Characteristics of gut microbiota and metabolic phenotype in patients with major depressive disorder based on multi-omics analysis

Depression is a chronic, relapsing mental illness, often accompanied by loss of appetite, increased fatigue, insomnia and poor concentration. Here, we performed serum and urine metabolomics and fecal 16S rDNA sequencing studies on 57 unmedicated patients with major depressive disorder (MDD) and 57 healthy controls to characterize the metabolic and flora profile of MDD patients. We observed significant differences in serum and urinary metabolome between MDD patients and healthy individuals. Specifically, glycerophospholipid metabolism, primary bile acid biosynthesis and linoleic acid metabolism were significantly disordered in serum, and aminoacyl-tRNA biosynthesis, arginine biosynthesis, purine metabolism, phenylalanine metabolism, alanine, aspartate and glutamate metabolism, and pyrimidine metabolism were significantly impaired in urine. On this basis, we identified four potential diagnostic biomarkers for carnitine and four fatty acid classes in serum and urine, respectively. In addition, we observed significant disturbances of the gut microbiota in MDD patients. Spearman correlation analysis showed that imbalances in the gut microbiota were associated with metabolic disturbances, suggesting an important role of the gut microbiota in the pathogenesis of MDD. Our study provides a theoretical basis for further understanding of the pathogenesis of depression and for future clinical diagnosis and screening, as well as a basis for targeting the gut flora to optimize its structure for the prevention and treatment of depression.

Jiangu granules ameliorate postmenopausal osteoporosis via rectifying bone homeostasis imbalance: A network pharmacology analysis based on multi-omics validation

BACKGROUND

Postmenopausal osteoporosis (PMOP) is a series of reactions to bone homeostasis dysregulation mediated by estrogen deficiency in elderly women. Jiangu granules, a traditional Chinese medicine formula, has been proven as an effective treatment approach for PMOP, which still needs more research iin its complex regulatory mechanisms.

PURPOSE

Our study aimed to identify the putative targets and regulatory mechanisms of Jiangu granules in PMOP treating.

METHODS

We utilized the NHANES database to compare the clinical information of normal population and PMOP patients. Associated with transcriptomics and proteomic data, we identified the PMOP-related genes, and further studied them with bioinformatic methods including and prognosis model. Network pharmacology was applied for confirming the action targets of Jiangu granules in PMOP. We verified the safety and effectiveness in PMOP treatments of Jiangu granules, and also demonstrated our hypothesis in rats.

RESULTS

We discovered that the PMOP patients had higher monocytes than the normal women. Moreover, the transcriptomics and proteomic analysis suggested that the dysregulation of PMOP-related genes expression was associated with monocytes, and the Notch pathway were the critical targets representing bone homeostasis imbalance highly involved in the occurrence of PMOP. We also ascertained network pharmacology results further revealing that Jiangu granules might treat PMOP via recovering the bone homeostasis imbalance identified above. In vivo experiments, we confirmed the high efficacy which mainly resulted from function in mitigating the imbalance in bone homeostasis by recovering the normal expression of PMOP-related genes associated with monocytes, Notch, and steroid pathway in the rat models.

CONCLUSION

Our finding underscored the clinical potential of Jiangu granules in treating PMOP, and enriched the comprehension of the related pathogenic and therapeutic mechanisms.

Mechanisms of multi-omics and network pharmacology to explain traditional chinese medicine for vascular cognitive impairment: A narrative review

BACKGROUND

The term "vascular cognitive impairment" (VCI) describes various cognitive conditions that include vascular elements. It increases the risk of morbidity and mortality in the elderly population and is the most common cognitive impairment associated with cerebrovascular disease. Understanding the etiology of VCI may aid in identifying approaches to target its possible therapy for the condition. Treatment of VCI has focused on vascular risk factors. There are no authorized conventional therapies available right now. The medications used to treat VCI are solely approved for symptomatic relief and are not intended to prevent or slow the development of VCI.

PURPOSE

The function of Chinese medicine in treating VCI has not yet been thoroughly examined. This review evaluates the preclinical and limited clinical evidence to comprehend the "multi-component, multi-target, multi-pathway" mechanism of Traditional Chinese medicine (TCM). It investigates the various multi-omics approaches in the search for the pathological mechanisms of VCI, as well as the new research strategies, in the hopes of supplying supportive evidence for the clinical treatment of VCI.

