Is my network module preserved and reproducible?

Characteristics of gene expression in epicardial adipose tissue and subcutaneous adipose tissue in patients at risk for heart failure undergoing coronary artery bypass grafting

BACKGROUND

Epicardial adipose tissue (EAT) surrounds the heart and is hypothesised to play a role in the development of heart failure (HF). In this study, we first investigated the differences in gene expression between epicardial adipose tissue (EAT) and subcutaneous adipose tissue (SAT) in patients undergoing elective coronary artery bypass graft (CABG) surgery (n = 21; 95% male). Secondly, we examined the association between EAT and SAT in patients at risk for HF stage A (n = 12) and in pre-HF patients, who show signs but not symptoms of HF, stage B (n = 9).

RESULTS

The study confirmed a distinct separation between EAT and SAT. In EAT 17 clusters of genes were present, of which several novel gene modules are associated with characteristics of HF. Notably, seven gene modules showed significant correlation to measures of HF, such as end diastolic left ventricular posterior wall thickness, e'mean, deceleration time and BMI. One module was particularly distinct in EAT when compared to SAT, featuring key genes such as FLT4, SEMA3A, and PTX3, which are implicated in angiogenesis, inflammation regulation, and tissue repair, suggesting a unique role in EAT linked to left ventricular dysfunction. Genetic expression was compared in EAT across all pre-HF and normal phenotypes, revealing small genetic changes in the form of 18 differentially expressed genes in ACC/AHA Stage A vs. Stage B.

CONCLUSIONS

The roles of subcutaneous and epicardial fat are clearly different. We highlight the gene expression difference in search of potential modifiers of HF progress. The true implications of our findings should be corroborated in other studies since HF ACC/AHA stage B patients are common and carry a considerable risk for progression to symptomatic HF.

Differential gene expression and chromatin accessibility in the medial prefrontal cortex associated with individual differences in rat behavioral models of opioid use disorder

Opioid use disorder (OUD) is a neuropsychological disease that has a devastating impact on public health. Substantial individual differences in vulnerability exist, the neurobiological substrates of which remain unclear. To address this question, we investigated genome-wide gene transcription (RNA-seq) and chromatin accessibility (ATAC-seq) in the medial prefrontal cortex (mPFC) of male and female rats exhibiting differential vulnerability in behavioral paradigms modeling different phases of OUD: Withdrawal-Induced Anhedonia (WIA), Demand, and Reinstatement. Ingenuity Pathway Analysis (IPA) of RNA-seq revealed greater changes in canonical pathways in Resilient (vs. Saline) rats in comparison to Vulnerable (vs. Saline) rats across 3 paradigms, suggesting brain adaptations that might contribute to resilience to OUD across its trajectory. Analyses of gene networks and upstream regulators implicated processes involved in oligodendrocyte maturation and myelination in WIA, neuroinflammation in Demand, and metabolism in Reinstatement. Motif analysis of ATAC-seq showed changes in chromatin accessibility to a small set of transcription factor (TF) binding sites as a function either of opioid exposure (i.e., morphine versus saline) generally or of individual vulnerability specifically. Some of these were shared across the 3 paradigms and others were unique to each. In conclusion, we have identified changes in biological pathways, TFs, and their binding motifs that vary with paradigm and OUD vulnerability. These findings point to the involvement of distinct transcriptional and epigenetic mechanisms in response to opioid exposure, vulnerability to OUD, and different stages of the disorder.

Endotype-driven Co-module mechanisms of danhong injection in the Co-treatment of cardiovascular and cerebrovascular diseases: A modular-based drug and disease integrated analysis

ETHNOPHARMACOLOGICAL RELEVANCE

Cardiovascular and cerebrovascular diseases are the leading causes of death worldwide and interact closely with each other. Danhong Injection (DHI) is a widely used preparation for the co-treatment of brain and heart diseases (CTBH). However, the underlying molecular endotype mechanisms of DHI in the CTBH remain unclear.

AIM OF THIS STUDY

To elucidate the underlying endotype mechanisms of DHI in the CTBH.

MATERIALS AND METHODS

In this study, we proposed a modular-based disease and drug-integrated analysis (MDDIA) strategy for elucidating the systematic CTBH mechanisms of DHI using high-throughput transcriptome-wide sequencing datasets of DHI in the treatment of patients with stable angina pectoris (SAP) and cerebral infarction (CI). First, we identified drug-targeted modules of DHI and disease modules of SAP and CI based on the gene co-expression networks of DHI therapy and the protein-protein interaction networks of diseases. Moreover, module proximity-based topological analyses were applied to screen CTBH co-module pairs and driver genes of DHI. At the same time, the representative driver genes were validated via in vitro experiments on hypoxia/reoxygenation-related cardiomyocytes and neuronal cell lines of H9C2 and HT22.

RESULTS

Seven drug-targeted modules of DHI and three disease modules of SAP and CI were identified by co-expression networks. Five modes of modular relationships between the drug and disease modules were distinguished by module proximity-based topological analyses. Moreover, 13 targeted module pairs and 17 driver genes associated with DHI in the CTBH were also screened. Finally, the representative driver genes AKT1, EDN1, and RHO were validated by in vitro experiments.

CONCLUSIONS

This study, based on clinical sequencing data and modular topological analyses, integrated diseases and drug targets. The CTBH mechanism of DHI may involve the altered expression of certain driver genes (SRC, STAT3, EDN1, CYP1A1, RHO, RELA) through various enriched pathways, including the Wnt signaling pathway.

Multi-layer molecular analysis reveals distinctive metabolomic and transcriptomic profiles of different sweet corn varieties

In plants, sugar metabolism involves a complex interplay of genetic, molecular and environmental factors. To better understand the molecular mechanisms underlying these processes, we utilized a multi-layered approach that integrated transcriptomic and metabolomic datasets generated from multiple different varieties of sweet corn. Through this analysis, we found 2533 genes that were differentially expressed in the immature kernel tissues of sweet corn, including genes involved in transcriptional regulation, sugar metabolism, primary metabolism, and other processes associated with adaptability of sweet corn. We also detected 31 differential metabolites among the three types of sweet corn. Utilizing an integrated approach encompassing transcriptomics and eGWAS, we elucidated the transcriptional regulatory patterns governing these differential metabolites. Specifically, we delved into the transcriptional modulation of malate- and ubiquitin-associated genes across a range of sweet corn varieties, shedding new light on the molecular mechanisms underlying their regulation. This study provides a framework for future research aimed at improving the current understanding of sugar metabolism and regulatory gene networks in sweet corn, which could ultimately lead to the development of novel strategies for crop improvement.

