The Gene Ontology Resource: 20 years and still GOing strong

A hypoxia-derived gene signature to suggest cisplatin-based therapeutic responses in patients with cervical cancer

Cervical cancer remains a significant global public health concern, often exhibits cisplatin resistance in clinical settings. Hypoxia, a characteristic of cervical cancer, substantially contributes to cisplatin resistance. To evaluate the therapeutic efficacy of cisplatin in patients with cervical cancer and to identify potential effective drugs against cisplatin resistance, we established a hypoxia-inducible factor-1 (HIF-1)-related risk score (HRRS) model using clinical data from patients treated with cisplatin. Cox and LASSO regression analyses were used to stratify patient risks and prognosis. Through qRT-PCR, we validated nine potential prognostic HIF-1 genes that successfully predict cisplatin responsiveness in patients and cell lines. Subsequently, we identified fostamatinib, an FDA-approved spleen tyrosine kinase inhibitor, as a promising drug for targeting the HRRS-high group. We observed a positive correlation between the IC50 values of fostamatinib and HRRS in cervical cancer cell lines. Moreover, fostamatinib exhibited potent anticancer effects on high HRRS groups in vitro and in vivo. In summary, we developed a hypoxia-related gene signature that suggests cisplatin response prediction in cervical cancer and identified fostamatinib as a potential novel treatment approach for resistant cases.

Comprehensive analysis of abnormal methylation modification differential expression mRNAs between low-grade and high-grade intervertebral disc degeneration and its correlation with immune cells

BACKGROUND

Intervertebral disc degeneration (IDD) is an important cause of low back pain. The aim of this study is to identify the potential molecular mechanism of abnormal methylation-modified DNA in the progression of IDD, hoping to contribute to the diagnosis and management of IDD.

METHODS

Low-grade IDD (grade I-II) and high-grade IDD (grade III-V) data were downloaded from GSE70362 and GSE129789 datasets. The abnormally methylated modified differentially expressed mRNAs (DEmRNAs) were identified by differential expression analysis (screening criteria were p < .05 and |logFC| > 1) and differential methylation analysis (screening criteria were p < .05 and |δβ| > 0.1). The classification models were constructed, and the receiver operating characteristic analysis was also carried out. In addition, functional enrichment analysis and immune correlation analysis were performed and the miRNAs targeted for the abnormally methylated DEmRNAs were predicted. Finally, expression validation was performed using real-time PCR.

RESULTS

Compared with low-grade IDD, seven abnormal methylation-modified DEmRNAs (AOX1, IBSP, QDPR, ABLIM1, CRISPLD2, ACTC1 and EMILIN1) were identified in high-grade IDD, and the classification models of random forests (RF) and support vector machine (SVM) were constructed. Moreover, seven abnormal methylation-modified DEmRNAs and classification models have high diagnostic accuracy (area under the curve [AUC] > 0.8). We also found that AUC values of single abnormal methylation-modified DEmRNA were all lower than those of RF and SVM classification models. Pearson correlation analysis found that macrophages M2 and EMILIN1 had significant negative correlation, while macrophages M2 and IBSP had significant positive correlation. In addition, four targeted relationship pairs (hsa-miR-4728-5p-QDPR, hsa-miR-4533-ABLIM1, hsa-miR-4728-5p-ABLIM1 and hsa-miR-4534-CRISPLD2) and multiple signalling pathways (for example, PI3K-AKT signalling pathway, osteoclast differentiation and calcium signalling pathway) were also identified that may be involved in the progression of IDD.

CONCLUSION

The identification of abnormal methylation-modified DEmRNAs and the construction of classification models in this study were helpful for the diagnosis and management of IDD progression.

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.

Metabolomics and molecular dynamics unveil the therapeutic potential of epalrestat in diabetic nephropathy

Diabetic nephropathy (DN) is one of the leading clinical causes of end-stage renal failure. The classical aldose reductase (AR) inhibitor epalrestat shows beneficial effect on renal dysfunction induced by DN, with metabolic profile and molecular mechanisms remains to be investigated further. In the current study, integrated untargeted metabolomics, network pharmacology and molecular dynamics approaches were applied to explore the therapeutic mechanisms of epalrestat against DN. Firstly, untargeted serum and urine metabolomics analysis based on UPLC-Q-TOF-MS was performed, revealed that epalrestat could regulate the metabolic disorders of amino acids metabolism, arachidonic acid metabolism, pyrimidine metabolism and citrate cycle metabolism pathways after DN. Subsequently, metabolomics-based network analysis was carried out to predict potential active targets of epalrestat, mainly involving AGE-RAGE signaling pathway, TNF signaling pathway and HIF-1 signaling pathway. Moreover, a 100 ns molecular dynamics approach was employed to validate the interactions between epalrestat and the core targets, showing that epalrestat could form remarkable tight binding with GLUT1 and NFκB than it with AR. Surface-plasmon resonance assay further verified epalrestat could bind GLUT1 and NFκB proteins specifically. Overall, integrated system network analysis not only demonstrated that epalrestat could attenuate DN induced metabolic disorders and renal injuries, but also revealed that it could interact with multi-targets to play a synergistic regulatory role in the treatment of DN.

De novo mutations promote inflammation in children with STAT3 gain-of-function syndrome by affecting IL-1β expression

STAT3 gain-of-function syndrome, characterized by early-onset autoimmunity and primary immune regulatory disorder, remains poorly understood in terms of its immunological mechanisms. We employed whole-genome sequencing of familial trios to elucidate the pivotal role of de novo mutations in genetic diseases. We identified 37 high-risk pathogenic loci affecting 23 genes, including a novel STAT3 c.508G>A mutation. We also observed significant down-regulation of pathogenic genes in affected individuals, potentially associated with inflammatory responses regulated by PTPN14 via miR378c. These findings enhance our understanding of the pathogenesis of STAT3 gain-of-function syndrome and suggest potential therapeutic strategies. Notably, combined JAK inhibitors and IL-6R antagonists may offer promising treatment avenues for mitigating the severity of STAT3 gain-of-function syndrome.

Single-cell RNA sequencing analysis provides novel insights into the role of apoptosis-related genes in muscle aging

OBJECTIVE

This study employed a comprehensive single-cell analysis approach to explore the role of cell apoptosis-related genes in muscle aging.

METHODS

The single-cell RNA sequencing data from the GSE143704 dataset were used to identify distinct cell clusters and assess gene expression patterns related to apoptosis activation. The "limma" package was used to identify hub genes, after which we performed Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis to identify relevant pathways. Additionally, Gene Set Enrichment Analysis(GSEA) and Gene Set Variation Analysis (GSVA) were used to uncover relevant biological pathways. The Receiver Operating Characteristic Curve (ROC) was used to evaluate the diagnostic value of the hub genes. Single-sample Gene Set Enrichment Analysis (ssGSEA) was used to analyze the immune cell infiltration levels.

RESULTS

Single-cell sequencing data from muscle aging patients allowed the identification of various cell types, including epithelial cells, adipocytes, and tissue-resident macrophages. By conducting a differential expression analysis that intersected active and nonactive apoptosis, as well as comparing elderly and young samples, a total of 22 hub genes were identified (p < 0.05). The 22 hub genes have discriminative ability as potential biomarkers for diagnosing muscle aging. The enrichment analysis indicated that these genes were closely associated with diverse pathways, including "response to UV-B" and "extracellular matrix organization" (p < 0.05). Furthermore, GSEA and GSVA indicated that multiple pathways emerged-for example, the "complement and coagulation cascades", "proteasome", "insulin signaling pathway", and "MAPK signaling pathway". Additionally, the analysis of immune cell infiltration revealed positive correlations between most of the hub genes and immune cells.

CONCLUSION

Our study identified 22 apoptosis-related genes involved in muscle aging and indicated their potential diagnostic value. These findings offer a novel perspective on the pathogenesis of muscle aging and present potential targets for therapeutic interventions.

Mammary adipocytes promote breast tumor cell invasion and angiogenesis in the context of menopause and obesity

The mechanism(s) underlying obesity-related postmenopausal (PM) breast cancer (BC) are not clearly understood. We hypothesized that the increased local presence of 'obese' mammary adipocytes within the BC microenvironment promotes the acquisition of an invasive and angiogenic BC cell phenotype and accelerates tumor proliferation and progression. BC cells, treated with primary mammary adipocyte secretome from premenopausal (Pre-M) and PM obese women (ObAdCM; obese adipocyte conditioned-media) upregulated the expression of several pro-tumorigenic factors including VEGF, lipocalin-2 and IL-6. Both Pre-M and PM ObAdCM stimulated endothelial cell recruitment and proliferation and significantly stimulated BC cell proliferation, migration and invasion. IL-6 and LCN2 induced STAT3/Akt signaling in BC cells and STAT3 inhibition abrogated the ObAdCM-stimulated BC cell proliferation and migration. Expression of proangiogenic regulators including VEGF, NRP1, NRP2, IL8RB, TGFβ2, and TSP-1 were found to be differentially regulated in mammary adipocytes from obese PM women. Comparative RNAseq indicated an upregulation of PI3K/Akt signaling, ECM-receptor interactions and lipid/fatty acid metabolism in PM versus Pre-M mammary adipocytes. Our results demonstrate that irrespective of menopausal status, cross-talk between obese mammary adipocytes and BC cells promotes tumor aggressiveness and suggest that targeting the LCN2/IL-6/STAT3 signaling axis may be a useful strategy in obesity-driven breast tumorigenesis.