METHODS

This review used the Preferred Reporting Items for Preferred reporting items for systematic reviews and meta-analyses (PRISMA) statements. Using integrated bioinformatics and network pharmacology approaches, a thorough evaluation and analysis of 25 preclinical studies published up to July 1, 2023, were conducted to shed light on the mechanisms of TCM for vascular cognitive impairment. The studies for the systematic review were located using the following databases: PubMed, Web of Science, Scopus, Cochrane, and ScienceDirect.

RESULTS

We discovered that the multi-omics analysis approach would hasten the discovery of the role of TCM in the treatment of VCI. It will explore components, compounds, targets, and pathways, slowing the progression of VCI from the perspective of inhibiting oxidative stress, stifling neuroinflammation, increasing cerebral blood flow, and inhibiting iron deposition by a variety of molecular mechanisms, which have significant implications for the treatment of VCI.

CONCLUSION

TCM is a valuable tool for developing dementia therapies, and further research is needed to determine how TCM components may affect the operation of the neurovascular unit. There are still some limitations, although several research have offered invaluable resources for searching for possible anti-dementia medicines and treatments. To gain new insights into the molecular mechanisms that precisely modulate the key molecules at different levels during pharmacological interventions-a prerequisite for comprehending the mechanism of action and determining the potential therapeutic value of the drugs-further research should employ more standardized experimental methods as well as more sophisticated science and technology. Given the results of this review, we advocate integrating chemical and biological component analysis approaches in future research on VCI to provide a more full and objective assessment of the standard of TCM. With the help of bioinformatics, a multi-omics analysis approach will hasten the discovery of the role of TCM in the treatment of VCI, which has significant implications for the treatment of VCI.

Multiomics Analyses Reveal Microbiome-Gut-Brain Crosstalk Centered on Aberrant Gamma-Aminobutyric Acid and Tryptophan Metabolism in Drug-Naïve Patients with First-Episode Schizophrenia

BACKGROUND AND HYPOTHESIS

Schizophrenia (SCZ) is associated with complex crosstalk between the gut microbiota and host metabolism, but the underlying mechanism remains elusive. Investigating the aberrant neurotransmitter processes reflected by alterations identified using multiomics analysis is valuable to fully explain the pathogenesis of SCZ.

STUDY DESIGN

We conducted an integrative analysis of multiomics data, including the serum metabolome, fecal metagenome, single nucleotide polymorphism data, and neuroimaging data obtained from a cohort of 127 drug-naïve, first-episode SCZ patients and 92 healthy controls to characterize the microbiome-gut-brain axis in SCZ patients. We used pathway-based polygenic risk score (PRS) analyses to determine the biological pathways contributing to genetic risk and mediation effect analyses to determine the important neuroimaging features. Additionally, a random forest model was generated for effective SCZ diagnosis.

STUDY RESULTS

We found that the altered metabolome and dysregulated microbiome were associated with neuroactive metabolites, including gamma-aminobutyric acid (GABA), tryptophan, and short-chain fatty acids. Further structural and functional magnetic resonance imaging analyses highlighted that gray matter volume and functional connectivity disturbances mediate the relationships between Ruminococcus_torgues and Collinsella_aerofaciens and symptom severity and the relationships between species Lactobacillus_ruminis and differential metabolites l-2,4-diaminobutyric acid and N-acetylserotonin and cognitive function. Moreover, analyses of the Polygenic Risk Score (PRS) support that alterations in GABA and tryptophan neurotransmitter pathways are associated with SCZ risk, and GABA might be a more dominant contributor.

CONCLUSIONS

This study provides new insights into systematic relationships among genes, metabolism, and the gut microbiota that affect brain functional connectivity, thereby affecting SCZ pathogenesis.

Single-cell spatial multi-omics and deep learning dissect enhancer-driven gene regulatory networks in liver zonation

In the mammalian liver, hepatocytes exhibit diverse metabolic and functional profiles based on their location within the liver lobule. However, it is unclear whether this spatial variation, called zonation, is governed by a well-defined gene regulatory code. Here, using a combination of single-cell multiomics, spatial omics, massively parallel reporter assays and deep learning, we mapped enhancer-gene regulatory networks across mouse liver cell types. We found that zonation affects gene expression and chromatin accessibility in hepatocytes, among other cell types. These states are driven by the repressors TCF7L1 and TBX3, alongside other core hepatocyte transcription factors, such as HNF4A, CEBPA, FOXA1 and ONECUT1. To examine the architecture of the enhancers driving these cell states, we trained a hierarchical deep learning model called DeepLiver. Our study provides a multimodal understanding of the regulatory code underlying hepatocyte identity and their zonation state that can be used to engineer enhancers with specific activity levels and zonation patterns.

