Sclerotinia sclerotiorum (Ss) is one of the most devastating fungal pathogens, causing huge yield loss in multiple economically important crops including oilseed rape. Plant resistance to Ss pertains to quantitative disease resistance (QDR) controlled by multiple minor genes. Genome-wide identification of genes involved in QDR to Ss is yet to be conducted. In this study, we integrated several assays including genome-wide association study (GWAS), multi-omics co-localization, and machine learning prediction to identify, on a genome-wide scale, genes involved in the oilseed rape QDR to Ss. Employing GWAS and multi-omics co-localization, we identified seven resistance-associated loci (RALs) associated with oilseed rape resistance to Ss. Furthermore, we developed a machine learning algorithm and named it Integrative Multi-Omics Analysis and Machine Learning for Target Gene Prediction (iMAP), which integrates multi-omics data to rapidly predict disease resistance-related genes within a broad chromosomal region. Through iMAP based on the identified RALs, we revealed multiple calcium signaling genes related to the QDR to Ss. Population-level analysis of selective sweeps and haplotypes of variants confirmed the positive selection of the predicted calcium signaling genes during evolution. Overall, this study has developed an algorithm that integrates multi-omics data and machine learning methods, providing a powerful tool for predicting target genes associated with specific traits. Furthermore, it makes a basis for further understanding the role and mechanisms of calcium signaling genes in the QDR to Ss.

OBJECTIVE: Heterogeneity in the rate of β-cell loss in newly diagnosed type 1 diabetes patients is poorly understood and creates a barrier to designing and interpreting disease-modifying clinical trials. Integrative analyses of baseline multi-omics data obtained after the diagnosis of type 1 diabetes may provide mechanistic insight into the diverse rates of disease progression after type 1 diabetes diagnosis.
METHODS: We collected samples in a pan-European consortium that enabled the concerted analysis of five different omics modalities in data from 97 newly diagnosed patients. In this study, we used Multi-Omics Factor Analysis to identify molecular signatures correlating with post-diagnosis decline in β-cell mass measured as fasting C-peptide.
RESULTS: Two molecular signatures were significantly correlated with fasting C-peptide levels. One signature showed a correlation to neutrophil degranulation, cytokine signalling, lymphoid and non-lymphoid cell interactions and G-protein coupled receptor signalling events that were inversely associated with a rapid decline in β-cell function. The second signature was related to translation and viral infection was inversely associated with change in β-cell function. In addition, the immunomics data revealed a Natural Killer cell signature associated with rapid β-cell decline.
CONCLUSIONS: Features that differ between individuals with slow and rapid decline in β-cell mass could be valuable in staging and prediction of the rate of disease progression and thus enable smarter (shorter and smaller) trial designs for disease modifying therapies as well as offering biomarkers of therapeutic effect.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is a metabolic disorder with severe comorbidities. A multiomics approach can facilitate the identification of novel therapeutic targets and biomarkers with proper validation of potential microRNA (miRNA) interactions.
OBJECTIVE: The aim of this study was to identify significant differentially expressed common target genes in various tissues and their regulating miRNAs from publicly available Gene Expression Omnibus (GEO) data sets of patients with T2DM using in silico analysis.
METHODS: Using differentially expressed genes (DEGs) identified from 5 publicly available T2DM data sets, we performed functional enrichment, coexpression, and network analyses to identify pathways, protein-protein interactions, and miRNA-mRNA interactions involved in T2DM.
RESULTS: We extracted 2852, 8631, 5501, 3662, and 3753 DEGs from the expression profiles of GEO data sets GSE38642, GSE25724, GSE20966, GSE26887, and GSE23343, respectively. DEG analysis showed that 16 common genes were enriched in insulin secretion, endocrine resistance, and other T2DM-related pathways. Four DEGs, MAML3, EEF1D, NRG1, and CDK5RAP2, were important in the cluster network regulated by commonly targeted miRNAs (hsa-let-7b-5p, hsa-mir-155-5p, hsa-mir-124-3p, hsa-mir-1-3p), which are involved in the advanced glycation end products (AGE)-receptor for advanced glycation end products (RAGE) signaling pathway, culminating in diabetic complications and endocrine resistance.
CONCLUSIONS: This study identified tissue-specific DEGs in T2DM, especially pertaining to the heart, liver, and pancreas. We identified a total of 16 common DEGs and the top four common targeting miRNAs (hsa-let-7b-5p, hsa-miR-124-3p, hsa-miR-1-3p, and has-miR-155-5p). The miRNAs identified are involved in regulating various pathways, including the phosphatidylinositol-3-kinase-protein kinase B, endocrine resistance, and AGE-RAGE signaling pathways.