NFKBIE is a predictive factor of survival and is correlated with immune infiltration and antigen processing and presentation in hepatocellular carcinoma

The important role of the nuclear factor κB (NFκB) pathway in tumour development has long been recognized; however, the role of the NFκB inhibitor family in liver cancer has not been elucidated. Hepatocellular carcinoma (HCC) is a serious public health burden with a high incidence, poor prognosis, and early detection, especially in Asia, where hepatitis is prevalent. In the present study, the mRNA expression level of the NFκB inhibitor family was assessed in HCC and normal tissues using the Metabolic Gene Rapid Visualizer, University of Alabama at Birmingham Cancer Data Analysis Portal, and the Tumor Immune Estimation Resource database (TIMER). Survival curves of nuclear factor of κ light polypeptide gene enhancer in B-cells inhibitor (NFKBI)E were obtained using the Kaplan-Meier method. Genes co-expressed with NFKBIE in HCC samples were studied using data from the LinkedOmics and the Hepatocellular Carcinoma Databases. Protein-protein interaction networks, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment pathway analyses were used to assess the NFKBIE mechanism in HCC. Using the TIMER database, the association between immune infiltration and NFKBIE was determined. RNA-sequencing (RNA-seq) was used to evaluate the function of NFKBIE in HCC and its impact on proliferation and migration. Western blotting was used to confirm the expression of NFKBIE in HCC cell lines. In addition, NFKBIE overexpression in HCC was demonstrated using tissue microarrays encompassing 80 pairs of HCC and normal liver tissues. NFKBIE was the only NFκB inhibitor with high expression and an improved prognosis in HCC compared with other NFκB inhibitors. NFKBIE was correlated with clinical characteristics, such as tumour grade, tumour protein P53 mutation status and tumour stage. Data obtained from Gene Set Cancer Analysis suggested that NFKBIE may inhibit the PI3K/AKT, RAS/MAPK, RTK and TSC/mTOR pathways. In addition, NFKBIE was significantly associated with B-cell immune infiltration and the RNA-seq data demonstrated that knockdown of NFKBIE significantly affected 'Antigen processing and presentation' and 'hepatocellular carcinoma' pathways. Immunohistochemistry of microarrays of tissue samples revealed that NFKBIE was overexpressed in several stages of HCC. Finally, inhibition of NFKBIE decreased the proliferation and migration of HCC cells. In conclusion, due to its prognostic value and overexpression in HCC, NFKBIE distinguished itself from other NFκB inhibitors. As such, it may provide a novel prognostic indicator and immunotherapeutic target for HCC.

C/EBPβ deletion in macrophages impairs mammary gland alveolar budding during the estrous cycle

Macrophages have important roles in mammary gland development and tissue homeostasis, but the specific mechanisms that regulate macrophage function need further elucidation. We have identified C/EBPβ as an important transcription factor expressed by multiple macrophage populations in the normal mammary gland. Mammary glands from mice with C/EBPβ-deficient macrophages (Cebpb ΔM) show a significant decrease in alveolar budding during the diestrus stage of the reproductive cycle, whereas branching morphogenesis remains unchanged. Defects in alveolar budding were found to be the result of both systemic hormones and local macrophage-directed signals. RNA sequencing shows significant changes in PR-responsive genes and alterations in the Wnt landscape of mammary epithelial cells of Cebpb ΔM mice, which regulate stem cell expansion during diestrus. Cebpb ΔM macrophages demonstrate a shift from a pro-inflammatory to a tissue-reparative phenotype, and exhibit increased phagocytic capacity as compared to WT. Finally, Cebpb ΔM macrophages down-regulate Notch2 and Notch3, which normally promote stem cell expansion during alveolar budding. These results suggest that C/EBPβ is an important macrophage factor that facilitates macrophage-epithelial crosstalk during a key stage of mammary gland tissue homeostasis.

Network pharmacology combined with molecular docking revealed the potential targets of Coridius chinensis in prostate cancer treatment

BACKGROUND

Prostate cancer (PCa) has high morbidity and mortality rates in elderly men. With a history of thousands of years, traditional Chinese medicine derived from insects could be an important source for developing cancer-targeted drugs to prevent tumorigenesis, enhance therapeutic effects, and reduce the risk of recurrence and metastasis. Multiple studies have shown that Coridius chinensis (Cc) has anticancer effects.

AIM

To elucidate the mechanism of action of Cc against PCa via network pharmacology and molecular docking.

METHODS

Potential targets for Cc and PCa were predicted using ChemDraw 19.0 software, the PharmMapper database and the GeneCards database. Then, the STRING database was used to construct the protein–protein interaction network. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment and molecular docking analyses were subsequently conducted to identify the key targets, active ingredients and pathways involved.

RESULTS

GO and KEGG analyses indicated that the PI3K-Akt signalling pathway was the critical pathway (P value < 1.0 × 10^-8). Multiple targeting ingredients that can affect multiple pathways in PCa have been identified in Cc. Seven active compounds (asponguanosines A, asponguanine B, asponguanine C, aspongpyrazine A, N-acetyldopamine, aspongadenine B and aspongpyrazine B) were selected for molecular docking with 9 potential targets, and the results revealed that aspongpyrazine A and asponguanosine A are the main components by which Cc affects PCa (affinity<-5 kcal/mol, hydrogen bonding), but more studies are needed.

CONCLUSION

We used network pharmacology to predict the bioactive components and important targets of Cc for the treatment of PCa, supporting the development of Cc as a natural anticancer agent.

Anti-Toxoplasma gondii effects of XYP1-derived peptides and regulatory mechanisms of XYP1

BACKGROUND

Toxoplasmosis, caused by Toxoplasma gondii , poses serious health issues for humans and animals. Individuals with impaired immune systems are more susceptible to severe toxoplasmosis. Pregnant women infected by T. gondii can face the possibility of birth defects and miscarriages. While pyrimethamine and sulfadiazine are commonly used drugs in clinical practice, concerns over their side effects and resistance are on the rise. A spider peptide XYP1 isolated from Lycosa coelestis had potent anti-T. gondii effects, but it had a high synthesis cost and strong cytotoxicity.

METHODS

This study intended to modify XYP1 for producing derived peptides via amino acid truncation and substitution. The anti-T. gondii effect was evaluated by trypan blue staining assay and killing experiment of RH strain tachyzoites. The CCK8 and hemolysis assays were used to compare their safeties. The morphological changes of T. gondii were observed by scanning electron microscope and transmission electron microscope. In addition, the mechanism of XYP1 against T. gondii through RNA-sequencing was further explored.

RESULTS

In vivo and in vitro experiments revealed that XYP1-18 and XYP1-18-1 had excellent anti-T. gondii activity with lower cytotoxicity and hemolysis activity than XYP1. XYP1, XYP1-18, and XYP1-18-1 were able to disrupt the surface membrane integrity of T. gondii tachyzoites, forming pores and causing the disruption of organelles. Furthermore, RNA-sequencing analysis indicated that XYP1 could stimulate the host immune response to effectively eliminate T. gondii and lessen the host's inflammatory reaction.

CONCLUSIONS

XYP1-18 had lower cytotoxicity and hemolysis activity than XYP1, as well as significantly extending the survival time of the mice. XYP1 played a role in host inflammation and immune responses, revealing its potential mechanism. Our research provided valuable insights into the development and application of peptide-based drugs, offering novel strategies and directions for treating toxoplasmosis.

Analysis of Unfolded Protein Response Activation in Colon Adenocarcinoma Epithelial Cells: A Proteomic Study

PURPOSE

High throughput technologies have identified molecular patterns in colorectal cancer (CRC) cells, aiding in modeling responses to anti-cancer treatments. The different responses observed depend on the type of cancer, the tumour grade and the functional programme of the cancer cells. Recent studies suggest that the unfolded protein response (UPR), autophagy and apoptosis could be involved in treatment resistance mechanisms by interacting with the tumour microenvironment (TME).

EXPERIMENTAL DESIGN

We analysed by LC-MS/MS the proteome of two representative colon adenocarcinoma epithelial cell lines from different tumour grades (CCL-233 and CCL-221) at the basal state or after the UPR induction.

RESULTS

Cell lines expressed a different proteome on about 10% of their total proteins identified, especially on UPR, autophagy and apoptosis pathways proteins at basal state. After UPR induction, the proteome of the cells was modified with a greater adaptive response to cellular stress in CCL-221 cells where the UPR was strongly activated at the basal state.

CONCLUSIONS AND CLINICAL RELEVANCE

CRC cell lines at different tumour grades expressed different functional programmes at the proteomic level and were characterised by different responses to the UPR induction. This study suggests that baseline cancer cell stress status could have an impact on the efficiency of cancer therapies.