Statistical integration of multi-omics and drug screening data from cell lines

Data integration methods are used to obtain a unified summary of multiple datasets. For multi-modal data, we propose a computational workflow to jointly analyze datasets from cell lines. The workflow comprises a novel probabilistic data integration method, named POPLS-DA, for multi-omics data. The workflow is motivated by a study on synucleinopathies where transcriptomics, proteomics, and drug screening data are measured in affected LUHMES cell lines and controls. The aim is to highlight potentially druggable pathways and genes involved in synucleinopathies. First, POPLS-DA is used to prioritize genes and proteins that best distinguish cases and controls. For these genes, an integrated interaction network is constructed where the drug screen data is incorporated to highlight druggable genes and pathways in the network. Finally, functional enrichment analyses are performed to identify clusters of synaptic and lysosome-related genes and proteins targeted by the protective drugs. POPLS-DA is compared to other single- and multi-omics approaches. We found that HSPA5, a member of the heat shock protein 70 family, was one of the most targeted genes by the validated drugs, in particular by AT1-blockers. HSPA5 and AT1-blockers have been previously linked to α-synuclein pathology and Parkinson's disease, showing the relevance of our findings. Our computational workflow identified new directions for therapeutic targets for synucleinopathies. POPLS-DA provided a larger interpretable gene set than other single- and multi-omic approaches. An implementation based on R and markdown is freely available online.

Antibiotic-induced gut dysbiosis elicits gut-brain axis relevant multi-omic signatures and behavioral and neuroendocrine changes in a nonhuman primate model

Emerging evidence indicates that antibiotic-induced dysbiosis can play an etiological role in the pathogenesis of neuropsychiatric disorders. However, most of this evidence comes from rodent models. The objective of this study was to evaluate if antibiotic-induced gut dysbiosis can elicit changes in gut metabolites and behavior indicative of gut-brain axis disruption in common marmosets (Callithrix jacchus) - a nonhuman primate model often used to study sociability and stress. We were able to successfully induce dysbiosis in marmosets using a custom antibiotic cocktail (vancomycin, enrofloxacin and neomycin) administered orally for 28 days. This gut dysbiosis altered gut metabolite profiles, behavior, and stress reactivity. Increase in gut Fusobacterium spp. post-antibiotic administration was a novel dysbiotic response and has not been observed in any rodent or human studies to date. There were significant changes in concentrations of several gut metabolites which are either neurotransmitters (e.g., GABA and serotonin) or have been found to be moderators of gut-brain axis communication in rodent models (e.g., short-chain fatty acids and bile acids). There was an increase in affiliative behavior and sociability in antibiotic-administered marmosets, which might be a coping mechanism in response to gut dysbiosis-induced stress. Increase in urinary cortisol levels after multiple stressors provides more definitive proof that this model of dysbiosis may cause disrupted communication between gut and brain in common marmosets. This study is a first attempt to establish common marmosets as a novel model to study the impact of severe gut dysbiosis on gut-brain axis cross-talk and behavior.

A Circular RNA Generated from Nebulin (NEB) Gene Splicing Promotes Skeletal Muscle Myogenesis in Cattle as Detected by a Multi-Omics Approach

Cattle and the draught force provided by its skeletal muscle have been integral to agro-ecosystems of agricultural civilization for millennia. However, relatively little is known about the cattle muscle functional genomics (including protein coding genes, non-coding RNA, etc.). Circular RNAs (circRNAs), as a new class of non-coding RNAs, can be effectively translated into detectable peptides, which enlightened us on the importance of circRNAs in cattle muscle physiology function. Here, RNA-seq, Ribosome profiling (Ribo-seq), and peptidome data are integrated from cattle skeletal muscle, and detected five encoded peptides from circRNAs. It is further identified and functionally characterize a 907-amino acids muscle-specific peptide that is named circNEB-peptide because derived by the splicing of Nebulin (NEB) gene. This peptide localizes to the nucleus and cytoplasm and directly interacts with SKP1 and TPM1, key factors regulating physiological activities of myoblasts, via ubiquitination and myoblast fusion, respectively. The circNEB-peptide is found to promote myoblasts proliferation and differentiation in vitro, and induce muscle regeneration in vivo. These findings suggest circNEB-peptide is an important regulator of skeletal muscle regeneration and underscore the possibility that more encoding polypeptides derived by RNAs currently annotated as non-coding exist.