BACKGROUND: Innate/adaptive immunity is the key to anti-tumor therapy. However, its causal relationship to Gastrointestinal (GI) cancer remains unclear.
METHODS: Immunity genes were extracted from the MSigDB database. The Genome-wide association studies (GWAS) summary data of GI cancer were integrated with expression quantitative trait loci (eQTL) and DNA methylation quantitative trait loci (mQTL) associated with genes. Summary-data-based Mendelian randomization (SMR) and co-localization analysis were used to reveal causal relationships between genes and GI cancer. Two-sample MR analysis was used for sensitivity analysis. Single cell analysis clarified the enrichment of genes.
RESULTS: Three-step SMR analysis showed that a putative mechanism, cg17294865 CpG site regulating HLA-DRA expression was negatively associated with gastric cancer risk. HLA-DRA was significantly differentially expressed in monocyte/macrophage and myeloid cells in gastric cancer.
CONCLUSIONS: This study provides evidence that upregulating the expression level of HLA-DRA can reduce the risk of gastric cancer.

Mitochondrial RNA modification (MRM) plays a crucial role in regulating the expression of key mitochondrial genes and promoting tumor metastasis. Despite its significance, comprehensive studies on MRM in lower grade gliomas (LGGs) remain unknown. Single-cell RNA-seq data (GSE89567) was used to evaluate the distribution functional status, and correlation of MRM-related genes in different cell types of LGG microenvironment. We developed an MRM scoring system by selecting potential MRM-related genes using LASSO regression analysis and the Random Survival Forest algorithm, based on multiple bulk RNA-seq datasets from TCGA, CGGA, GSE16011, and E-MTAB-3892. Analysis was performed on prognostic and immunological features, signaling pathways, metabolism, somatic mutations and copy number variations (CNVs), treatment responses, and forecasting of potential small-molecule agents. A total of 35 MRM-related genes were selected from the literature. Differential expression analysis of 1120 normal brain tissues and 529 LGGs revealed that 22 and 10 genes were upregulated and downregulated, respectively. Most genes were associated with prognosis of LGG. METLL8, METLL2A, TRMT112, and METTL2B were extensively expressed in all cell types and different cell cycle of each cell type. Almost all cell types had clusters related to mitochondrial RNA processing, ribosome biogenesis, or oxidative phosphorylation. Cell-cell communication and Pearson correlation analyses indicated that MRM may promoting the development of microenvironment beneficial to malignant progression via modulating NCMA signaling pathway and ICP expression. A total of 11 and 9 MRM-related genes were observed by LASSO and the RSF algorithm, respectively, and finally 6 MRM-related genes were used to establish MRM scoring system (TRMT2B, TRMT11, METTL6, METTL8, TRMT6, and TRUB2). The six MRM-related genes were then validated by qPCR in glioma and normal tissues. MRM score can predict the malignant clinical characteristics, abundance of immune infiltration, gene variation, clinical outcome, the enrichment of signaling pathways and metabolism. In vitro experiments demonstrated that silencing METTL8 significantly curbs glioma cell proliferation and enhances apoptosis. Patients with a high MRM score showed a better response to immunotherapies and small-molecule agents such as arachidonyl trifluoromethyl ketone, MS.275, AH.6809, tacrolimus, and TTNPB. These novel insights into the biological impacts of MRM within the glioma microenvironment underscore its potential as a target for developing precise therapies, including immunotherapeutic approaches.