Gut microbiome and metabolome alterations in traditional Chinese medicine damp-heat constitution following treatment with a Chinese patent medicine and lifestyle intervention

BACKGROUND

The gut microbiota is crucial in human health and diseases. Traditional Chinese Medicine Constitution (TCMC) divides people into those with a balanced constitution (Ping-he [PH]) and those with an unbalanced constitution. Dampness-heat constitution (Shi-re [SR]) is a common unbalanced constitution in the Chinese population and is susceptible to diseases. However, unbalanced constitutions can be regulated by Chinese medicine and lifestyle interventions in clinical practice. Ermiao Pill (EMP) is a Chinese medicine known for clearing heat and draining dampness and improving SR. However, the efficacy and mechanism of EMP are unclear.

HYPOTHESIS/PURPOSE

To determine alterations in the gut microbiota and metabolome in SR and any changes after EMP treatment combined with lifestyle intervention.

STUDY DESIGN

Randomized clinical trial.

METHODS

We enrolled 112 healthy SR individuals and evaluated the efficacy of EMP along with lifestyle interventions. We further assessed serum cytokine levels, serum and urinary metabolomes, and the gut microbiota by 16S rRNA gene sequencing analysis before and after the EMP and lifestyle interventions.

RESULTS

107 SR individuals (55 in the intervention group and 52 in the control group) completed the 1-month-intervention and 1-year-follow-up. The intervention group significantly improved their health status within 1 month, with a reduced SR symptom score, and the efficacy lasted to the 1-year follow-up. The control group needed a further 6 months to reduce the SR symptom score. The gut microbiota of PH individuals was more diverse and had significantly higher proportions of many bacterial species than the SR. Microbiota co-occurrence network analysis showed that SR enriches metabolites correlating with microbial community structure, consistent with traits of healthy SR-enriched microbiota.

CONCLUSION

EMP combined with lifestyle intervention produced health benefits in SR individuals. Our study indicates a pivotal role of gut microbiota and metabolome alterations in distinguishing between healthy SR and PH. Furthermore, the study reveals structural changes of gut microbiota and metabolites induced by EMP and lifestyle intervention. The treatment enriched the number of beneficial bacteria, such as Akkermansia muciniphila and Lactobacillus in the gut. Our findings provide a strong indication that several metabolite factors are associated with the gut microbiota. Moreover, the gut microbiome and metabolome might be powerful tools for TCMC diagnosis and personalized therapy.

Leveraging neighborhood representations of single-cell data to achieve sensitive DE testing with miloDE

Single-cell RNA-sequencing enables testing for differential expression (DE) between conditions at a cell type level. While powerful, one of the limitations of such approaches is that the sensitivity of DE testing is dictated by the sensitivity of clustering, which is often suboptimal. To overcome this, we present miloDE-a cluster-free framework for DE testing (available as an open-source R package). We illustrate the performance of miloDE on both simulated and real data. Using miloDE, we identify a transient hemogenic endothelia-like state in mouse embryos lacking Tal1 and detect distinct programs during macrophage activation in idiopathic pulmonary fibrosis.

Identification of key genes associated with acute myocardial infarction using WGCNA and two-sample mendelian randomization study

OBJECTIVE

Acute myocardial infarction (AMI) is a severe condition with high morbidity and mortality rates. This study aimed to identify hub genes potentially associated with AMI and assess their clinical utility in predicting AMI occurrence.

METHODS

Gene microarray data were obtained from the Gene Expression Omnibus (GEO) database. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were conducted on samples from patients with AMI and control samples to identify modules significantly associated with AMI. GO and KEGG analyses were applied to investigate the potential functions of these hub genes. Lastly, the mendelian randomization (MR) method was applied to analyze the causal relationship between the hub gene TNF and AMI.

RESULTS

285 differentially expressed genes (DEGs) were identified through WCGNA and were clustered into 6 modules. The yellow module appeared most relevant to AMI. Further exploration through GO and KEGG pathway enrichment showed that key hub genes in the yellow module were linked to positive regulation of cytokine production, cytokine receptor binding, NF-kappa B signaling pathway, IL-17 signaling pathway, and TNF signaling pathway. The top 10 genes identified through Cytoscape software analysis were IL1B, TNF, TLR4, TLR2, FCGR3B, MMP9, CXCL8, TLR8, ICAM1, and JUK. Utilizing inverse variance weighting (IVW) analysis, we discovered a significant association between TNF and AMI risk, with an OR of 0.946 (95% CI = 0.911-0.984, p = 0.005).

CONCLUSIONS

The result of this study indicated that TNF, TLR2, TLR4, IL1B and FCGR3B may be potential biodiagnostic markers for AMI. TNF can inhibit inflammatory and oxidative stress responses in AMI, exerting a protective role in the heart.

Critical reasoning on the co-expression module QTL in the dorsolateral prefrontal cortex

Expression quantitative trait locus (eQTL) analysis is a popular method of gaining insight into the function of regulatory variation. While cis-eQTL resources have been instrumental in linking genome-wide association study variants to gene function, complex trait heritability may be additionally mediated by other forms of gene regulation. Toward this end, novel eQTL methods leverage gene co-expression (module-QTL) to investigate joint regulation of gene modules by single genetic variants. Here we broadly define a "module-QTL" as the association of a genetic variant with a summary measure of gene co-expression. This approach aims to reduce the multiple testing burden of a trans-eQTL search through the consolidation of gene-based testing and provide biological context to eQTLs shared between genes. In this article we provide an in-depth examination of the co-expression module eQTL (module-QTL) through literature review, theoretical investigation, and real-data application of the module-QTL to three large prefrontal cortex genotype-RNA sequencing datasets. We find module-QTLs in our study that are disease associated and reproducible are not additionally informative beyond cis- or trans-eQTLs for module genes. Through comparison to prior studies, we highlight promises and limitations of the module-QTL across study designs and provide recommendations for further investigation of the module-QTL framework.

DNA methylation patterns in the frontal lobe white matter of multiple system atrophy, Parkinson's disease, and progressive supranuclear palsy: a cross-comparative investigation

Multiple system atrophy (MSA) is a rare neurodegenerative disease characterized by neuronal loss and gliosis, with oligodendroglial cytoplasmic inclusions (GCIs) containing α-synuclein being the primary pathological hallmark. Clinical presentations of MSA overlap with other parkinsonian disorders, such as Parkinson's disease (PD), dementia with Lewy bodies (DLB), and progressive supranuclear palsy (PSP), posing challenges in early diagnosis. Numerous studies have reported alterations in DNA methylation in neurodegenerative diseases, with candidate loci being identified in various parkinsonian disorders including MSA, PD, and PSP. Although MSA and PSP present with substantial white matter pathology, alterations in white matter have also been reported in PD. However, studies comparing the DNA methylation architectures of white matter in these diseases are lacking. We therefore aimed to investigate genome-wide DNA methylation patterns in the frontal lobe white matter of individuals with MSA (n = 17), PD (n = 17), and PSP (n = 16) along with controls (n = 15) using the Illumina EPIC array, to identify shared and disease-specific DNA methylation alterations. Genome-wide DNA methylation profiling of frontal lobe white matter in the three parkinsonian disorders revealed substantial commonalities in DNA methylation alterations in MSA, PD, and PSP. We further used weighted gene correlation network analysis to identify disease-associated co-methylation signatures and identified dysregulation in processes relating to Wnt signaling, signal transduction, endoplasmic reticulum stress, mitochondrial processes, RNA interference, and endosomal transport to be shared between these parkinsonian disorders. Our overall analysis points toward more similarities in DNA methylation patterns between MSA and PD, both synucleinopathies, compared to that between MSA and PD with PSP, which is a tauopathy. Our results also highlight several shared DNA methylation changes and pathways indicative of converging molecular mechanisms in the white matter contributing toward neurodegeneration in all three parkinsonian disorders.