Multi-omics and single-cell sequencing analyses reveal the potential significance of circadian pathways in cancer therapy

BACKGROUND

Circadian rhythm disturbance is an independent risk factor for cancer. However, few studies have been reported on circadian rhythm related genes (CRGs) in cancer, so it is important to further explore the impact of CRGs in pan-cancer.

RESEARCH DESIGN AND METHODS

The Cancer Genome Atlas database was used to collect cancer-related data such as copy number variation, single nucleotide variants, methylation, and survival differences. Immunohistochemistry (IHC) was used to verify the expression of circadian rhythm hub genes. The circadian pathway scores (CRS) were calculated using single-sample gene enrichment analysis. TIMER and GEPIA databases were used for immune-cell integration and assessment. Single-cell sequencing data was used to evaluate the abundance of CRS in tumor microenvironment cells.

RESULTS

In this study, we found that the expression of circadian pathway varies between tumors. CSNK1E was significantly up-regulated in most tumors and CRY2 was significantly down-regulated in most tumors. The protein interaction network suggested CRY2 as the core gene and IHC verified its significant low expression in KIRC. In addition, CRGs were found to be protective factors in most tumors and have the potential to act as specific immune markers in different tumors. CRS was significantly lower in abundance in most tumors. CRS was significantly associated with overall survival in tumor patients and associated with the expression of many immune cells in the tumor immune microenvironment. CRS is significantly associated with tumor mutational burden and microsatellite instability scores in most tumors and may serve as a potential immunotherapeutic marker.

CONCLUSIONS

The circadian rhythm pathway may be a breakthrough point in regulating the tumor microenvironment meanwhile a suitable immunotherapy method in the future.

Integrative Placental Multi-Omics Analysis Reveals Perturbed Pathways and Potential Prognostic Biomarkers in Gestational Hypertension

BACKGROUND

Gestational hypertension (GH) is a severe complication that occurs after 20 weeks of pregnancy; however, its molecular mechanisms are not yet fully understood.

OBJECTIVE

Through this case-control discovery phase study, we aimed to find disease-specific candidate placental microRNAs (miRNAs) and metabolite markers for differentiating GH by integrating next-generation sequencing and metabolomics multi-omics analysis of placenta. Using small RNA sequencing and metabolomics of placental tissues of healthy pregnant (HP, n = 24) and GH subjects (n = 20), the transcriptome and metabolome were characterized in both groups.

RESULTS

The study identified a total of 44 downregulated placental miRNAs which includes three novel, three mature and 38 precursor miRNAs. Six miRNAs including three mature (hsa-miR-181a-5p, hsa-miR-498-5p, and hsa-miR-26b-5p) and three novel (NC_000016.10_1061, NC_000005.10_475, and NC_000001.11_53) were considered for final target prediction and functional annotation. Integrative analysis of differentially expressed miRNAs and metabolites yielded five pathways such as purine, glutathione, glycerophospholipid, inositol phosphate and β-alanine to be significantly perturbed in GH. We present fourteen genes (LPCAT1, LPCAT2, DGKH, PISD, GPAT2, PTEN, SACM1L, PGM2, AMPD3, AK7, AK3, CNDP1, IDH2, and ODC1) and eight metabolites (xanthosine, xanthine, spermine, glycine, CDP-Choline, glyceraldehyde 3-phosphate, β-alanine, and histidine) with potential to distinguish GH and HP.

CONCLUSION

The differential expression of miRNAs, their target genes, altered metabolites and metabolic pathways in GH patients were identified for the first time in our study. Further, the altered miRNAs and metabolites were integrated to build their inter-connectivity network. The findings obtained from our study may be used as a valuable source to further unravel the molecular pathways associated with GH and also for the evaluation of prognostic markers.

Multi-Omics Analysis Reveals Sphingomyelin Accumulation, Glycerolipids Loss, and Disorders of Lipid Metabolism Regulated by Leucine Deprivation in the Liver of Mice

SCOPE

Branched-chain amino acids, especially leucine, have been reported to play a role in regulating lipid metabolism. This study aims to examine the effects of leucine deprivation on hepatic lipid metabolism.