UNASSIGNED: Extreme heat events caused by occupational exposure and heat waves are becoming more common. However, the molecular changes underlying the response to heat exposure in humans remain to be elucidated.
UNASSIGNED: This study used longitudinal multi-omics profiling to assess the impact of acute heat exposure (50°C for 30 min) in 24 subjects from a mine rescue team. Intravenous blood samples were collected before acute heat exposure (baseline) and at 5 min, 30 min, 1 h, and 24 h after acute heat exposure (recovery). In-depth multi-omics profiling was performed on each sample, including plasma proteomics (untargeted) and metabolomics (untargeted).
UNASSIGNED: After data curation and annotation, the final dataset contained 2,473 analytes, including 478 proteins and 1995 metabolites. Time-series analysis unveiled an orchestrated molecular choreography of changes involving the immune response, coagulation, acid-base balance, oxidative stress, cytoskeleton, and energy metabolism. Further analysis through protein-protein interactions and network analysis revealed potential regulators of acute heat exposure. Moreover, novel blood-based analytes that predicted change in cardiopulmonary function after acute heat exposure were identified.
UNASSIGNED: This study provided a comprehensive investigation of the dynamic molecular changes that underlie the complex physiological processes that occur in human males who undergo heat exposure. Our findings will help health impact assessment of extreme high temperature and inspire future mechanistic and clinical studies.

Acute GVHD (aGVHD) is a major complication of allogeneic hematopoietic cell transplantation (alloHCT) associated with gut microbiota disruptions. However, whether therapeutic microbiota modulation prevents aGVHD is unknown. We conducted a randomized, placebo-controlled trial of third-party fecal microbiota transplantation (FMT) administered at the peak of microbiota injury in 100 patients with acute myeloid leukemia receiving induction chemotherapy and alloHCT recipients. Despite improvements in microbiome diversity, expansion of commensals, and shrinkage of potential pathogens, aGVHD occurred more frequently after FMT than placebo. Although this unexpected finding could be explained by clinical differences between the two arms, we asked whether a microbiota explanation might be also present. To this end, we performed multi-omics analysis of preintervention and postintervention gut microbiome and serum metabolome. We found that postintervention expansion of Faecalibacterium, a commensal genus with gut-protective and anti-inflammatory properties under homeostatic conditions, predicted a higher risk for aGVHD. Faecalibacterium expansion occurred predominantly after FMT and was due to engraftment of unique donor taxa, suggesting that donor Faecalibacterium-derived antigens might have stimulated allogeneic immune cells. Faecalibacterium and ursodeoxycholic acid (an anti-inflammatory secondary bile acid) were negatively correlated, offering an alternative mechanistic explanation. In conclusion, we demonstrate context dependence of microbiota effects where a normally beneficial bacteria may become detrimental in disease. While FMT is a broad, community-level intervention, it may need precision engineering in ecologically complex settings where multiple perturbations (e.g., antibiotics, intestinal damage, alloimmunity) are concurrently in effect.
UNASSIGNED: Post-FMT expansion of Faecalibacterium, associated with donor microbiota engraftment, predicted a higher risk for aGVHD in alloHCT recipients. Although Faecalibacterium is a commensal genus with gut-protective and anti-inflammatory properties under homeostatic conditions, our findings suggest that it may become pathogenic in the setting of FMT after alloHCT. Our results support a future trial with precision engineering of the FMT product used as GVHD prophylaxis after alloHCT.