Exploration and validation of ceRNA regulatory networks in colorectal cancer based on associations whole transcriptome sequencing

Colorectal cancer (CRC) is a wide-spread gastrointestinal cancer that is associated with augmented morbidity and mortality, and we do not yet have a deep understanding of its epidemiology and carcinogenicity. The transcriptome can reveal the complexity and heterogeneity of tumors and uncover new biomarkers or treatment options. In this study, we identified messenger RNAs (mRNAs), long non-coding RNAs (lncRNAs), round RNAs (circRNAs), and microRNAs (miRNAs) using whole-transcriptome sequencing and generated competing endogenous RNA (ceRNA) modulatory axes. We conducted whole transcriptome sequencing on 10 CRC and para-cancer (CRCP) samples and discovered 2465 differentially expressed (DE) mRNAs (DEmRNAs), 77 DE miRNAs (DEmiRNAs). 2852 DE lncRNAs (DElncRNAs) and 1477 DE circRNAs (DEcircRNAs). In addition, utilizing co-DE analysis, we generated the ceRNA axis. Subsequently, we employed the ceRNA axis to identify essential genes and corresponding associations with lncRNAs, circRNAs, and miRNAs in CRC. ceRNA regulatory network including mRNA-miRNA-lncRNA and mRNA-miRNA-circRNA. These modulatory axes potentially modulate the positive regulation of smooth muscle contraction, melanosome, plasma membrane, integral plasma membrane component and so on. Finally, the results of RNA sequencing (RNA-SEQ) were combined with the TCGA and GEO databases, and the DEGs strongly correlated with the TCGA-COAD overall survival (OS) as estimated by univariate cox and logarithmic rank analyses were cross-analyzed, and the co-upregulated DEGs were screened. Among the many DEs, KPNA2 was chosen for additional analysis. Using invitro experimentations, western blot, CCK8, EdU and other experiments were performed to verify the results. We found siRNA-based KPNA2 depletion reduces bladder cancer cells' viability, migratory, and proliferative activities, which showed that the DEmRNA profiles were comparable to the sequencing information, confirming that the sequencing data were very reliable. These evidences highlight the ceRNA regulatory mechanisms in CRC and will aid future research into the molecular mechanisms behind colorectal cancer prevention and treatment.

The macroscale routing mechanism of structural brain connectivity related to body mass index

Understanding the brain's mechanisms in individuals with obesity is important for managing body weight. Prior neuroimaging studies extensively investigated alterations in brain structure and function related to body mass index (BMI). However, how the network communication among the large-scale brain networks differs across BMI is underinvestigated. This study used diffusion magnetic resonance imaging of 290 young adults to identify links between BMI and brain network mechanisms. Navigation efficiency, a measure of network routing, was calculated from the structural connectivity computed using diffusion tractography. The sensory and frontoparietal networks indicated positive associations between navigation efficiency and BMI. The neurotransmitter association analysis identified that serotonergic and dopaminergic receptors, as well as opioid and norepinephrine systems, were related to BMI-related alterations in navigation efficiency. The transcriptomic analysis found that genes associated with network routing across BMI overlapped with genes enriched in excitatory and inhibitory neurons, specifically, gene enrichments related to synaptic transmission and neuron projection. Our findings suggest a valuable insight into understanding BMI-related alterations in brain network routing mechanisms and the potential underlying cellular biology, which might be used as a foundation for BMI-based weight management.

Overexpression of REC8 induces aberrant gamete meiotic division and contributes to AML pathogenesis - a multiplexed microarray analysis and mendelian randomization study

Acute myeloid leukemia (AML) is a notably lethal disease, characterized by malignant clonal proliferation of hematopoietic stem cells in the bone marrow. This study seeks to unveil potential therapeutic targets for AML, using a combined approach of microarray analysis and Mendelian randomization (MR). We collected data samples from the Gene Expression Omnibus (GEO) database and extracted pQTL data from genome-wide association studies (GWAS) to identify overlapping genes between the DEGs and GWAS data. Gene enrichment and pathway annotation analyses were performed on these genes. Furthermore, we validated gene expression levels and assessed their clinical relevance. By taking the intersection of these gene sets, we obtained a list of co-expressed genes, including four upregulated genes (REC8, TPM2, ZMIZ1, CD82) and two downregulated genes (IFNAR1, TMCO3). MR analysis demonstrated that genetically predicted protein levels of CD82, REC8, ZMIZ1, and TPM2 were significantly associated with increased odds of AML, while IFNAR1 and TMCO3 showed a protective effect. Gene ontology and KEGG pathway analyses revealed significant enrichment in functions related to female gamete generation, meiosis, p53 signaling pathway, and cardiac muscle contraction. Differences in immune cell profiles were observed between AML survivors and those with poor prognosis, including lower levels of neutrophils and higher levels of follicular helper T cells in the latter group. This study identifies a causal relationship between gene expression and AML and highlights the potential role of REC8 in leukemogenesis, possibly through its impact on gametocyte meiotic abnormalities. The findings provide new insights into the prevention and treatment of leukemia.

Decoding functional proteome information in model organisms using protein language models

Protein language models have been tested and proved to be reliable when used on curated datasets but have not yet been applied to full proteomes. Accordingly, we tested how two different machine learning-based methods performed when decoding functional information from the proteomes of selected model organisms. We found that protein language models are more precise and informative than deep learning methods for all the species tested and across the three gene ontologies studied, and that they better recover functional information from transcriptomic experiments. The results obtained indicate that these language models are likely to be suitable for large-scale annotation and downstream analyses, and we recommend a guide for their use.

Pseudomonas protegens volatile organic compounds inhibited brown rot of postharvest peach fruit by repressing the pathogenesis-related genes in Monilinia fructicola

Brown rot, caused by Monilinia fructicola, is considered one of the devasting diseases of pre-harvest and post-harvest peach fruits, restricting the yield and quality of peach fruits and causing great economic losses to the peach industry every year. Presently, the management of the disease relies heavily on chemical control. In the study, we demonstrated that the volatile organic compounds (VOCs) of endophyte bacterial Pseudomonas protegens QNF1 inhibited the mycelial growth of M. fructicola by 95.35% compared to the control, thereby reducing the brown rot on postharvest fruits by 98.76%. Additionally, QNF1 VOCs severely damaged the mycelia of M. fructicola. RNA-seq analysis revealed that QNF1 VOCs significantly repressed the expressions of most of the genes related to pathogenesis (GO:0009405) and integral component of plasma membrane (GO:0005887), and further analysis revealed that QNF1 VOCs significantly altered the expressions of the genes involved in various metabolism pathways including Amino acid metabolism, Carbohydrate metabolism, and Lipid metabolism. The findings of the study indicated that QNF1 VOCs displayed substantial control efficacy by disrupting the mycelial morphology of M. fructicola, weakening its pathogenesis, and causing its metabolic disorders. The study provided a potential way and theoretical support for the management of the brown rot of peach fruits.

Moxibustion ameliorates ovarian function in premature ovarian insufficiency rats by activating cAMP/PKA/CREB to promote steroidogenesis in ovarian granulosa cells

Premature ovarian insufficiency (POI) presents a substantial challenge to women's physiological and psychological well-being. Hormone replacement therapy, as the preferred therapeutic approach, involves solely exogenous supplementation of estrogen. Moxibustion, a traditional Chinese external treatment, has been investigated in our previous studies. It not only improves hormone levels and clinical symptoms in POI patients but also safeguards ovarian reserve. This study aims to explore the regulatory mechanisms by which moxibustion modulates hormone levels and restores ovarian function in POI. A POI rat model was established using cyclophosphamide, and moxibustion treatment was applied at acupoints "CV4" and "SP6" for a total of four courses. Subsequently, ovaries from each group were subjected to transcriptome sequencing (Bulk RNA-seq). Target pathways and key genes were selected through enrichment analysis and GSVA scoring, with validation using various techniques including electron microscopy, ELISA, Western blot, and immunohistochemistry. The results demonstrated that moxibustion restored the estrous cycle in POI rats, improved sex hormone levels, reduced the number of atretic follicles, and increased the count of dominant follicles (P<0.05). Bulk RNA-seq analysis revealed that moxibustion downregulated pathways associated with ovarian dysfunction, infertility, and immune responses, upregulated pathways related to follicular development and ovarian steroidogenesis. Furthermore, our data confirmed that moxibustion significantly increased the number of ovarian granulosa cells (GCs) and upregulated the expression of proteins related to steroidogenesis in GCs, including FSHR, P450 arom, cAMP, PKA, and CREB (P<0.05), with no significant effect observed on proteins related to steroidogenesis in theca cells. These outcomes aligned with the RNA-seq results. In conclusion, these findings propose that moxibustion enhances steroidogenesis in GCs through the activation of the cAMP/PKA/CREB pathway, consequently improving impaired ovarian function in POI rats. This study provides robust evidence supporting moxibustion as a targeted intervention for treating POI by specifically regulating steroidogenesis in GCs.

Pleiotropy, epistasis and the genetic architecture of quantitative traits

Pleiotropy (whereby one genetic polymorphism affects multiple traits) and epistasis (whereby non-linear interactions between genetic polymorphisms affect the same trait) are fundamental aspects of the genetic architecture of quantitative traits. Recent advances in the ability to characterize the effects of polymorphic variants on molecular and organismal phenotypes in human and model organism populations have revealed the prevalence of pleiotropy and unexpected shared molecular genetic bases among quantitative traits, including diseases. By contrast, epistasis is common between polymorphic loci associated with quantitative traits in model organisms, such that alleles at one locus have different effects in different genetic backgrounds, but is rarely observed for human quantitative traits and common diseases. Here, we review the concepts and recent inferences about pleiotropy and epistasis, and discuss factors that contribute to similarities and differences between the genetic architecture of quantitative traits in model organisms and humans.