METHODS AND RESULTS

C57BL/6 mice are fed with a chow diet (control group, n = 8) or a leucine-free diet (-Leu group, n = 8) for 7 days. Histology, lipidomics, targeted metabolomics, and transcriptomics are performed to analyze the liver tissue. Compared to control group, -Leu group exhibits a notably reduced liver weight, accompanied by hepatic injury, and disorders of lipid metabolism. The level of sphingomyelin (SM) is significantly increased in the liver of -Leu group, while the glycerolipids (GL) level is significantly decreased. The expression of sphingomyelin synthase 1 (SGMS1) is upregulated by leucine deprivation in a time-dependent manner, leading to hepatic SM accumulation. Moreover, leucine deprivation results in hepatic GL loss via suppressing fatty acid synthase (FASN) and acetyl-CoA carboxylase 1 (ACC1) expression.

CONCLUSION

The findings demonstrate that leucine deprivation results in abnormal lipid metabolism in the liver, mainly manifested as SM accumulation and GL loss. These results provide insights into the role of leucine in regulating lipid metabolism.

Prioritization of risk genes in colorectal cancer by integrative analysis of multi-omics data and gene networks

Genome-wide association studies (GWASs) have identified over 140 colorectal cancer (CRC)-associated loci; however, target genes at the majority of loci and underlying molecular mechanisms are poorly understood. Here, we utilized a Bayesian approach, integrative risk gene selector (iRIGS), to prioritize risk genes at CRC GWAS loci by integrating multi-omics data. As a result, a total of 105 high-confidence risk genes (HRGs) were identified, which exhibited strong gene dependencies for CRC and enrichment in the biological processes implicated in CRC. Among the 105 HRGs, CEBPB, located at the 20q13.13 locus, acted as a transcription factor playing critical roles in cancer. Our subsequent assays indicated the tumor promoter function of CEBPB that facilitated CRC cell proliferation by regulating multiple oncogenic pathways such as MAPK, PI3K-Akt, and Ras signaling. Next, by integrating a fine-mapping analysis and three independent case-control studies in Chinese populations consisting of 8,039 cases and 12,775 controls, we elucidated that rs1810503, a putative functional variant regulating CEBPB, was associated with CRC risk (OR=0.90, 95%CI=0.86-0.93, P=1.07×10-7). The association between rs1810503 and CRC risk was further validated in three additional multi-ancestry populations consisting of 24,254 cases and 58,741 controls. Mechanistically, the rs1810503 A to T allele change weakened the enhancer activity in an allele-specific manner to decrease CEBPB expression via long-range promoter-enhancer interactions, mediated by the transcription factor, REST, and thus decreased CRC risk. In summary, our study provides a genetic resource and a generalizable strategy for CRC etiology investigation, and highlights the biological implications of CEBPB in CRC tumorigenesis, shedding new light on the etiology of CRC.

Microfluidics Coupled Mass Spectrometry for Single Cell Multi-Omics

Population-level analysis masks significant heterogeneity between individual cells, making it difficult to accurately reflect the true intricacies of life activities. Microfluidics is a technique that can manipulate individual cells effectively and is commonly coupled with a variety of analytical methods for single-cell analysis. Single-cell omics provides abundant molecular information at the single-cell level, fundamentally revealing differences in cell types and biological states among cell individuals, leading to a deeper understanding of cellular phenotypes and life activities. Herein, this work summarizes the microfluidic chips designed for single-cell isolation, manipulation, trapping, screening, and sorting, including droplet microfluidic chips, microwell arrays, hydrodynamic microfluidic chips, and microchips with microvalves. This work further reviews the studies on single-cell proteomics, metabolomics, lipidomics, and multi-omics based on microfluidics and mass spectrometry. Finally, the challenges and future application of single-cell multi-omics are discussed.

Integrated single-cell multiomics uncovers foundational regulatory mechanisms of lens development and pathology

Ocular lens development entails epithelial to fiber cell differentiation, defects in which cause congenital cataracts. We report the first single-cell multiomic atlas of lens development, leveraging snRNA-seq, snATAC-seq and CUT&RUN-seq to discover previously unreported mechanisms of cell fate determination and cataract-linked regulatory networks. A comprehensive profile of cis- and trans-regulatory interactions, including for the cataract-linked transcription factor MAF, is established across a temporal trajectory of fiber cell differentiation. Furthermore, we identify an epigenetic paradigm of cellular differentiation, defined by progressive loss of the H3K27 methylation writer Polycomb repressive complex 2 (PRC2). PRC2 localizes to heterochromatin domains across master-regulator transcription factor gene bodies, suggesting it safeguards epithelial cell fate. Moreover, we demonstrate that FGF hyper-stimulation in vivo leads to MAF network activation and the emergence of novel lens cell states. Collectively, these data depict a comprehensive portrait of lens fiber cell differentiation, while defining regulatory effectors of cell identity and cataract formation.