Coal seam microbes, as endogenous drivers of secondary biogenic gas production in coal seams, might be related to methane production in coal seams. In this study, we carried out anaerobic indoor culture experiments of microorganisms from three different depths of bituminous coal seams in Huainan mining area, and revealed the secondary biogas generation mechanism of bituminous coal seams by using the combined analysis of macro-genome and metabolism multi-omics. The results showed that the cumulative mass molar concentrations (Molality) of biomethane production increased with the increase of the coal seam depth in two consecutive cycles. At the genus level, there were significant differences in the bacterial and archaeal community structures corresponding to the three coal seams 1#, 6#, and 9#(p < 0.05). The volatile matter of air-dry basis (Vad) of coal was significantly correlated with differences in genus-level composition of bacteria and archaea, with correlations of R bacterial = 0.368 and R archaeal = 0.463, respectively. Functional gene analysis showed that the relative abundance of methanogenesis increased by 42% before and after anaerobic fermentation cultivation. Meanwhile, a total of 11 classes of carbon metabolism homologues closely related to methanogenesis were detected in the liquid metabolites of coal bed microbes after 60 days of incubation. Finally, the fatty acid, amino acid and carbohydrate synergistic methanogenic metabolic pathway was reconstructed based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The expression level of mcrA gene within the metabolic pathway of the 1# deep coal sample was significantly higher than that of the other two groups (p < 0.05 for significance), and the efficient expression of mcrA gene at the end of the methanogenic pathway promoted the conversion of bituminous coal organic matter to methane. Therefore, coal matrix compositions may be the key factors causing diversity in microbial community and metabolic function, which might be related to the different methane content in different coal seams.

BACKGROUND: Rheumatic heart disease (RHD), degenerative aortic stenosis (AS), and congenital valve diseases are prevalent in sub-Saharan Africa. Many knowledge gaps remain in understanding disease mechanisms, stratifying phenotypes, and prognostication. Therefore, we aimed to characterise patients through clinical profiling, imaging, histology, and molecular biomarkers to improve our understanding of the pathophysiology, diagnosis, and prognosis of RHD and AS.
METHODS: In this cross-sectional, case-controlled study, we plan to recruit RHD and AS patients and compare them to matched controls. Living participants will undergo clinical assessment, echocardiography, CMR and blood sampling for circulatory biomarker analyses. Tissue samples will be obtained from patients undergoing valve replacement, while healthy tissues will be obtained from cadavers. Immunohistology, proteomics, metabolomics, and transcriptome analyses will be used to analyse circulatory- and tissue-specific biomarkers. Univariate and multivariate statistical analyses will be used for hypothesis testing and identification of important biomarkers. In summary, this study aims to delineate the pathophysiology of RHD and degenerative AS using multiparametric CMR imaging. In addition to discover novel biomarkers and explore the pathomechanisms associated with RHD and AS through high-throughput profiling of the tissue and blood proteome and metabolome and provide a proof of concept of the suitability of using cadaveric tissues as controls for cardiovascular disease studies.

In recent years several experimental observations demonstrated that the gut microbiome plays a role in regulating positively or negatively metabolic homeostasis. Indole-3-propionic acid (IPA), a Tryptophan catabolic product mainly produced by C. Sporogenes, has been recently shown to exert either favorable or unfavorable effects in the context of metabolic and cardiovascular diseases. We performed a study to delineate clinical and multiomics characteristics of human subjects characterized by low and high IPA levels. Subjects with low IPA blood levels showed insulin resistance, overweight, low-grade inflammation, and features of metabolic syndrome compared to those with high IPA. Metabolomics analysis revealed that IPA was negatively correlated with leucine, isoleucine, and valine metabolism. Transcriptomics analysis in colon tissue revealed the enrichment of several signaling, regulatory, and metabolic processes. Metagenomics revealed several OTU of ruminococcus, alistipes, blautia, butyrivibrio and akkermansia were significantly enriched in highIPA group while in lowIPA group Escherichia-Shigella, megasphera, and Desulfovibrio genus were more abundant. Next, we tested the hypothesis that treatment with IPA in a mouse model may recapitulate the observations of human subjects, at least in part. We found that a short treatment with IPA (4 days at 20/mg/kg) improved glucose tolerance and Akt phosphorylation in the skeletal muscle level, while regulating blood BCAA levels and gene expression in colon tissue, all consistent with results observed in human subjects stratified for IPA levels. Our results suggest that treatment with IPA may be considered a potential strategy to improve insulin resistance in subjects with dysbiosis.