological processes such as muscle structure development and muscle cell proliferation were significantly enriched. KEGG pathway analysis revealed that the PI3K/AKT and MAPK signaling pathways were important pathways for DEG enrichment. Notably, we found that SOX6 AU inhibited the mRNA and protein expression levels of the SOX6 gene. Moreover, knockdown of the SOX6 gene promoted the proliferation and apoptosis of bovine primary skeletal muscle cells. Finally, we showed that SOX6 AU promoted the proliferation and apoptosis of bovine primary skeletal muscle cells by cis-modulation of SOX6 in cattle. This work illustrates our discovery of the molecular mechanisms underlying the regulation of SOX6 AU in the development of beef.

Epigenetic editing of BRCA1 promoter increases cisplatin and olaparib sensitivity of ovarian cancer cells

Drug resistance is the primary contributor to the high mortality rate of ovarian cancer (OC). The loss of BRCA1/2 function is linked to drug sensitivity in OC cells. The aim of this study is to enhance the drug sensitivity of OC cells by inducing BRCA1 dysfunction through promoter epigenetic editing. Epigenetic regulatory regions within the BRCA1 promoter, affecting gene expression, were initially discerned through analysis of clinical samples. Subsequently, we designed and rigorously validated epigenetic editing tools. Ultimately, we evaluated the cisplatin and olaparib sensitivity of the OC cells after editing. The BRCA1 promoter contains two CpG-rich regions, with methylation of the region covering the transcription start site (TSS) strongly correlating with transcription and influencing OC development, prognosis, and homologous recombination (HR) defects. Targeting this region in OC cells using our designed epigenetic editing tools led to substantial and persistent DNA methylation changes, accompanied by significant reductions in H3K27ac histone modifications. This resulted in a notable suppression of BRCA1 expression and a decrease in HR repair capacity. Consequently, edited OC cells exhibited heightened sensitivity to cisplatin and olaparib, leading to increased apoptosis rates. Epigenetic inactivation of the BRCA1 promoter can enhance cisplatin and olaparib sensitivity of OC cells through a reduction in HR repair capacity, indicating the potential utility of epigenetic editing technology in sensitization therapy for OC.

Elucidating the causal nexus and immune mediation between frailty and chronic kidney disease: integrative multi-omics analysis

BACKGROUND

Empirical research has consistently documented the concurrent manifestation of frailty and chronic kidney disease (CKD). However, the existence of a reverse causal association or the influence of confounding variables on these correlations remains ambiguous.

METHODS

Our analysis of 7,078 participants from National Health and Nutrition Examination Survey(NHANES) (1999-2018) applied weighted logistic regression and Mendelian Randomization (MR) to investigate the correlation between the frailty index (FI) and renal function. The multivariate MR analysis was specifically adjusted for type 2 diabetes and hypertension. Further analysis explored 3282 plasma proteins to link FI to CKD. A two-step network MR highlighted immune cells' mediating roles in the FI-CKD relationship.

RESULT

Genetically inferred FI and various renal function markers are significantly correlated, as supported by NHANES analyses. Multivariate MR analysis revealed a direct causal association between the FI and CKD. Additionally, our investigation into plasma proteins identified Tmprss11D and MICB correlated with FI and CKD, respectively. A two-step network MR to reveal 15 immune cell types, notably Central Memory CD4+ T cells and Lymphocytes, as crucial mediators between FI and CKD.

CONCLUSION

Our work establishes a causal connection between frailty and CKD, mediated by specific immune cell profiles. These findings highlight the importance of immune mechanisms in the frailty-CKD interplay and suggest that targeting shared risk factors and immune pathways could improve management strategies for these conditions. Our research contributes to a more nuanced understanding of frailty and CKD, offering new avenues for intervention and patient care in an aging population.

Biomarkers in diagnosing and therapeutic monitoring of tuberculosis: a review

Tuberculosis (TB) continues to pose a significant health challenge worldwide, emphasizing the importance of prompt diagnosis and efficient monitoring of treatment outcomes for effective disease control. Biomarkers have become increasingly important in the realm of TB diagnoses and treatment. The objective of this comprehensive review is to examine the present state of biomarkers employed in the diagnosis of TB, monitoring the response to treatment, and predicting treatment outcomes. In this study, we undertake a comprehensive examination of the diverse biomarkers utilized in TB diagnoses, spanning molecular, immunological, and other novel methodologies. Furthermore, we examine the potential of biomarkers in the context of therapeutic monitoring, assessment of treatment effectiveness, and anticipation of drug resistance. Additionally, this paper presents future prospects regarding the utilization of biomarkers in the therapy of tuberculosis.