Multi-omics reveals deoxycholic acid modulates bile acid metabolism via the gut microbiota to antagonize carbon tetrachloride-induced chronic liver injury

Deoxycholic acid (DCA) serves essential functions in both physiological and pathological liver processes; nevertheless, the relationship among DCA, gut microbiota, and metabolism in chronic liver injury remain insufficiently understood. The primary objective of this study is to elucidate the potential of DCA in ameliorating chronic liver injury and evaluate its regulatory effect on gut microbiota and metabolism via a comprehensive multi-omics approach. Our study found that DCA supplementation caused significant changes in the composition of gut microbiota, which were essential for its antagonistic effect against CCl4-induced chronic liver injury. When gut microbiota was depleted with antibiotics, the observed protective efficacy of DCA against chronic liver injury became noticeably attenuated. Mechanistically, we discovered that DCA regulates the metabolism of bile acids (BAs), including 3-epi DCA, Apo-CA, and its isomers 12-KLCA and 7-KLCA, IHDCA, and DCA, by promoting the growth of A.muciniphila in gut microbiota. This might lead to the inhibition of the IL-17 and TNF inflammatory signaling pathway, thereby effectively countering CCl4-induced chronic liver injury. This study illustrates that the enrichment of A. muciniphila in the gut microbiota, mediated by DCA, enhances the production of secondary bile acids, thereby mitigating chronic liver injury induced by CCl4. The underlying mechanism may involve the inhibition of hepatic IL-17 and TNF signaling pathways. These findings propose a promising approach to alleviate chronic liver injury by modulating both the gut microbiota and bile acids metabolism.

Multi-omic approaches provide insights into the molecular mechanisms of Sojae semen germinatum water extract against overactive bladder

Sojae semen germinatum (SSG) is derived from mature soybean seeds that have been germinated and dried, typically with sprouts measuring approximately 0.5 cm in length. SSG is traditionally known for its properties in clearing heat and moisture. Nevertheless, limited information was reported on the effects and mechanisms of SSG in alleviating urinary symptoms. This study employed urodynamic parameters to investigate the therapeutic effect of SSG water extract on overactive bladder (OAB) in the rat model with benign prostatic hyperplasia. Through a combination of transcriptomic and metabolomic analyses, the pathways and key proteins of the SSG treatment for OAB were identified and validated by ELISA and Western blotting. Furthermore, network pharmacology elucidated the roles of SSG's isoflavones acting on the target which was identified by above-mentioned multi-omics analysis. Our results indicate that SSG water extract significantly mitigated OAB by down-regulating the PGE2/EP1/PLCβ2/p-MLC signaling pathway. It was speculated that the active ingredient in the SSG on EP1 was genistein. This study provided valuable insights into the molecular mechanisms of SSG water extract, emphasizing the multi-target characteristics and critical pathways in improving OAB. Furthermore, this study contributes to the potential utilization of SSG as a functional food.

Multi-omic prediction of incident type 2 diabetes

AIMS/HYPOTHESIS

The identification of people who are at high risk of developing type 2 diabetes is a key part of population-level prevention strategies. Previous studies have evaluated the predictive utility of omics measurements, such as metabolites, proteins or polygenic scores, but have considered these separately. The improvement that combined omics biomarkers can provide over and above current clinical standard models is unclear. The aim of this study was to test the predictive performance of genome, proteome, metabolome and clinical biomarkers when added to established clinical prediction models for type 2 diabetes.

METHODS

We developed sparse interpretable prediction models in a prospective, nested type 2 diabetes case-cohort study (N=1105, incident type 2 diabetes cases=375) with 10,792 person-years of follow-up, selecting from 5759 features across the genome, proteome, metabolome and clinical biomarkers using least absolute shrinkage and selection operator (LASSO) regression. We compared the predictive performance of omics-derived predictors with a clinical model including the variables from the Cambridge Diabetes Risk Score and HbA1c.