Maternal Serum Metabolomics in Mid-Pregnancy Identifies Lipid Pathways as a Key Link to Offspring Obesity in Early Childhood

Maternal metabolism during pregnancy shapes offspring health via in utero programming. In the Healthy Start study, we identified five subgroups of pregnant women based on conventional metabolic biomarkers: Reference (n = 360); High HDL-C (n = 289); Dyslipidemic-High TG (n = 149); Dyslipidemic-High FFA (n = 180); Insulin Resistant (IR)-Hyperglycemic (n = 87). These subgroups not only captured metabolic heterogeneity among pregnant participants but were also associated with offspring obesity in early childhood, even among women without obesity or diabetes. Here, we utilize metabolomics data to enrich characterization of the metabolic subgroups and identify key compounds driving between-group differences. We analyzed fasting blood samples from 1065 pregnant women at 18 gestational weeks using untargeted metabolomics. We used weighted gene correlation network analysis (WGCNA) to derive a global network based on the Reference subgroup and characterized distinct metabolite modules representative of the different metabolomic profiles. We used the mummichog algorithm for pathway enrichment and identified key compounds that differed across the subgroups. Eight metabolite modules representing pathways such as the carnitine-acylcarnitine translocase system, fatty acid biosynthesis and activation, and glycerophospholipid metabolism were identified. A module that included 189 compounds related to DHA peroxidation, oxidative stress, and sex hormone biosynthesis was elevated in the Insulin Resistant-Hyperglycemic vs. the Reference subgroup. This module was positively correlated with total cholesterol (R:0.10; p-value < 0.0001) and free fatty acids (R:0.07; p-value < 0.05). Oxidative stress and inflammatory pathways may underlie insulin resistance during pregnancy, even below clinical diabetes thresholds. These findings highlight potential therapeutic targets and strategies for pregnancy risk stratification and reveal mechanisms underlying the developmental origins of metabolic disease risk.

Key gene modules and hub genes associated with pyrethroid and organophosphate resistance in Anopheles mosquitoes: a systems biology approach

Indoor residual spraying (IRS) and insecticide-treated nets (ITNs) are the main methods used to control mosquito populations for malaria prevention. The efficacy of these strategies is threatened by the spread of insecticide resistance (IR), limiting the success of malaria control. Studies of the genetic evolution leading to insecticide resistance could enable the identification of molecular markers that can be used for IR surveillance and an improved understanding of the molecular mechanisms associated with IR. This study used a weighted gene co-expression network analysis (WGCNA) algorithm, a systems biology approach, to identify genes with similar co-expression patterns (modules) and hub genes that are potential molecular markers for insecticide resistance surveillance in Kenya and Benin. A total of 20 and 26 gene co-expression modules were identified via average linkage hierarchical clustering from Anopheles arabiensis and An. gambiae, respectively, and hub genes (highly connected genes) were identified within each module. Three specific genes stood out: serine protease, E3 ubiquitin-protein ligase, and cuticular proteins, which were top hub genes in both species and could serve as potential markers and targets for monitoring IR in these malaria vectors. In addition to the identified markers, we explored molecular mechanisms using enrichment maps that revealed a complex process involving multiple steps, from odorant binding and neuronal signaling to cellular responses, immune modulation, cellular metabolism, and gene regulation. Incorporation of these dynamics into the development of new insecticides and the tracking of insecticide resistance could improve the sustainable and cost-effective deployment of interventions.

Differential Regulation of Opsin Gene Expression in Response to Internal and External Stimuli

Determining how internal and external stimuli interact to determine developmental trajectories of traits is a challenge that requires the integration of different subfields of biology. Internal stimuli, such as hormones, control developmental patterns of phenotypic changes, which might be modified by external environmental cues (e.g. plasticity). Thyroid hormone (TH) modulates the timing of opsin gene expression in developing Midas cichlid fish (Amphilophus citrinellus). Moreover, fish reared in red light accelerate this developmental timing compared to fish reared in white light. Hence, we hypothesized that plasticity caused by variation in light conditions has coopted the TH signaling pathway to induce changes in opsin gene expression. We treated Midas cichlids with TH and crossed this treatment with two light conditions, white and red. We observed that not only opsin expression responded similarly to TH and red light but also that, at high TH levels, there is limited capacity for light-induced plasticity. Transcriptomic analysis of the eye showed that genes in the TH pathway were affected by TH, but not by light treatments. Coexpression network analyses further suggested that response to light was independent of the response to TH manipulations. Taken together, our results suggest independent mechanisms mediating development and plasticity during development of opsin gene expression, and that responses to environmental stimuli may vary depending on internal stimuli. This conditional developmental response to external factors depending on internal ones (e.g. hormones) might play a fundamental role in the patterns of phenotypic divergence observed in Midas cichlids and potentially other organisms.

Bulk and Single-cell Transcriptomic Brain Data Identify Overlapping Processes and Cell-types with Human AUD and Mammalian Models of Alcohol Use

This study explores the neurobiological underpinnings of alcohol use disorder (AUD) by integrating bulk and single-cell transcriptomic data from humans, primates, and mice across three brain regions associated with addiction (i.e., prefrontal cortex (PFC), nucleus accumbens (NAc), and central amygdala (CeA)). We compared AUD RNA expression and cell-type abundance from 92 human brain to data from 53 primates and 90 mice engaged in diverse alcohol use paradigms. The findings revealed significant and reproducible correlations between human AUD and mammalian models of alcohol use that vary by tissue, species, and behavioral paradigm. The strongest correlations occurred between primate and mouse models of binge drinking (i.e., high drinking in the dark). Certain primate models demonstrated that the brain RNA correlations with human alcohol use disorder (AUD) were approximately 40% as strong as the correlations observed within human samples themselves. By integrating single-cell transcriptomic data, this study observed decreased oligodendrocyte proportions in the PFC and NAc of human AUD with similar trends in animal models. Gene co-expression network analyses revealed conserved systems associated with human AUD and animal models of heavy/binge alcohol consumption. Gene co-expression networks were enriched for pathways related to inflammation, myelination, and synaptic plasticity and the genes within them accounted for ~20% of the heritability in human alcohol consumption. Identified hub genes were associated with relevant traits (e.g., impulsivity, motivation) in humans and mice. This study sheds light on conserved biological entities underlying AUD and chronic alcohol use, providing insights into the cellular, genetic, and neuromolecular basis across species.