Gandouling ameliorates liver injury in Wilson's disease through the inhibition of ferroptosis by regulating the HSF1/HSPB1 pathway

Ferroptosis, an iron-dependent form of cell death, plays a crucial role in the progression of liver injury in Wilson's disease (WD). Gandouling (GDL) has emerged as a potential therapeutic agent for preventing and treating liver injury in WD. However, the precise mechanisms by which GDL mitigates ferroptosis in WD liver injury remain unclear. In this study, we discovered that treating Toxic Milk (TX) mice with GDL effectively decreased liver copper content, corrected iron homeostasis imbalances, and lowered lipid peroxidation levels, thereby preventing ferroptosis and improving liver injury. Bioinformatics analysis and machine learning algorithms identified Hspb1 as a pivotal regulator of ferroptosis. GDL treatment significantly upregulated the expression of HSPB1 and its upstream regulatory factor HSF1, thereby activating the HSF1/HSPB1 pathway. Importantly, inhibition of this pathway by NXP800 reversed the protective effects of GDL on ferroptosis in the liver of TX mice. In conclusion, GDL shows promise in alleviating liver injury in WD by inhibiting ferroptosis through modulation of the HSF1/HSPB1 pathway, suggesting its potential as a novel therapeutic agent for treating liver ferroptosis in WD.

Comprehensive pan-cancer analysis reveals EPHB2 is a novel predictive biomarker for prognosis and immunotherapy response

PURPOSE

Recent studies have increasingly linked Ephrin receptor B2 (EPHB2) to cancer progression. However, comprehensive investigations into the immunological roles and prognostic significance of EPHB2 across various cancers remain lacking.

METHODS

We employed various databases and bioinformatics tools to investigate the impact of EPHB2 on prognosis, immune infiltration, genome instability, and response to immunotherapy. Validation of the correlation between EPHB2 expression and M2 macrophages included analyses using bulk and single-cell transcriptomic datasets, spatial transcriptomics, and multi-fluorescence staining. Moreover, we performed cMap web tool to screen for EPHB2-targeted compounds and assessed their potential through molecular docking and dynamics simulations. Additionally, in vitro validation using lung adenocarcinoma (LUAD) cell lines was conducted to confirm the bioinformatics predictions about EPHB2.

RESULTS

EPHB2 dysregulation was observed across multiple cancer types, where it demonstrated significant diagnostic and prognostic value. Gene Set Enrichment Analysis (GSEA) indicated that EPHB2 is involved in enhancing cellular proliferation, invasiveness of cancer cells, and modulation of the anti-cancer immune response. Furthermore, it is emerged as a pan-cancer marker for M2 macrophage infiltration, supported by integrated analyses of transcriptomics and multiple fluorescence staining. In LUAD cells, knockdown of EPHB2 expression led to a decrease in both cell proliferation and migratory activity.

CONCLUSION

EPHB2 expression may serve as a pivotal indicator of M2 macrophage infiltration, offering vital insights into tumor dynamics and progression across various cancers, including lung adenocarcinoma, highlighting its significant prognostic and therapeutic potential for further exploration.

Comparative Morphological, Physiological, and Transcriptomic Analyses of Diploid and Tetraploid Wucai (Brassica campestris L.)

Polyploid plants often exhibit superior yield, stress resistance, and quality. In this study, homologous tetraploid wucai (Brassica campestris L.) was successfully obtained by spraying seedling growth points with colchicine. The morphological, cytological, and physiological characteristics of diploid and tetraploid wucai were analyzed, and transcriptomic sequencing was performed at three stages of development. Tetraploid seedings grew slowly but exhibited darker leaves, enlarged organs and cells, increased stomatal volume, decreased stomatal density, improved nutritional content, and enhanced photosynthesis. Differentially expressed genes (DEGs) identified in diploid and tetraploid plants at three stages of development were enriched in different pathways. Notably, DEGs identified in the tetraploid plants were specifically enriched in starch and sucrose metabolism, pentose and glucuronate interconversions, and ascorbate and aldarate metabolism. In addition, we found that the light green module was most relevant to ploidy, and DEGs in this module were significantly enriched in the glycolysis/gluconeogenesis and TCA cycle pathways. The differential expression of key glycolysis-associated genes at different developmental stages may be the driver of the observed differences between diploid and tetraploid wucai. This study lays a technical foundation for the development of polyploid wucai germplasm resources as well as the breeding of new varieties with improved quality, yield, and stress resistance. It also provides a good empirical reference for the genetic breeding of closely related Brassica species.

Unveiling FRG1's DNA repair role in breast cancer

The FRG1(FSHD region gene 1) gene has emerged as a pivotal tumor suppressor in both breast and prostate cancer. HPF1 (Histone PARylation Factor 1), a gene crucial in the base excision repair (BER) mechanism for single-stranded DNA (ssDNA) lesions, showcases a robust correlation with FRG1. This implies that FRG1 might have the capacity to influence BER via HPF1, potentially playing a role in tumorigenesis. Using a comprehensive approach that integrates in-silico analyses involving differential gene expression, KEGG (Kyoto Encyclopedia of Genes and Genomes), GO (Gene Ontology), and STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) databases, we unravelled the intricate network of genes and pathways influenced by FRG1, which includes BER. Our linear regression analysis unveiled a positive relationship between FRG1 and key genes crucial for BER. Notably, breast cancer patients with low FRG1 expression exhibited a significantly higher frequency of mutation in TP53. To enhance the accuracy of our analysis, we conducted qRT-PCR assays, which demonstrated that FRG1 affects the transcription of DNA base excision repair genes, showing differential expression in breast cancer cells. Moreover, through the Alkaline Comet Assay, a technique that quantifies DNA damage at the single-cell level, we observed diminished DNA repair capabilities when FRG1 levels are low. Risk scores were calculated using the Cox regression coefficients, and we found notable differences in Overall Survival (OS) and mRNA expression of DEGs in the low and high-risk groups. In summary, our findings shed light on the pivotal role of FRG1 in maintaining DNA repair efficiency within breast cancer cells.

Identification of key metabolism-related genes and pathways in spontaneous preterm birth: combining bioinformatic analysis and machine learning

Background

Spontaneous preterm birth (sPTB) is a global disease that is a leading cause of death in neonates and children younger than 5 years of age. However, the etiology of sPTB remains poorly understood. Recent evidence has shown a strong association between metabolic disorders and sPTB. To determine the metabolic alterations in sPTB patients, we used various bioinformatics methods to analyze the abnormal changes in metabolic pathways in the preterm placenta via existing datasets.

Methods

In this study, we integrated two datasets (GSE203507 and GSE174415) from the NCBI GEO database for the following analysis. We utilized the "Deseq2" R package and WGCNA for differentially expressed genes (DEGs) analysis; the identified DEGs were subsequently compared with metabolism-related genes. To identify the altered metabolism-related pathways and hub genes in sPTB patients, we performed multiple functional enrichment analysis and applied three machine learning algorithms, LASSO, SVM-RFE, and RF, with the hub genes that were verified by immunohistochemistry. Additionally, we conducted single-sample gene set enrichment analysis to assess immune infiltration in the placenta.

Results

We identified 228 sPTB-related DEGs that were enriched in pathways such as arachidonic acid and glutathione metabolism. A total of 3 metabolism-related hub genes, namely, ANPEP, CKMT1B, and PLA2G4A, were identified and validated in external datasets and experiments. A nomogram model was developed and evaluated with 3 hub genes; the model could reliably distinguish sPTB patients and term labor patients with an area under the curve (AUC) > 0.75 for both the training and validation sets. Immune infiltration analysis revealed immune dysregulation in sPTB patients.

Conclusion

Three potential hub genes that influence the occurrence of sPTB through shadow participation in placental metabolism were identified; these results provide a new perspective for the development and targeting of treatments for sPTB.

Role of sphingolipid metabolism signaling in a novel mouse model of renal osteodystrophy based on transcriptomic approach

BACKGROUND

Renal osteodystrophy (ROD) is a skeletal pathology associated with chronic kidney disease-mineral and bone disorder (CKD-MBD) that is characterized by aberrant bone mineralization and remodeling. ROD increases the risk of fracture and mortality in CKD patients. The underlying mechanisms of ROD remain elusive, partially due to the absence of an appropriate animal model. To address this gap, we established a stable mouse model of ROD using an optimized adenine-enriched diet and conducted exploratory analyses through ribonucleic acid sequencing (RNA-seq).

METHODS

Male 8-week-old C57BL/6J mice were randomly allocated into three groups: control group (n = 5), adenine and high-phosphate (HP) diet group (n = 20), and the optimized adenine-containing diet group (n = 20) for 12 weeks. We assessed the skeletal characteristics of model mice through blood biochemistry, microcomputed tomography (micro-CT), and bone histomorphometry. RNA-seq was utilized to profile gene expression changes of ROD. We elucidated the functions of differentially expressed genes (DEGs) using gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and gene set enrichment analysis (GSEA). DEGs were validated via quantitative real-time polymerase chain reaction (qRT-PCR).

RESULTS

By the fifth week, adenine followed by an HP diet induced rapid weight loss and high mortality rates in the mouse group, precluding further model development. Mice with optimized adenine diet-induced ROD displayed significant abnormalities in serum creatinine and blood urea nitrogen levels, accompanied by pronounced hyperparathyroidism and hyperphosphatemia. The femur bone mineral density (BMD) of the model mice was lower than that of control mice, with substantial bone loss and cortical porosity. ROD mice exhibited substantial bone turnover with an increase in osteoblast and osteoclast markers. Transcriptomic profiling revealed 1907 genes with upregulated expression and 723 genes with downregulated expression in the femurs of ROD mice relative to those of control mice. Pathway analyses indicated significant enrichment of upregulated genes in the sphingolipid metabolism pathway. The significant upregulation of alkaline ceramidase 1 (Acer1), alkaline ceramidase 2 (Acer2), prosaposin-like 1 (Psapl1), adenosine A1 receptor (Adora1), and sphingosine-1-phosphate receptor 5 (S1pr5) were successfully validated in mouse femurs by qRT-PCR.