RESULTS

Among single omics prediction models that did not include clinical risk factors, the top ten proteins alone achieved the highest performance (concordance index [C index]=0.82 [95% CI 0.75, 0.88]), suggesting the proteome as the most informative single omic layer in the absence of clinical information. However, the largest improvement in prediction of type 2 diabetes incidence over and above the clinical model was achieved by the top ten features across several omic layers (C index=0.87 [95% CI 0.82, 0.92], Δ C index=0.05, p=0.045). This improvement by the top ten omic features was also evident in individuals with HbA1c <42 mmol/mol (6.0%), the threshold for prediabetes (C index=0.84 [95% CI 0.77, 0.90], Δ C index=0.07, p=0.03), the group in whom prediction would be most useful since they are not targeted for preventative interventions by current clinical guidelines. In this subgroup, the type 2 diabetes polygenic risk score was the major contributor to the improvement in prediction, and achieved a comparable improvement in performance when added onto the clinical model alone (C index=0.83 [95% CI 0.75, 0.90], Δ C index=0.06, p=0.002). However, compared with those with prediabetes, individuals at high polygenic risk in this group had only around half the absolute risk for type 2 diabetes over a 20 year period.

CONCLUSIONS/INTERPRETATION

Omic approaches provided marginal improvements in prediction of incident type 2 diabetes. However, while a polygenic risk score does improve prediction in people with an HbA1c in the normoglycaemic range, the group in whom prediction would be most useful, even individuals with a high polygenic burden in that subgroup had a low absolute type 2 diabetes risk. This suggests a limited feasibility of implementing targeted population-based genetic screening for preventative interventions.

Multiomic spatial landscape of innate immune cells at human central nervous system borders

The innate immune compartment of the human central nervous system (CNS) is highly diverse and includes several immune-cell populations such as macrophages that are frequent in the brain parenchyma (microglia) and less numerous at the brain interfaces as CNS-associated macrophages (CAMs). Due to their scantiness and particular location, little is known about the presence of temporally and spatially restricted CAM subclasses during development, health and perturbation. Here we combined single-cell RNA sequencing, time-of-flight mass cytometry and single-cell spatial transcriptomics with fate mapping and advanced immunohistochemistry to comprehensively characterize the immune system at human CNS interfaces with over 356,000 analyzed transcriptomes from 102 individuals. We also provide a comprehensive analysis of resident and engrafted myeloid cells in the brains of 15 individuals with peripheral blood stem cell transplantation, revealing compartment-specific engraftment rates across different CNS interfaces. Integrated multiomic and high-resolution spatial transcriptome analysis of anatomically dissected glioblastoma samples shows regionally distinct myeloid cell-type distributions driven by hypoxia. Notably, the glioblastoma-associated hypoxia response was distinct from the physiological hypoxia response in fetal microglia and CAMs. Our results highlight myeloid diversity at the interfaces of the human CNS with the periphery and provide insights into the complexities of the human brain's immune system.

Identification of USP29 as a key regulator of nucleotide biosynthesis in neuroblastoma through integrative analysis of multi-omics data

Cancer cells show enhanced nucleotide biosynthesis, which is essential for their unlimited proliferation, but the underlying mechanisms are not entirely clear. Ubiquitin specific peptidase 29 (USP29) was reported to sustain neuroblastoma progression by promoting glycolysis and glutamine catabolism; however, its potential role in regulating nucleotide biosynthesis in tumor cells remains unknown. In this study, we depleted endogenous USP29 in MYCN-amplified neuroblastoma SK-N-BE2 cells by sgRNAs and conducted metabolomic analysis in cells with or without USP29 depletion, we found that USP29 deficiency caused a disorder of intermediates involved in glycolysis and nucleotide biosynthesis. De novo nucleotide biosynthesis was analyzed using 13C6 glucose as a tracer under normoxia and hypoxia. The results indicated that USP29-depleted cells showed inhibition of nucleotide anabolic intermediates derived from glucose, and this inhibition was more significant under hypoxic conditions. Analysis of RNA sequencing data in SK-N-BE2 cells demonstrated that USP29 promoted the gene expression of metabolic enzymes involved in nucleotide anabolism, probably by regulating MYC and E2F downstream pathways. These findings indicated that USP29 is a key regulator of nucleotide biosynthesis in tumor cells.