Early life adversity is associated with differential gene expression in immune cells: A cluster-based analysis across an acute psychosocial stressor

Elucidating mechanisms by which early-life adversity (ELA) contributes to increased disease risk is important for mitigating adverse health outcomes. Prior work has found differences in immune cell gene expression related to inflammation and mitochondrial activity. Using a within-person between-group experimental design, we investigated differences in gene expression clusters across acute psychosocial stress and no-stress conditions. Participants were young adults (N = 29, aged 18 - 25 years, 62 % female, 47 % with a history of ELA). Gene expression was assessed in peripheral blood mononuclear cells collected at 8 blood draws spanning two 5-hour sessions (stress vs. no-stress) separated by a week, 4 across each session (number of observations = 221). We applied two unsupervised gene clustering methods - latent profile analysis (LPA) and weighted gene co-expression analysis (WGCNA) - to cluster genes with similar expression patterns across participants. LPA identified 11 clusters, 7 of which were significantly associated with ELA-status. WGCNA identified 5 clusters, 3 of which were significantly associated with ELA-status. LPA- and WGCNA-identified clusters were correlated, and all clusters were highly preserved across sessions and time. There was no significant effect of acute stress on cluster gene expression, but there was a significant effect of time, and significant differences by ELA-status. ELA-associated clusters related to RNA splicing/processing, inflammation, leukocyte differentiation and division, and mitochondrial activity were differentially expressed across time: ELA-exposed individuals showed decreased expression of these clusters at 90-minutes while controls showed increased expression. Our findings replicate previous work in this area and highlight additional mechanisms by which ELA may contribute to disease risk.

Sex-Differential Gene Expression in Developing Human Cortex and Its Intersection With Autism Risk Pathways

Background

Sex-differential biology may contribute to the consistently male-biased prevalence of autism spectrum disorder (ASD). Gene expression differences between males and females in the brain can indicate possible molecular and cellular mechanisms involved, although transcriptomic sex differences during human prenatal cortical development have been incompletely characterized, primarily due to small sample sizes.

Methods

We performed a meta-analysis of sex-differential expression and co-expression network analysis in 2 independent bulk RNA sequencing datasets generated from cortex of 273 prenatal donors without known neuropsychiatric disorders. To assess the intersection between neurotypical sex differences and neuropsychiatric disorder biology, we tested for enrichment of ASD-associated risk genes and expression changes, neuropsychiatric disorder risk genes, and cell type markers within identified sex-differentially expressed genes (sex-DEGs) and sex-differential co-expression modules.

Results

We identified 101 significant sex-DEGs, including Y-chromosome genes, genes impacted by X-chromosome inactivation, and autosomal genes. Known ASD risk genes, implicated by either common or rare variants, did not preferentially overlap with sex-DEGs. We identified 1 male-specific co-expression module enriched for immune signaling that is unique to 1 input dataset.

Conclusions

Sex-differential gene expression is limited in prenatal human cortex tissue, although meta-analysis of large datasets allows for the identification of sex-DEGs, including autosomal genes that encode proteins involved in neural development. Lack of sex-DEG overlap with ASD risk genes in the prenatal cortex suggests that sex-differential modulation of ASD symptoms may occur in other brain regions, at other developmental stages, or in specific cell types, or may involve mechanisms that act downstream from mutation-carrying genes.

Brain Cell-based Genetic Subtyping and Drug Repositioning for Alzheimer Disease

Alzheimer's Disease (AD) is characterized by its complex and heterogeneous etiology and gradual progression, leading to high drug failure rates in late-stage clinical trials. In order to better stratify individuals at risk for AD and discern potential therapeutic targets we employed a novel procedure utilizing cell-based co-regulated gene networks and polygenic risk scores (cbPRSs). After defining genetic subtypes using extremes of cbPRS distributions, we evaluated correlations of the genetic subtypes with previously defined AD subtypes defined on the basis of domain-specific cognitive functioning and neuroimaging biomarkers. Employing a PageRank algorithm, we identified priority gene targets for the genetic subtypes. Pathway analysis of priority genes demonstrated associations with neurodegeneration and suggested candidate drugs currently utilized in diabetes, hypertension, and epilepsy for repositioning in AD. Experimental validation utilizing human induced pluripotent stem cell (hiPSC)-derived astrocytes demonstrated the modifying effects of estradiol, levetiracetam, and pioglitazone on expression of APOE and complement C4 genes, suggesting potential repositioning for AD.

RNA sequencing and gene co-expression network of in vitro matured oocytes and blastocysts of buffalo

In reproductive technologies, uncovering the molecular aspects of oocyte and embryo competence under different conditions is crucial for refining protocols and enhancing efficiency. RNA-seq generates high-throughput data and provides transcriptomes that can undergo additional computational analyses. This study presented the transcriptomic profiles of in vitro matured oocytes and blastocysts produced in vitro from buffalo crossbred (Bubalus bubalis), coupled with gene co-expression and module preservation analysis. Cumulus Oophorus Complexes, obtained from slaughterhouse-derived ovaries, were subjected to in vitro maturation to yield metaphase II oocytes (616) or followed in vitro fertilization and culture to yield blastocysts for sequencing (526). Oocyte maturation (72%, ±3.34 sd) and embryo development (21.3%, ±4.18 sd) rates were obtained from three in vitro embryo production routines following standard protocols. Sequencing of 410 metaphase II oocytes and 70 hatched blastocysts (grade 1 and 2) identified a total of 13,976 genes, with 62% being ubiquitously expressed (8,649). Among them, the differentially expressed genes (4,153) and the strongly variable genes with the higher expression (fold-change above 11) were highlighted in oocytes (BMP15, UCHL1, WEE1, NLRPs, KPNA7, ZP2, and ZP4) and blastocysts (APOA1, KRT18, ANXA2, S100A14, SLC34A2, PRSS8 and ANXA2) as representative indicators of molecular quality. Additionally, genes exclusively found in oocytes (224) and blastocysts (2,200) with specific biological functions were identified. Gene co-expression network and module preservation analysis revealed strong preservation of functional modules related to exosome components, steroid metabolism, cell proliferation, and morphogenesis. However, cell cycle and amino acid transport modules exhibited weak preservation, which may reflect differences in embryo development kinetics and the activation of cell signaling pathways between buffalo and bovine. This comprehensive transcriptomic profile serves as a valuable resource for assessing the molecular quality of buffalo oocytes and embryos in future in vitro embryo production assays.