CONCLUSIONS

Optimized adenine diet mouse model may be a valuable proxy for studying ROD. RNA-seq analysis revealed that the sphingolipid metabolism pathway is likely a key player in ROD pathogenesis, thereby providing new avenues for therapeutic intervention.

Transcriptional Modulation during Photomorphogenesis in Rice Seedlings

Light is one of the most important factors regulating plant gene expression patterns, metabolism, physiology, growth, and development. To explore how light may induce or alter transcript splicing, we conducted RNA-Seq-based transcriptome analyses by comparing the samples harvested as etiolated seedlings grown under continuous dark conditions vs. the light-treated green seedlings. The study aims to reveal differentially regulated protein-coding genes and novel long noncoding RNAs (lncRNAs), their light-induced alternative splicing, and their association with biological pathways. We identified 14,766 differentially expressed genes, of which 4369 genes showed alternative splicing. We observed that genes mapped to the plastid-localized methyl-erythritol-phosphate (MEP) pathway were light-upregulated compared to the cytosolic mevalonate (MVA) pathway genes. Many of these genes also undergo splicing. These pathways provide crucial metabolite precursors for the biosynthesis of secondary metabolic compounds needed for chloroplast biogenesis, the establishment of a successful photosynthetic apparatus, and photomorphogenesis. In the chromosome-wide survey of the light-induced transcriptome, we observed intron retention as the most predominant splicing event. In addition, we identified 1709 novel lncRNA transcripts in our transcriptome data. This study provides insights on light-regulated gene expression and alternative splicing in rice.

Novel CDKL5 targets identified in human iPSC-derived neurons

CDKL5 Deficiency Disorder (CDD) is a debilitating epileptic encephalopathy disorder affecting young children with no effective treatments. CDD is caused by pathogenic variants in Cyclin-Dependent Kinase-Like 5 (CDKL5), a protein kinase that regulates key phosphorylation events in neurons. For therapeutic intervention, it is essential to understand molecular pathways and phosphorylation targets of CDKL5. Using an unbiased phosphoproteomic approach we identified novel targets of CDKL5, including GTF2I, PPP1R35, GATAD2A and ZNF219 in human iPSC-derived neuronal cells. The phosphoserine residue in the target proteins lies in the CDKL5 consensus motif. We validated direct phosphorylation of GTF2I and PPP1R35 by CDKL5 using complementary approaches. GTF2I controls axon guidance, cell cycle and neurodevelopment by regulating expression of neuronal genes. PPP1R35 is critical for centriole elongation and cilia morphology, processes that are impaired in CDD. PPP1R35 interacts with CEP131, a known CDKL5 phospho-target. GATAD2A and ZNF219 belong to the Nucleosome Remodelling Deacetylase (NuRD) complex, which regulates neuronal activity-dependent genes and synaptic connectivity. In-depth knowledge of molecular pathways regulated by CDKL5 will allow a better understanding of druggable disease pathways to fast-track therapeutic development.

Complete genome sequence of Erwinia amylovora PBI209 isolated from a necrotic flower of Pyrus sinkiangensis in China

Here, we report the complete genome sequence of Erwinia amylovora PBI209 that causes fire blight isolated from a necrotic flower of Pyrus sinkiangensis in Xinjiang, China. The genome consists of 3,800,955 bp, with 3,403 protein-coding genes and a guanine-cytosine content of 53.61%.

Navigating the landscape of enzyme design: from molecular simulations to machine learning

Global environmental issues and sustainable development call for new technologies for fine chemical synthesis and waste valorization. Biocatalysis has attracted great attention as the alternative to the traditional organic synthesis. However, it is challenging to navigate the vast sequence space to identify those proteins with admirable biocatalytic functions. The recent development of deep-learning based structure prediction methods such as AlphaFold2 reinforced by different computational simulations or multiscale calculations has largely expanded the 3D structure databases and enabled structure-based design. While structure-based approaches shed light on site-specific enzyme engineering, they are not suitable for large-scale screening of potential biocatalysts. Effective utilization of big data using machine learning techniques opens up a new era for accelerated predictions. Here, we review the approaches and applications of structure-based and machine-learning guided enzyme design. We also provide our view on the challenges and perspectives on effectively employing enzyme design approaches integrating traditional molecular simulations and machine learning, and the importance of database construction and algorithm development in attaining predictive ML models to explore the sequence fitness landscape for the design of admirable biocatalysts.

Shirebi granules ameliorate acute gouty arthritis by inhibiting NETs-induced imbalance between immunity and inflammation

BACKGROUND

Acute gouty arthritis (AGA) is classified as 'arthritis' in traditional Chinese medicine (TCM) theory. Shirebi granules (SGs), derived from the classic prescription SiMiaoWan, exerts satisfying therapeutic efficacy in ameliorating AGA clinically. However, the underlying mechanisms of SGs against AGA remain unclarified.

METHODS

AGA-related biological processes, signal pathways and biomarker genes were mined from the GEO database through bioinformatics. SGs components were systematically recognized using the UPLC-Q-TOF-MS/MS. A correlation network was established based on the biomarker genes and the chemical components, from which the signal pathway used for further study was selected. Finally, we established an AGA model using SD rats injected with monosodium urate (MSU) in the ankle joint for experimental validation. A combination of behavioral tests, H&E, safranin O- fast green, western blotting, and immunofluorescence were employed to reveal the mechanism of action of SGs on AGA.

RESULTS

The deterioration of AGA was significantly related to the imbalance between immunity and inflammation, neutrophil chemotaxis and inflammatory factor activation. HDAC5, PRKCB, NFκB1, MPO, PRKCA, PIK3CA were identified to be the candidate targets of SGs against AGA, associated with neutrophil extracellular traps (NETs) signal pathway. Animal experiments demonstrated that SGs effectively repaired cartilage damage, blocked TLR4 activation, and inhibited the expression of NETs indicators and inflammatory factors. In addition, SGs prominently alleviated joint redness and swelling, improved joint dysfunction, inhibited inflammatory infiltration of AGA rats.

CONCLUSION

Our data reveal that SGs may effectively alleviate the disease severity of AGA by suppressing NETs-promoted imbalance between immunity and inflammation.

The overview of the BioRED (Biomedical Relation Extraction Dataset) track at BioCreative VIII

The BioRED track at BioCreative VIII calls for a community effort to identify, semantically categorize, and highlight the novelty factor of the relationships between biomedical entities in unstructured text. Relation extraction is crucial for many biomedical natural language processing (NLP) applications, from drug discovery to custom medical solutions. The BioRED track simulates a real-world application of biomedical relationship extraction, and as such, considers multiple biomedical entity types, normalized to their specific corresponding database identifiers, as well as defines relationships between them in the documents. The challenge consisted of two subtasks: (i) in Subtask 1, participants were given the article text and human expert annotated entities, and were asked to extract the relation pairs, identify their semantic type and the novelty factor, and (ii) in Subtask 2, participants were given only the article text, and were asked to build an end-to-end system that could identify and categorize the relationships and their novelty. We received a total of 94 submissions from 14 teams worldwide. The highest F-score performances achieved for the Subtask 1 were: 77.17% for relation pair identification, 58.95% for relation type identification, 59.22% for novelty identification, and 44.55% when evaluating all of the above aspects of the comprehensive relation extraction. The highest F-score performances achieved for the Subtask 2 were: 55.84% for relation pair, 43.03% for relation type, 42.74% for novelty, and 32.75% for comprehensive relation extraction. The entire BioRED track dataset and other challenge materials are available at https://ftp.ncbi.nlm.nih.gov/pub/lu/BC8-BioRED-track/ and https://codalab.lisn.upsaclay.fr/competitions/13377 and https://codalab.lisn.upsaclay.fr/competitions/13378. Database URL: https://ftp.ncbi.nlm.nih.gov/pub/lu/BC8-BioRED-track/https://codalab.lisn.upsaclay.fr/competitions/13377https://codalab.lisn.upsaclay.fr/competitions/13378.

A novel mitochondria-related algorithm for predicting the survival outcomes and drug sensitivity of patients with lung adenocarcinoma

Background

Mitochondria have always been considered too be closely related to the occurrence and development of malignant tumors. However, the bioinformatic analysis of mitochondria in lung adenocarcinoma (LUAD) has not been reported yet.

Methods

In the present study, we constructed a novel and reliable algorithm, comprising a consensus cluster analysis and risk assessment model, to predict the survival outcomes and tumor immunity for patients with terminal LUAD.

Results

Patients with LUAD were classified into three clusters, and patients in cluster 1 exhibited the best survival outcomes. The patients in cluster 3 had the highest expression of PDL1 (encoding programmed cell death 1 ligand 11) and HAVCR2 (encoding Hepatitis A virus cellular receptor 2), and the highest tumor mutation burden (TMB). In the risk assessment model, patients in the low-risk group tended to have a significantly better survival outcome. Furthermore, the risk score combined with stage could act as a reliable independent prognostic indicator for patients with LUAD. The prognostic signature is a novel and effective biomarker to select anti-tumor drugs. Low-risk patients tended to have a higher expression of CTLA4 (encoding cytotoxic T-lymphocyte associated protein 4) and HAVCR2. Moreover, patients in the high-risk group were more sensitive to Cisplatin, Docetaxel, Erlotinib, Gemcitabine, and Paclitaxel, while low-risk patients would probably benefit more from Gefitinib.