Integrated of multi-omics and molecular docking reveal PHGDH, PSAT1 and PSPH in the serine synthetic pathway as potential targets of T-2 toxin exposure in pig intestinal tract

T-2 toxin (T-2) with a molecular weight of 466.52 g/mol is an inevitable mycotoxin in food products and feeds, posing a significant threat to human and animal health. However, the underlying molecular mechanisms of the cytotoxic effects of T-2 exposure on porcine intestinal epithelial cells (IPEC-J2) remain unclear. Here, we investigated the cytotoxic effects of T-2 exposure on IPEC-J2 through the detection of cell viability, cell morphology, mitochondrial membrane potential, ROS, apoptosis and autophagy. Further transcriptomic and proteomic analyses of IPEC-J2 upon T-2 exposure were performed by using RNA-seq and TMT techniques. A total of 546 differential expressed genes (DEGs) and 269 differentially expressed proteins (DEPs) were detected. Among these, 24 common DEGs/DEPs were involved in IPEC-J2 upon T-2 exposure. Interestingly, molecular docking analysis revealed potential interactions between T-2 and three key enzymes (PHGDP, PSAT1, and PSPH) in the serine biosynthesis pathway. Besides, further experimental showed that PSAT1 knockdown exacerbated T-2-induced oxidative damage. Together, our findings indicated that the serine biosynthesis pathway including PHGDP, PSAT1, PSPH genes probably acts critical roles in the regulation of T-2-induced cell damage. This study provided new insights into the global molecular effects of T-2 exposure and identified the serine biosynthesis pathway as molecular targets and potential treatment strategies against T-2.

Comprehensive evaluation of the prebiotic properties of Dendrobium officinale polysaccharides, β-glucan, and inulin during in vitro fermentation via multi-omics analysis

Dietary fiber is crucial for human health mainly due to its impact on gut microbiota structure and metabolites. This study aimed to investigate the impact of Dendrobium officinale polysaccharides (DOP) and two common fibers (β-glucan and inulin) on the gut microbiome structure and metabolic profile in vitro. Fecal samples were obtained from 30 healthy volunteers, which were then individually subjected to fermentation with each type of fiber. The results revealed that all fibers were efficiently degraded by gut microbiota, with DOP exhibiting a slower fermentation rate compared to β-glucan and inulin. The fermentation of all fibers led to a significant increase in the production of short-chain fatty acids (SCFAs) and a reduction in branched-chain fatty acids (BCFAs), sulfides, phenols, and indole. Moreover, the abundance of unclassified Enterobacteriaceae, which was positively correlated with sulfide, phenols, and indole levels, was significantly reduced by all fibers. Additionally, DOP specifically promoted the growth of Parabacteroides, while β-glucan and inulin promoted the growth of Bifidobacterium and Faecalibacterium. Taken together, these findings enhance our understanding of the role of DOP, β-glucan, and inulin in modulating gut microbiota and metabolites, where the fermentation with fecal bacteria from different volunteers could provide valuable insights for personalized therapeutic approaches.

Systemic toxicity of snake venom metalloproteinases: Multi-omics analyses of kidney and blood plasma disturbances in a mouse model

Snakebite envenomation is classified as a Neglected Tropical Disease. Bothrops jararaca venom induces kidney injury and coagulopathy. HF3, a hemorrhagic metalloproteinase of B. jararaca venom, participates in the envenomation pathogenesis. We evaluated the effects of HF3 in mouse kidney and blood plasma after injection in the thigh muscle, mimicking a snakebite. Transcriptomic analysis showed differential expression of 31 and 137 genes related to kidney pathology after 2 h and 6 h, respectively. However, only subtle changes were observed in kidney proteome, with differential abundance of 15 proteins after 6 h, including kidney injury markers. N-terminomic analysis of kidney proteins showed 420 proteinase-generated peptides compatible with meprin specificity, indicating activation of host proteinases. Plasma analysis revealed differential abundance of 90 and 219 proteins, respectively, after 2 h and 6 h, including coagulation-cascade and complement-system components, and creatine-kinase, whereas a semi-specific search of N-terminal peptides indicated activation of endogenous proteinases. HF3 promoted host reactions, altering the gene expression and the proteolytic profile of kidney tissue, and inducing plasma proteome imbalance driven by changes in abundance and proteolysis. The overall response of the mouse underscores the systemic action of a hemorrhagic toxin that transcends local tissue damage and is related to known venom-induced systemic effects.