The role of mitochondria in sex- and age-specific gene expression in a species without sex chromosomes

Mitochondria perform an array of functions, many of which involve interactions with gene products encoded by the nucleus. These mitochondrial functions, particularly those involving energy production, can be expected to differ between sexes and across ages. Here, we measured mitochondrial effects on sex- and age-specific gene expression in parental and reciprocal F1 hybrids between allopatric populations of Tigriopus californicus with over 20% mitochondrial DNA divergence. Because the species lacks sex chromosomes, sex-biased mitochondrial effects are not confounded by the effects of sex chromosomes. Results revealed pervasive sex differences in mitochondrial effects, including effects on energetics and aging involving nuclear interactions throughout the genome. Using single-individual RNA sequencing, sex differences were found to explain more than 80% of the variance in gene expression. Males had higher expression of mitochondrial genes and mitochondrially targeted proteins (MTPs) involved in oxidative phosphorylation (OXPHOS), while females had elevated expression of non-OXPHOS MTPs, indicating strongly sex-dimorphic energy metabolism at the whole organism level. Comparison of reciprocal F1 hybrids allowed insights into the nature of mito-nuclear interactions, showing both mitochondrial effects on nuclear expression, and nuclear effects on mitochondrial expression. While based on a small set of crosses, sex-specific increases in mitochondrial expression with age were associated with longer life. Network analyses identified nuclear components of strong mito-nuclear interactions and found them to be sexually dimorphic. These results highlight the profound impact of mitochondria and mito-nuclear interactions on sex- and age-specific gene expression.

Transcriptomic Analysis of Hub Genes Reveals Associated Inflammatory Pathways in Estrogen-Dependent Gynecological Diseases

Gynecological diseases are triggered by aberrant molecular pathways that alter gene expression, hormonal balance, and cellular signaling pathways, which may lead to long-term physiological consequences. This study was able to identify highly preserved modules and key hub genes that are mainly associated with gynecological diseases, represented by endometriosis (EM), ovarian cancer (OC), cervical cancer (CC), and endometrial cancer (EC), through the weighted gene co-expression network analysis (WGCNA) of microarray datasets sourced from the Gene Expression Omnibus (GEO) database. Five highly preserved modules were observed across the EM (GSE51981), OC (GSE63885), CC (GSE63514), and EC (GSE17025) datasets. The functional annotation and pathway enrichment analysis revealed that the highly preserved modules were heavily involved in several inflammatory pathways that are associated with transcription dysregulation, such as NF-kB signaling, JAK-STAT signaling, MAPK-ERK signaling, and mTOR signaling pathways. Furthermore, the results also include pathways that are relevant in gynecological disease prognosis through viral infections. Mutations in the ESR1 gene that encodes for ERα, which were shown to also affect signaling pathways involved in inflammation, further indicate its importance in gynecological disease prognosis. Potential drugs were screened through the Drug Repurposing Encyclopedia (DRE) based on the up-and downregulated hub genes, wherein a bacterial ribosomal subunit inhibitor and a benzodiazepine receptor agonist were the top candidates. Other drug candidates include a dihydrofolate reductase inhibitor, glucocorticoid receptor agonists, cholinergic receptor agonists, selective serotonin reuptake inhibitors, sterol demethylase inhibitors, a bacterial antifolate, and serotonin receptor antagonist drugs which have known anti-inflammatory effects, demonstrating that the gene network highlights specific inflammatory pathways as a therapeutic avenue in designing drug candidates for gynecological diseases.

Single-cell transcriptomics reveals stage- and side-specificity of gene modules in colorectal cancer

BACKGROUND

An understanding of mechanisms underlying colorectal cancer (CRC) development and progression is yet to be fully elucidated. This study aims to employ network theoretic approaches to analyse single cell transcriptomic data from CRC to better characterize its progression and sided-ness.

METHODS

We utilized a recently published single-cell RNA sequencing data (GEO-GSE178341) and parsed the cell X gene data by stage and side (right and left colon). Using Weighted Gene Co-expression Network Analysis (WGCNA), we identified gene modules with varying preservation levels (weak or strong) of network topology between early (pT1) and late stages (pT234), and between right and left colons. Spearman's rank correlation (ρ) was used to assess the similarity or dissimilarity in gene connectivity.

RESULTS

Equalizing cell counts across different stages, we detected 13 modules for the early stage, two of which were non-preserved in late stages. Both non-preserved modules displayed distinct gene connectivity patterns between the early and late stages, characterized by low ρ values. One module predominately dealt with myeloid cells, with genes mostly enriched for cytokine-cytokine receptor interaction potentiallystimulating myeloid cells to participate in angiogenesis. The second module, representing a subset of epithelial cells, was mainly enriched for carbohydrate digestion and absorption, influencing the gut microenvironment through the breakdown of carbohydrates. In the comparison of left vs. right colons, two of 12 modules identified in the right colon were non-preserved in the left colon. One captured a small fraction of epithelial cells and was enriched for transcriptional misregulation in cancer, potentially impacting communication between epithelial cells and the tumor microenvironment. The other predominantly contained B cells with a crucial role in maintaining human gastrointestinal health and was enriched for B-cell receptor signalling pathway.

CONCLUSIONS

We identified modules with topological and functional differences specific to cell types between the early and late stages, and between the right and left colons. This study enhances the understanding of roles played by different cell types at different stages and sides, providing valuable insights for future studies focused on the diagnosis and treatment of CRC.

Sex affects transcriptional associations with schizophrenia across the dorsolateral prefrontal cortex, hippocampus, and caudate nucleus

Schizophrenia is a complex neuropsychiatric disorder with sexually dimorphic features, including differential symptomatology, drug responsiveness, and male incidence rate. Prior large-scale transcriptome analyses for sex differences in schizophrenia have focused on the prefrontal cortex. Analyzing BrainSeq Consortium data (caudate nucleus: n = 399, dorsolateral prefrontal cortex: n = 377, and hippocampus: n = 394), we identified 831 unique genes that exhibit sex differences across brain regions, enriched for immune-related pathways. We observed X-chromosome dosage reduction in the hippocampus of male individuals with schizophrenia. Our sex interaction model revealed 148 junctions dysregulated in a sex-specific manner in schizophrenia. Sex-specific schizophrenia analysis identified dozens of differentially expressed genes, notably enriched in immune-related pathways. Finally, our sex-interacting expression quantitative trait loci analysis revealed 704 unique genes, nine associated with schizophrenia risk. These findings emphasize the importance of sex-informed analysis of sexually dimorphic traits, inform personalized therapeutic strategies in schizophrenia, and highlight the need for increased female samples for schizophrenia analyses.