Conclusion

We constructed a novel and reliable algorithm comprising a consensus cluster analysis and risk assessment model to predict survival outcomes, which functions as a reliable guideline for anti-tumor drug treatment for patients with terminal LUAD.

The life-saving benefit of dexamethasone in severe COVID-19 is linked to a reversal of monocyte dysregulation

Dexamethasone is a life-saving treatment for severe COVID-19, yet its mechanism of action is unknown, and many patients deteriorate or die despite timely treatment initiation. Here, we identify dexamethasone treatment-induced cellular and molecular changes associated with improved survival in COVID-19 patients. We observed a reversal of transcriptional hallmark signatures in monocytes associated with severe COVID-19 and the induction of a monocyte substate characterized by the expression of glucocorticoid-response genes. These molecular responses to dexamethasone were detected in circulating and pulmonary monocytes, and they were directly linked to survival. Monocyte single-cell RNA sequencing (scRNA-seq)-derived signatures were enriched in whole blood transcriptomes of patients with fatal outcome in two independent cohorts, highlighting the potential for identifying non-responders refractory to dexamethasone. Our findings link the effects of dexamethasone to specific immunomodulation and reversal of monocyte dysregulation, and they highlight the potential of single-cell omics for monitoring in vivo target engagement of immunomodulatory drugs and for patient stratification for precision medicine approaches.

GWAS-significant loci and severe COVID-19: analysis of associations, link with thromboinflammation syndrome, gene-gene, and gene-environmental interactions

Objective

The aim of this study was to replicate associations of GWAS-significant loci with severe COVID-19 in the population of Central Russia, to investigate associations of the SNPs with thromboinflammation parameters, to analyze gene-gene and gene-environmental interactions.

Materials and Methods

DNA samples from 798 unrelated Caucasian subjects from Central Russia (199 hospitalized COVID-19 patients and 599 controls with a mild or asymptomatic course of COVID-19) were genotyped using probe-based polymerase chain reaction for 10 GWAS-significant SNPs: rs143334143 CCHCR1, rs111837807 CCHCR1, rs17078346 SLC6A20-LLZTFL1, rs17713054 SLC6A20-LLZTFL1, rs7949972 ELF5, rs61882275 ELF5, rs12585036 ATP11A, rs67579710 THBS3, THBS3-AS1, rs12610495 DPP9, rs9636867 IFNAR2.

Results

SNP rs17713054 SLC6A20-LZTFL1 was associated with increased risk of severe COVID-19 in the entire group (risk allele A, OR = 1.78, 95% CI = 1.22-2.6, p = 0.003), obese individuals (OR = 2.31, 95% CI = 1.52-3.5, p = 0.0002, (p bonf = 0.0004)), patients with low fruit and vegetable intake (OR = 1.72, 95% CI = 1.15-2.58, p = 0.01, (p bonf = 0.02)), low physical activity (OR = 1.93, 95% CI = 1.26-2.94, p = 0.0035, (p bonf = 0.007)), and nonsmokers (OR = 1.65, 95% CI = 1.11-2.46, p = 0.02). This SNP correlated with increased BMI (p = 0.006) and worsened thrombodynamic parameters (maximum optical density of the formed clot, D (p = 0.02), delayed appearance of spontaneous clots, Tsp (p = 0.02), clot size 30 min after coagulation activation, CS (p = 0.036)). SNP rs17078346 SLC6A20-LZTFL1 was linked with increased BMI (p = 0.01) and severe COVID-19 in obese individuals (risk allele C, OR = 1.72, 95% CI = 1.15-2.58, p = 0.01, (p bonf = 0.02)). SNP rs12610495 DPP9 was associated with increased BMI (p = 0.01), severe COVID-19 in obese patients (risk allele G, OR = 1.48, 95% CI = 1.09-2.01, p = 0.01, (p bonf = 0.02)), and worsened thrombodynamic parameters (time to the start of clot growth, Tlag (p = 0.01)). For rs7949972 ELF5, a protective effect against severe COVID-19 was observed in non-obese patients (effect allele T, OR = 0.67, 95% CI = 0.47-0.95, p = 0.02, (p bonf = 0.04)), improving thrombodynamic parameters (CS (p = 0.02), stationary spatial clot growth rates, Vst (p = 0.02)). Finally, rs12585036 ATP11A exhibited a protective effect against severe COVID-19 in males (protective allele A, OR = 0.51, 95% CI = 0.32-0.83, p = 0.004). SNPs rs67579710 THBS3, THBS3-AS1, rs17713054 SLC6A20-LZTFL1, rs7949972 ELF5, rs9636867 IFNAR2-were involved in two or more of the most significant G×G interactions (p perm ≤ 0.01). The pairwise combination rs67579710 THBS3, THBS3-AS1 × rs17713054 SLC6A20-LZTFL1 was a priority in determining susceptibility to severe COVID-19 (it was included in four of the top five most significant SNP-SNP interaction models).

Conclusion

Overall, this study represents a comprehensive molecular-genetic and bioinformatics analysis of the involvement of GWAS-significant loci in the molecular mechanisms of severe COVID-19, gene-gene and gene-environmental interactions, and provides evidence of their relationship with thromboinflammation parameters in patients hospitalized in intensive care units.

Male autism spectrum disorder is linked to brain aromatase disruption by prenatal BPA in multimodal investigations and 10HDA ameliorates the related mouse phenotype

Male sex, early life chemical exposure and the brain aromatase enzyme have been implicated in autism spectrum disorder (ASD). In the Barwon Infant Study birth cohort (n = 1074), higher prenatal maternal bisphenol A (BPA) levels are associated with higher ASD symptoms at age 2 and diagnosis at age 9 only in males with low aromatase genetic pathway activity scores. Higher prenatal BPA levels are predictive of higher cord blood methylation across the CYP19A1 brain promoter I.f region (P = 0.009) and aromatase gene methylation mediates (P = 0.01) the link between higher prenatal BPA and brain-derived neurotrophic factor methylation, with independent cohort replication. BPA suppressed aromatase expression in vitro and in vivo. Male mice exposed to mid-gestation BPA or with aromatase knockout have ASD-like behaviors with structural and functional brain changes. 10-hydroxy-2-decenoic acid (10HDA), an estrogenic fatty acid alleviated these features and reversed detrimental neurodevelopmental gene expression. Here we demonstrate that prenatal BPA exposure is associated with impaired brain aromatase function and ASD-related behaviors and brain abnormalities in males that may be reversible through postnatal 10HDA intervention.

RBPs: an RNA editor's choice

RNA-binding proteins (RBPs) play a key role in gene expression and post-transcriptional RNA regulation. As integral components of ribonucleoprotein complexes, RBPs are susceptible to genomic and RNA Editing derived amino acid substitutions, impacting functional interactions. This article explores the prevalent RNA Editing of RBPs, unravelling the complex interplay between RBPs and RNA Editing events. Emphasis is placed on their influence on single amino acid variants (SAAVs) and implications for disease development. The role of Proteogenomics in identifying SAAVs is briefly discussed, offering insights into the RBP landscape. RNA Editing within RBPs emerges as a promising target for precision medicine, reshaping our understanding of genetic and epigenetic variations in health and disease.

Development and validation of a hypoxia- and mitochondrial dysfunction- related prognostic model based on integrated single-cell and bulk RNA sequencing analyses in gastric cancer

Introduction

Gastric cancer (GC) remains a major global health threat ranking as the fifth most prevalent cancer. Hypoxia, a characteristic feature of solid tumors, significantly contributes to the malignant progression of GC. Mitochondria are the major target of hypoxic injury that promotes mitochondrial dysfunction during the development of cancers including GC. However, the gene signature and prognostic model based on hypoxia- and mitochondrial dysfunction-related genes (HMDRGs) in the prediction of GC prognosis have not yet been established.

Methods

The gene expression profile datasets of stomach cancer patients were retrieved from The Cancer Genome Atlas and the Gene Expression Omnibus databases. Prognostic genes were selected using Least Absolute Shrinkage and Selection Operator Cox (LASSO-Cox) regression analysis to construct a prognostic model. Immune infiltration was evaluated through ESTIMATE, CIBERSORT, and ssGSEA analyses. Tumor immune dysfunction and exclusion (TIDE) and immunophenoscore (IPS) were utilized to explore implications for immunotherapy. Furthermore, in vitro experiments were conducted to validate the functional roles of HMDRGs in GC cell malignancy.

Results

In this study, five HMDRGs (ZFP36, SERPINE1, DUSP1, CAV1, and AKAP12) were identified for developing a prognostic model in GC. This model stratifies GC patients into high- and low-risk groups based on median risk scores. A nomogram predicting overall survival (OS) was constructed and showed consistent results with observed OS. Immune infiltration analysis indicated that individuals in the high-risk group tend to exhibit increased immune cell infiltration. Additionally, analysis of cancer immunotherapy responses revealed that high-risk group patients exhibit poorer responses to cancer immunotherapy compared to the low-risk group. Immunohistochemistry (IHC) staining indicated that the expression levels of HMDRGs were remarkably correlated with GC, of which, SERPINE1 displayed the most pronounced up-regulation, while ZFP36 exhibited the most notable down-regulation in GC patients. Furthermore, in vitro investigation validated that SERPINE1 and ZFP36 contribute to the malignant processes of GC cells correlated with mitochondrial dysfunction.

Conclusions

This study presents a novel and efficient approach to evaluate GC prognosis and immunotherapy efficacy, and also provides insights into understanding the pathogenesis of GC.

Hallmarks of cancer in patients with heart failure: data from BIOSTAT-CHF

BACKGROUND

Within cardio-oncology, emerging epidemiologic studies have demonstrated a bi-directional relationship between heart failure (HF) and cancer. In the current study, we aimed to further explore this relationship and investigate the underlying pathophysiological pathways that connect these two disease entities.

METHODS

We conducted a post-hoc analysis in which we identified 24 Gene Ontology (GO) processes associated with the hallmarks of cancer based on 92 biomarkers in 1960 patients with HF. We performed Spearman's correlations and Cox-regression analyses to evaluate associations with HF biomarkers, severity and all-cause mortality.

RESULTS

Out of a total of 24 GO processes, 9 biological processes were significantly associated with adverse clinical outcome. Positive regulation of mononuclear cell proliferation demonstrated the highest hazard for reaching the clinical endpoint, even after adjusting for confounders: all-cause mortality HR 2.00 (95% CI 1.17-3.42), p = 0.012. In contrast, negative regulation of apoptotic process was consistently associated with a lower hazard of reaching the clinical outcome, even after adjusting for confounders: all-cause mortality HR 0.74 (95% CI 0.59-0.95), p = 0.016. All processes significantly correlated with HF biomarkers, renal function and HF severity.

CONCLUSIONS

In patients with HF, GO processes associated with hallmarks of cancer are associated with HF biomarkers, severity and all-cause mortality.

A microglia clonal inflammatory disorder in Alzheimer's Disease

Somatic genetic heterogeneity resulting from post-zygotic DNA mutations is widespread in human tissues and can cause diseases, however few studies have investigated its role in neurodegenerative processes such as Alzheimer's Disease (AD). Here we report the selective enrichment of microglia clones carrying pathogenic variants, that are not present in neuronal, glia/stromal cells, or blood, from patients with AD in comparison to age-matched controls. Notably, microglia-specific AD-associated variants preferentially target the MAPK pathway, including recurrent CBL ring-domain mutations. These variants activate ERK and drive a microglia transcriptional program characterized by a strong neuro-inflammatory response, both in vitro and in patients. Although the natural history of AD-associated microglial clones is difficult to establish in human, microglial expression of a MAPK pathway activating variant was previously shown to cause neurodegeneration in mice, suggesting that AD-associated neuroinflammatory microglial clones may contribute to the neurodegenerative process in patients.

Atorvastatin lowers breast cancer risk by reversing an early tumorigenic signature

Breast cancer remains a significant health challenge with complex molecular mechanisms. While many studies have explored genetic markers in breast carcinogenesis, few have studied the potential impact of pharmacological interventions such as Atorvastatin on its genetic landscape. This study aimed to elucidate the molecular distinctions between normal and tumor-adjacent tissues in breast cancer and to investigate the potential protective role of atorvastatin, primarily known for its lipid-lowering effects, against breast cancer. Searching the Gene Expression Omnibus database identified two datasets, GSE9574 and GSE20437, comparing normal breast tissues with tumor-adjacent samples, which were merged, and one dataset, GSE63427, comparing paired pre- and post-treated patients with atorvastatin. Post-ComBat application showed merged datasets' consistency, revealing 116 DEGs between normal and tumor-adjacent tissues. Although initial GSE63427 data analysis suggested a minimal impact of atorvastatin, 105 DEGs post-treatment were discovered. Thirteen genes emerged as key players, both affected by Atorvastatin and dysregulated in tumor-adjacent tissues. Pathway analysis spotlighted the significance of these genes in processes like inflammation, oxidative stress, apoptosis, and cell cycle control. Moreover, there was a noticeable interaction between these genes and the immunological microenvironment in tumor-adjacent tissues, with Atorvastatin potentially altering the suppressive immune landscape to favor anti-tumor immunity. Survival analysis further highlighted the prognostic potential of the 13-gene panel, with 12 genes associated with improved survival outcomes. The 13-gene signature offers promising insights into breast cancer's molecular mechanisms and atorvastatin's potential therapeutic role. The preliminary findings advocate for an in-depth exploration of atorvastatin's impact on.

Spatial variation in genomic signatures of local adaptation during the cane toad invasion of Australia

Adaptive evolution can facilitate species' range expansions across environmentally heterogeneous landscapes. However, serial founder effects can limit the efficacy of selection, and the evolution of increased dispersal during range expansions may result in gene flow swamping local adaptation. Here, we study how genetic drift, gene flow and selection interact during the cane toad's (Rhinella marina) invasion across the heterogeneous landscape of Australia. Following its introduction in 1935, the cane toad colonised eastern Australia and established several stable range edges. The ongoing, more rapid range expansion in north-central Australia has occurred concomitant with an evolved increase in dispersal capacity. Using reduced representation genomic data of Australian cane toads from the expansion front and from two areas of their established range, we test the hypothesis that high gene flow constrains local adaptation at the expansion front relative to established areas. Genetic analyses indicate the three study areas are genetically distinct but show similar levels of allelic richness, heterozygosity and inbreeding. Markedly higher gene flow or recency of colonisation at the expansion front have likely hindered local adaptation at the time of sampling, as indicated by reduced slopes of genetic-environment associations (GEAs) estimated using a novel application of geographically weighted regression that accounts for allele surfing; GEA slopes are significantly steeper in established parts of the range. Our work bolsters evidence supporting adaptation of invasive species post-introduction and adds novel evidence for differing strengths of evolutionary forces among geographic areas with different invasion histories.

Bulk and single-cell transcriptome profiling identify potential cellular targets of the long noncoding RNA Gas5 in renal fibrosis

The long noncoding RNA growth arrest-specific 5 (lncRNA Gas5) is implicated in various kidney diseases. In this study, we investigated the lncRNA Gas5 expression profile and its critical role as a potential biomarker in the progression of chronic kidney disease. Subsequently, we assessed the effect of lncRNA Gas5 deletion on renal fibrosis induced by unilateral ureteral obstruction (UUO). The results indicated that loss of lncRNA Gas5 exacerbates UUO-induced renal injury and extracellular matrix deposition. Notably, the deletion of lncRNA Gas5 had a similar effect on control mice. The fibrogenic phenotype observed in mice lacking lncRNA Gas5 correlates with peroxisome proliferator-activated receptor (PPAR) signaling pathway activation and aberrant cytokine and chemokine reprogramming. Single-cell RNA sequencing analysis revealed key transcriptomic features of fibroblasts after Gas5 deletion, revealing heterogeneous cellular states suggestive of a propensity for renal fibrosis. Our findings indicate that lncRNA Gas5 regulates the differentiation and activation of immune cells and the transcription of key genes in the PPAR signaling pathway. These data offer novel insights into the involvement of lncRNA Gas5 in renal fibrosis, potentially paving the way for innovative diagnostic and therapeutic targets.

Neuroprotective Effect and Mechanism of Tanreqing Injection on Ischemic Stroke: Insights from Network Pharmacology and in vivo Experiments

OBJECTIVE

To explore the neuroprotective effects and mechanism of Tanreqing Injection (TRQ) on treating ischemic stroke based on network pharmacology and in vivo experimental validation.

METHODS

The chemical compounds of TRQ were retrieved based on published data, with targets retrieved from PubChem, Therapeutic Target Database and DrugBank. Network visualization and analysis were performed using Cytoscape, with protein-protein interaction networks derived from the STRING database. Enrichment analysis was performed using Kyoto Encyclopedia of Genes Genomes pathway and Gene Ontology analysis. In in vivo experiments, the middle cerebral artery occlusion (MCAO) model was used. Infarct volume was determined by 2,3,5-triphenyltetrazolium hydrochloride staining and protein expressions were analyzed by Western blot. Molecular docking was performed to predict ligand-receptor interactions.

RESULTS

We screened 81 chemical compounds in TRQ and retrieved their therapeutic targets. Of the targets, 116 were therapeutic targets for stroke. The enrichment analysis showed that the apelin signaling pathway was a key pathway for ischemic stroke. Furthermore, in in vivo experiment we found that administering with intraperitoneal injection of 2.5 mL/kg TRQ every 6 h could significantly reduce the infarct volume of MCAO rats (P<0.05). In addition, protein levels of the apelin receptor (APJ)/phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) pathway were increased by TRQ (P<0.05). In addition, 41 chemical compounds in TRQ could bind to APJ.

CONCLUSIONS

The neuroprotective effect of TRQ may be related to the APJ/PI3K/AKT signaling pathway. However, further studies are needed to confirm the findings.