Parthenogenetic Stick Insects Exhibit Signatures of Preservation in the Molecular Architecture of Male Reproduction

After the loss of a trait, theory predicts that the molecular machinery underlying its phenotypic expression should decay. Yet, empirical evidence is contrasting. Here, we test the hypotheses that (i) the molecular ground plan of a lost trait could persist due to pleiotropic effects on other traits and (ii) that gene co-expression network architecture could constrain individual gene expression. Our testing ground has been the Bacillus stick insect species complex, which contains close relatives that are either bisexual or parthenogenetic. After the identification of genes expressed in male reproductive tissues in a bisexual species, we investigated their gene co-expression network structure in two parthenogenetic species. We found that gene co-expression within the male gonads was partially preserved in parthenogens. Furthermore, parthenogens did not show relaxed selection on genes upregulated in male gonads in the bisexual species. As these genes were mostly expressed in female gonads, this preservation could be driven by pleiotropic interactions and an ongoing role in female reproduction. Connectivity within the network also played a key role, with highly connected-and more pleiotropic-genes within male gonad also having a gonad-biased expression in parthenogens. Our findings provide novel insight into the mechanisms which could underlie the production of rare males in parthenogenetic lineages; more generally, they provide an example of the cryptic persistence of a lost trait molecular architecture, driven by gene pleiotropy on other traits and within their co-expression network.

Late-Stage Skeletal Muscle Transcriptome in Duchenne muscular dystrophy shows a BMP4-Induced Molecular Signature

Duchenne muscular dystrophy (DMD) is a fatal X-linked recessive disease due to loss-of-function mutations in the DYSTROPHIN gene. DMD-related skeletal muscle wasting is typified by an aberrant immune response involving upregulation of TGFβ family of cytokines. We previously demonstrated that bone morphogenetic protein 4 (BMP4) is increased in DMD and BMP4 stimulation induces a 20-fold upregulation of Smad8 transcription. However, the role of BMP4 in severely affected DMD skeletal muscle is unknown. We hypothesized that transcriptomic signatures in severely affected human DMD skeletal muscle are driven by BMP4 signaling. Transcriptomes from skeletal muscle biopsies of late-stage DMD vs. non-DMD controls and C2C12 muscle cells with or without BMP4 stimulation were generated by RNA-Seq and analyzed for single transcript differential expression as well as by Ingenuity Pathway Analysis and weighted gene co-expression network analyses. A total of 2,328 and 5,291 transcripts in the human muscle and C2C12 muscle cells, respectively, were differentially expressed. We identified an overlapping molecular signature of 1,027 genes dysregulated in DMD muscle that were induced in BMP4-stimulated C2C12 muscle cells. Highly upregulated DMD transcripts that overlapped with BMP4-stimulated C2C12 muscle cells included ADAMTS3, HCAR2, SERPING1, SMAD8 , and UNC13C. The DMD transcriptome was characterized by dysregulation of pathways involving immune function, extracellular matrix remodeling, and metabolic/mitochondrial function. In summary, we define a late-stage DMD skeletal muscle transcriptome that substantially overlaps with the BMP4-induced molecular signature in C2C12 muscle cells. This supports BMP4 as a disease-driving regulator of transcriptomic changes in late-stage DMD skeletal muscle and expands our understanding of the evolution of dystrophic signaling pathways and their associated gene networks that could be explored for therapeutic development.

Identifying Candidate Gene Drivers Associated with Relapse in Pediatric T-Cell Acute Lymphoblastic Leukemia Using a Gene Co-Expression Network Approach

Pediatric T-cell Acute Lymphoblastic Leukemia (T-ALL) relapses are still associated with a dismal outcome, justifying the search for new therapeutic targets and relapse biomarkers. Using single-cell RNA sequencing (scRNAseq) data from three paired samples of pediatric T-ALL at diagnosis and relapse, we first conducted a high-dimensional weighted gene co-expression network analysis (hdWGCNA). This analysis highlighted several gene co-expression networks (GCNs) and identified relapse-associated hub genes, which are considered potential driver genes. Shared relapse-expressed genes were found to be related to antigen presentation (HLA, B2M), cytoskeleton remodeling (TUBB, TUBA1B), translation (ribosomal proteins, EIF1, EEF1B2), immune responses (MIF, EMP3), stress responses (UBC, HSP90AB1/AA1), metabolism (FTH1, NME1/2, ARCL4C), and transcriptional remodeling (NF-κB family genes, FOS-JUN, KLF2, or KLF6). We then utilized sparse partial least squares discriminant analysis to select from a pool of 481 unique leukemic hub genes, which are the genes most discriminant between diagnosis and relapse states (comprising 44, 35, and 31 genes, respectively, for each patient). Applying a Cox regression method to these patient-specific genes, along with transcriptomic and clinical data from the TARGET-ALL AALL0434 cohort, we generated three model gene signatures that efficiently identified relapsed patients within the cohort. Overall, our approach identified new potential relapse-associated genes and proposed three model gene signatures associated with lower survival rates for high-score patients.

Large-scale network analysis of the cerebrospinal fluid proteome identifies molecular signatures of frontotemporal lobar degeneration

The pathophysiological mechanisms driving disease progression of frontotemporal lobar degeneration (FTLD) and corresponding biomarkers are not fully understood. We leveraged aptamer-based proteomics (> 4,000 proteins) to identify dysregulated communities of co-expressed cerebrospinal fluid proteins in 116 adults carrying autosomal dominant FTLD mutations (C9orf72, GRN, MAPT) compared to 39 noncarrier controls. Network analysis identified 31 protein co-expression modules. Proteomic signatures of genetic FTLD clinical severity included increased abundance of RNA splicing (particularly in C9orf72 and GRN) and extracellular matrix (particularly in MAPT) modules, as well as decreased abundance of synaptic/neuronal and autophagy modules. The generalizability of genetic FTLD proteomic signatures was tested and confirmed in independent cohorts of 1) sporadic progressive supranuclear palsy-Richardson syndrome and 2) frontotemporal dementia spectrum syndromes. Network-based proteomics hold promise for identifying replicable molecular pathways in adults living with FTLD. 'Hub' proteins driving co-expression of affected modules warrant further attention as candidate biomarkers and therapeutic targets.