Expression-environment associations in transcriptomic heat stress responses for a global plant lineage

The increasing frequency and severity of heatwaves will intensify stress on plants. Given regional variation in heatwave exposure and expected differences in thermal tolerance between species it is unlikely that all plant species will be affected equally by climate change. However, little is currently known about variation in the responses of plants to heat stress, or how those responses differ among closely related species adapted to different environments. Here we quantify the response of 17 Acacia species (175 RNA-seq libraries), from across Australia's diverse biomes, to a multi-day experimental heatwave treatment to identify variation in transcriptomic and physiological responses to heat stress. Genes with known heat response functions showed consistent responses across Acacia species. Up to 10% of all genes and over 100 gene families showed significant clinal variation in the magnitude of their expression plasticity across species. Specifically, gene families linked to the temperature stress response were overrepresented among significant relationships with home range temperature conditions. Gene expression responses seen on the first day of the heatwave were more frequently associated with home range climates, while expression responses by day four were more commonly related to photosystem II acclimation. Comparative transcriptomics on non-model species has the potential to provide key information on stress response plasticity, especially when linked with our understanding of model species. Our study indicates that the pressing challenge to identifying potentially vulnerable species to climate change could be benefited by the further exploration of clinal variation in transcriptome plasticity.

PLK1-activating IFI16-STING-TBK1 pathway induces apoptosis of intestinal epithelial cells in patients with intestinal Behçet's syndrome

Inflammatory signals from immunological cells may cause damage to intestinal epithelial cells (IECs), resulting in intestinal inflammation and tissue impairment. Interferon-γ-inducible protein 16 (IFI16) was reported to be involved in the pathogenesis of Behçet's syndrome (BS). This study aimed to investigate how inflammatory cytokines released by immunological cells and IFI16 participate in the pathogenesis of intestinal BS. RNA sequencing and real-time quantitative PCR (qPCR) showed that the positive regulation of tumor necrosis factor-α (TNF-α) production in peripheral blood mononuclear cells (PBMCs) of intestinal BS patients may be related to the upregulation of polo like kinase 1 (PLK1) in PBMCs (P = 0.012). The plasma TNF-α protein level in intestinal BS was significantly higher than in healthy controls (HCs; P = 0.009). PBMCs of intestinal BS patients and HCs were co-cultured with human normal IECs (NCM460) to explore the interaction between immunological cells and IECs. Using IFI16 knockdown, PBMC-NCM460 co-culture, TNF-α neutralizing monoclonal antibody (mAb), stimulator of interferon genes (STING) agonist 2'3'-cGAMP, and the PLK1 inhibitor SBE 13 HCL, we found that PLK1 promotes the secretion of TNF-α from PBMCs of intestinal BS patients, which causes overexpression of IFI16 and induces apoptosis of IECs via the STING-TBK1 pathway. The expressions of IFI16, TNF-α, cleaved caspase 3, phosphorylated STING (pSTING) and phosphorylated tank binding kinase 1 (pTBK1) in the intestinal ulcer tissue of BS patients were significantly higher than that of HCs (all P < 0.05). PLK1 in PBMCs of intestinal BS patients increased TNF-α secretion, inducing IEC apoptosis via activation of the IFI16-STING-TBK1 pathway. PLK1 and the IFI16-STING-TBK1 pathway may be new therapeutic targets for intestinal BS.

Low-level brain somatic mutations in exonic regions are collectively implicated in autism with germline mutations in autism risk genes

Low-level somatic mutations in the human brain are implicated in various neurological disorders. The contribution of low-level brain somatic mutations to autism spectrum disorder (ASD), however, remains poorly understood. Here, we performed high-depth exome sequencing with an average read depth of 559.3x in 181 cortical, cerebellar, and peripheral tissue samples to identify brain somatic single nucleotide variants (SNVs) in 24 ASD subjects and 31 controls. We detected ~2.4 brain somatic SNVs per exome per single brain region, with a variant allele frequency (VAF) as low as 0.3%. The mutational profiles, including the number, signature, and type, were not significantly different between the ASD patients and controls. Intriguingly, when considering genes with low-level brain somatic SNVs and ASD risk genes with damaging germline SNVs together, the merged set of genes carrying either somatic or germline SNVs in ASD patients was significantly involved in ASD-associated pathophysiology, including dendrite spine morphogenesis (p = 0.025), mental retardation (p = 0.012), and intrauterine growth retardation (p = 0.012). Additionally, the merged gene set showed ASD-associated spatiotemporal expression in the early and mid-fetal cortex, striatum, and thalamus (all p < 0.05). Patients with damaging mutations in the merged gene set had a greater ASD risk than did controls (odds ratio = 3.92, p = 0.025, 95% confidence interval = 1.12-14.79). The findings of this study suggest that brain somatic SNVs and germline SNVs may collectively contribute to ASD-associated pathophysiology.

Transcriptomic analysis for the gamma-ray-induced sweetpotato mutants with altered stem growth pattern

Introduction

Sweetpotato faces breeding challenges due to physiological and genomic issues. Gamma radiation is a novel approach for inducing genetic variation in crops. We analyzed the transcriptomic changes in gamma ray-induced sweetpotato mutants with altered stem development compared with those in the wild-type 'Tongchaeru' cultivar.

Methods

RNA sequencing analyses were performed to identify changes in the expression of genes related to stem development.

Results

Transcriptomic analysis identified 8,931 upregulated and 6,901 downregulated genes, including the upregulation of the auxin-responsive SMALL AUXIN UP RNA (SAUR) and three PHYTOCHROME INTERACTING FACTOR 4 (PIF4) genes. PIF4 is crucial for regulating the expression of early auxin-responsive SAUR genes and stem growth in Arabidopsis thaliana. In the mutant, several genes related to stem elongation, including PIF4 and those involved in various signaling pathways such as auxin and gibberellin, were upregulated.

Discussion

Our results suggest that gamma ray-induced mutations influence auxin-dependent stem development by modulating a complex regulatory network involving the expression of PIF4 and SAUR genes, and other signaling pathways such as gibberellin and ethylene signaling genes. This study enhances our understanding of the regulatory mechanisms underlying stem growth in sweetpotato, providing valuable insights for genomics-assisted breeding efforts.

Identification of macrophage differentiation related genes and subtypes linking atherosclerosis plaque processing and metabolic syndrome via integrated bulk and single-cell sequence analysis

Metabolic syndrome(MS) is a separate risk factor for the advancement of atherosclerosis(AS) plaque but mechanism behind this remains unclear. There may be a significant role for the immune system in this process. This study aims to identify potential diagnostic genes in MS patients at a higher risk of developing and progressing to AS. Datasets were retrevied from gene expression omnibus(GEO) database and differentially expressed genes were identified. Hub genes, immune cell dysregulation and AS subtypes were identified using a conbination of muliple bioinformatic analysis, machine learning and consensus clustering. Diagnostic value of hub genes was estimated using a nomogram and ROC analysis. Finally, enrichment analysis, competing endogenous RNA(ceRNA) network, single-cell RNA(scRNA) sequencing analysis and drug-protein interaction prediction was constructed to identify the functional roles, potential regulators and distribution for hub genes. Four hub genes and two macrophage-related subtypes were identified. Their strong diagnostic value was validated and functional process were identified. ScRNA analysis identified the macrophage differentiation regulation function of F13A1. CeRNA network and drug-protein binding modes revealed the potential therapeutic method. Four immune-correlated hub genes(F13A1, MMRN1, SLCO2A1 and ZNF521) were identified with their diagnostic value being assesed, which F13A1 was found strong correlated with macrophage differentiation and could be potential diagnostic and therapeutic marker for AS progression in MS patients.

Advances in Parkinson's disease research - A computational network pharmacological approach

Parkinson's disease (PD), the second most prevalent neurodegenerative disorder, is projected to see a significant rise in incidence over the next three decades. The precise treatment of PD remains a formidable challenge, prompting ongoing research into early diagnostic methodologies. Network pharmacology, a burgeoning field grounded in systems biology, examines the intricate networks of biological systems to identify critical signal nodes, facilitating the development of multi-target therapeutic molecules. This approach systematically maps the components of Parkinson's disease, thereby reducing its complexity. In this review, we explore the application of network pharmacology workflows in PD, discuss the techniques employed in this field, and evaluate the current advancements and status of network pharmacology in the context of Parkinson's disease. The comprehensive insights will pave newer paths to explore early disease biomarkers and to develop diagnosis with a holistic in silico, in vitro, in vivo and clinical studies.

Protein signatures associated with loneliness and social isolation: plasma proteome analyses in the English Longitudinal Study of Ageing, with causal evidence from Mendelian randomization

The understanding of biological pathways related to loneliness and social isolation remains incomplete. Cutting-edge population-based proteomics offers opportunities to uncover novel biological pathways linked to social deficits. This study employed a proteome-wide and data-driven approach to estimate the cross-sectional associations between objective measures of social connections (i.e., social isolation) and subjective measures (i.e., loneliness) with protein abundance, using the English Longitudinal Study of Ageing. Greater social isolation was associated with higher levels of 11 proteins (TNFRSF10A, MMP12, TRAIL-R2, SKR3, TNFRSF11A, VSIG2, PRSS8, FGFR2, KIM1, REN, and NEFL) after minimal adjustments; and three proteins were significantly associated after full adjustments (TNFRSF10A, TNFRSF11A, and HAOX1). Findings from two-sample Mendelian randomization indicated that a lower frequency of in-person social contact with friends or family causally increased levels of TNFRSF10A, TRAIL-R2, TNFRSF11A, and KIM1, and decreased the level of NEFL. The study also highlighted several enriched biological pathways, including necrosis and cell death regulation, dimerization of procaspase-8, and inhibition of caspase-8 pathways, which have previously not been linked to social deficits. These findings could help explain the relationship between social deficits and disease, confirming the importance of continuing to explore novel biological pathways associated with social deficits.