Neurogenomic landscape associated with status-dependent cooperative behaviour

The neurogenomic mechanisms mediating male-male reproductive cooperative behaviours remain unknown. We leveraged extensive transcriptomic and behavioural data on a neotropical bird species (Pipra filicauda) that performs cooperative courtship displays to understand these mechanisms. In this species, the cooperative display is modulated by testosterone, which promotes cooperation in non-territorial birds, but suppresses cooperation in territory holders. We sought to understand the neurogenomic underpinnings of three related traits: social status, cooperative display behaviour and testosterone phenotype. To do this, we profiled gene expression in 10 brain nuclei spanning the social decision-making network (SDMN), and two key endocrine tissues that regulate social behaviour. We associated gene expression with each bird's behavioural and endocrine profile derived from 3 years of repeated measures taken from free-living birds in the Ecuadorian Amazon. We found distinct landscapes of constitutive gene expression were associated with social status, testosterone phenotype and cooperation, reflecting the modular organization and engagement of neuroendocrine tissues. Sex-steroid and neuropeptide signalling appeared to be important in mediating status-specific relationships between testosterone and cooperation, suggesting shared regulatory mechanisms with male aggressive and sexual behaviours. We also identified differentially regulated genes involved in cellular activity and synaptic potentiation, suggesting multiple mechanisms underpin these genomic states. Finally, we identified SDMN-wide gene expression differences between territorial and floater males that could form the basis of 'status-specific' neurophysiological phenotypes, potentially mediated by testosterone and growth hormone. Overall, our findings provide new, systems-level insights into the mechanisms of cooperative behaviour and suggest that differences in neurogenomic state are the basis for individual differences in social behaviour.

Post-translational modifications linked to preclinical Alzheimer's disease-related pathological and cognitive changes

INTRODUCTION

In this study, we leverage proteomic techniques to identify communities of proteins underlying Alzheimer's disease (AD) risk among clinically unimpaired (CU) older adults.

METHODS

We constructed a protein co-expression network using 3869 cerebrospinal fluid (CSF) proteins quantified by SomaLogic, Inc., in a cohort of participants along the AD clinical spectrum. We then replicated this network in an independent cohort of CU older adults and related these modules to clinically-relevant outcomes.

RESULTS

We discovered modules enriched for phosphorylation and ubiquitination that were associated with abnormal amyloid status, as well as p-tau181 (M4: β = 2.44, p < 0.001, M7: β = 2.57, p < 0.001) and executive function performance (M4: β = -2.00, p = 0.005, M7: β = -2.39, p < 0.001).

DISCUSSION

In leveraging CSF proteomic data from individuals spanning the clinical spectrum of AD, we highlight the importance of post-translational modifications for early cognitive and pathological changes.

A leaky gut dysregulates gene networks in the brain associated with immune activation, oxidative stress, and myelination in a mouse model of colitis

The gut and brain are increasingly linked in human disease, with neuropsychiatric conditions classically attributed to the brain showing an involvement of the intestine and inflammatory bowel diseases (IBDs) displaying an ever-expanding list of neurological comorbidities. To identify molecular systems that underpin this gut-brain connection and thus discover therapeutic targets, experimental models of gut dysfunction must be evaluated for brain effects. In the present study, we examine disturbances along the gut-brain axis in a widely used murine model of colitis, the dextran sodium sulfate (DSS) model, using high-throughput transcriptomics and an unbiased network analysis strategy coupled with standard biochemical outcome measures to achieve a comprehensive approach to identify key disease processes in both colon and brain. We examine the reproducibility of colitis induction with this model and its resulting genetic programs during different phases of disease, finding that DSS-induced colitis is largely reproducible with a few site-specific molecular features. We focus on the circulating immune system as the intermediary between the gut and brain, which exhibits an activation of pro-inflammatory innate immunity during colitis. Our unbiased transcriptomics analysis provides supporting evidence for immune activation in the brain during colitis, suggests that myelination may be a process vulnerable to increased intestinal permeability, and identifies a possible role for oxidative stress and brain oxygenation. Overall, we provide a comprehensive evaluation of multiple systems in a prevalent experimental model of intestinal permeability, which will inform future studies using this model and others, assist in the identification of druggable targets in the gut-brain axis, and contribute to our understanding of the concomitance of intestinal and neuropsychiatric dysfunction.

Gene co-expression patterns in Atlantic salmon adipose tissue provide a molecular link among seasonal changes, energy balance and age at maturity

Sexual maturation in many fishes requires a major physiological change that involves a rapid transition between energy storage and usage. In Atlantic salmon, this transition for the initiation of maturation is tightly controlled by seasonality and requires a high-energy status. Lipid metabolism is at the heart of this transition since lipids are the main energy storing molecules. The balance between lipogenesis (lipid accumulation) and lipolysis (lipid use) determines energy status transitions. A genomic region containing a transcription co-factor of the Hippo pathway, vgll3, is the main determinant of maturation timing in Atlantic salmon. Interestingly, vgll3 acts as an inhibitor of adipogenesis in mice and its genotypes are potentially associated with seasonal heterochrony in lipid storage and usage in juvenile Atlantic salmon. Here, we explored changes in expression of more than 300 genes directly involved in the processes of adipogenesis, lipogenesis and lipolysis, as well as the Hippo pathway in the adipose tissue of immature and mature Atlantic salmon with distinct vgll3 genotypes. We found molecular evidence consistent with a scenario in which immature males with different vgll3 genotypes exhibit contrasting seasonal dynamics in their lipid profiles. We also identified components of the Hippo signalling pathway as potential major drivers of vgll3 genotype-specific differences in adipose tissue gene expression. This study demonstrates the importance of adipose gene expression patterns for directly linking environmental changes with energy balance and age at maturity through genetic factors bridging lipid metabolism, seasonality and sexual maturation.

A miR-137-Related Biological Pathway of Risk for Schizophrenia Is Associated With Human Brain Emotion Processing

BACKGROUND

miR-137 is a microRNA involved in brain development, regulating neurogenesis and neuronal maturation. Genome-wide association studies have implicated miR-137 in schizophrenia risk but do not explain its involvement in brain function and underlying biology. Polygenic risk for schizophrenia mediated by miR-137 targets is associated with working memory, although other evidence points to emotion processing. We characterized the functional brain correlates of miR-137 target genes associated with schizophrenia while disentangling previously reported associations of miR-137 targets with working memory and emotion processing.

METHODS

Using RNA sequencing data from postmortem prefrontal cortex (N = 522), we identified a coexpression gene set enriched for miR-137 targets and schizophrenia risk genes. We validated the relationship of this set to miR-137 in vitro by manipulating miR-137 expression in neuroblastoma cells. We translated this gene set into polygenic scores of coexpression prediction and associated them with functional magnetic resonance imaging activation in healthy volunteers (n1 = 214; n2 = 136; n3 = 2075; n4 = 1800) and with short-term treatment response in patients with schizophrenia (N = 427).

RESULTS

In 4652 human participants, we found that 1) schizophrenia risk genes were coexpressed in a biologically validated set enriched for miR-137 targets; 2) increased expression of miR-137 target risk genes was mediated by low prefrontal miR-137 expression; 3) alleles that predict greater gene set coexpression were associated with greater prefrontal activation during emotion processing in 3 independent healthy cohorts (n1, n2, n3) in interaction with age (n4); and 4) these alleles predicted less improvement in negative symptoms following antipsychotic treatment in patients with schizophrenia.

CONCLUSIONS

The functional translation of miR-137 target gene expression linked with schizophrenia involves the neural substrates of emotion processing.

Gene expression and alternative splicing contribute to adaptive divergence of ecotypes

Regulation of gene expression is a critical link between genotype and phenotype explaining substantial heritable variation within species. However, we are only beginning to understand the ways that specific gene regulatory mechanisms contribute to adaptive divergence of populations. In plants, the post-transcriptional regulatory mechanism of alternative splicing (AS) plays an important role in both development and abiotic stress response, making it a compelling potential target of natural selection. AS allows organisms to generate multiple different transcripts/proteins from a single gene and thus may provide a source of evolutionary novelty. Here, we examine whether variation in alternative splicing and gene expression levels might contribute to adaptation and incipient speciation of dune-adapted prairie sunflowers in Great Sand Dunes National Park, Colorado, USA. We conducted a common garden experiment to assess transcriptomic variation among ecotypes and analyzed differential expression, differential splicing, and gene coexpression. We show that individual genes are strongly differentiated for both transcript level and alternative isoform proportions, even when grown in a common environment, and that gene coexpression networks are disrupted between ecotypes. Furthermore, we examined how genome-wide patterns of sequence divergence correspond to divergence in transcript levels and isoform proportions and find evidence for both cis and trans-regulation. Together, our results emphasize that alternative splicing has been an underappreciated mechanism providing source material for natural selection at short evolutionary time scales.

A network-based transcriptomic landscape of HepG2 cells uncovering causal gene-cytotoxicity interactions underlying drug-induced liver injury

Drug-induced liver injury (DILI) remains the main reason for drug development attritions largely due to poor mechanistic understanding. Toxicogenomic to interrogate the mechanism of DILI has been broadly performed. Gene coregulation network-based transcriptome analysis is a bioinformatics approach that potentially contributes to improve mechanistic interpretation of toxicogenomic data. Here we performed an extensive concentration time course response-toxicogenomic study in the HepG2 cell line exposed to 20 DILI compounds, 7 reference compounds for stress response pathways, and 10 agonists for cytokines and growth factor receptors. We performed whole transcriptome targeted RNA sequencing to more than 500 conditions and applied weighted gene coregulated network analysis to the transcriptomics data followed by the identification of gene coregulated networks (modules) that were strongly modulated upon the exposure of DILI compounds. Preservation analysis on the module responses of HepG2 and PHH demonstrated highly preserved adaptive stress response gene coregulated networks. We correlated gene coregulated networks with cell death onset and causal relationships of 67 critical target genes of these modules with the onset of cell death was evaluated using RNA interference screening. We identified GTPBP2, HSPA1B, IRF1, SIRT1, and TSC22D3 as essential modulators of DILI compound-induced cell death. These genes were also induced by DILI compounds in PHH. Altogether, we demonstrate the application of large transcriptome datasets combined with network-based analysis and biological validation to uncover the candidate determinants of DILI.

Integrative brain omics approach reveals key role for sn-1 lysophosphatidylethanolamine in Alzheimer's dementia

The biology of individual lipid species and their relevance in Alzheimer's disease (AD) remains incompletely understood. We utilized non-targeted mass spectrometry to examine brain lipids variations across 316 post-mortem brains from participants in the Religious Orders Study (ROS) or Rush Memory and Aging Project (MAP) cohorts classified as either control, asymptomatic AD (AAD), or symptomatic AD (SAD) and integrated the lipidomics data with untargeted proteomic characterization on the same individuals. Lipid enrichment analysis and analysis of variance identified significantly lower abundance of lysophosphatidylethanolamine (LPE) and lysophosphatidylcholine (LPC) species in SAD than controls or AAD. Lipid-protein co-expression network analyses revealed that lipid modules consisting of LPE and LPC exhibited a significant association to protein modules associated with MAPK/metabolism, post-synaptic density, and Cell-ECM interaction pathways and were associated with better antemortem cognition and with neuropathological changes seen in AD. Particularly, LPE 22:6 [sn-1] levels are significantly decreased across AD cases (SAD) and show the most influence on protein changes compared to other lysophospholipid species. LPE 22:6 may be a lipid signature for AD and could be leveraged as potential therapeutic or dietary targets for AD.

Renal transcriptome analysis of uninephrectomized db/db mice identified a mechanism for the transition to severe diabetic nephropathy

Diabetic nephropathy (DN), included in diabetic kidney disease (DKD), is a primary driver of end-stage renal disease (ESRD) leading to dialysis treatment. To develop new therapeutic drugs to prevent ESRD and avoid dialysis treatment, insight into DKD pathophysiology and animal models suitable for drug efficacy testing are needed. In this study, transcriptome analysis of kidneys from 26-week-old and 35-week-old uninephrectomized (UNX) db/db mice was used to identify the pathways that affect the deterioration of renal function in db/db mice. Differentially expressed genes suggested that there was increased interferon (IFN)-γ signaling during the 26 to 35-week period. Modules that changed between 26 and 35 weeks of age extracted by weighted gene co-expression network analysis (WGCNA) suggested increased the tumor necrosis factor (TNF)-α and nuclear factor-kappa B (NF-κB) signaling pathway in component cells of glomeruli. The protein-protein interaction (PPI) network analysis identified Cxcl16 as a hub gene for those signaling pathways, and it was shown that the pathways in this module changed when the glomerular filtration rate decreased in patients with DN. These results suggested the possibility that signaling mediated by Cxcl16 induced by IFN-γ and TNF-α between 26 and 35 weeks of age leads to renal fibrosis, resulting in severe disease. Drugs that target such pathways can be options for developing drugs for DN. We also think that the uninephrectomized db/db mouse can be used as an animal model of severe DKD and to evaluate efficacy in patients with DN.

Large-scale integrative analysis of juvenile idiopathic arthritis for new insight into its pathogenesis

BACKGROUND

Juvenile idiopathic arthritis (JIA) is one of the most prevalent rheumatic disorders in children and is classified as an autoimmune disease (AID). While a robust genetic contribution to JIA etiology has been established, the exact pathogenesis remains unclear.

METHODS

To prioritize biologically interpretable susceptibility genes and proteins for JIA, we conducted transcriptome-wide and proteome-wide association studies (TWAS/PWAS). Then, to understand the genetic architecture of JIA, we systematically analyzed single-nucleotide polymorphism (SNP)-based heritability, a signature of natural selection, and polygenicity. Next, we conducted HLA typing using multi-ethnicity RNA sequencing data. Additionally, we examined the T cell receptor (TCR) repertoire at a single-cell level to explore the potential links between immunity and JIA risk.

RESULTS

We have identified 19 TWAS genes and two PWAS proteins associated with JIA risks. Furthermore, we observe that the heritability and cell type enrichment analysis of JIA are enriched in T lymphocytes and HLA regions and that JIA shows higher polygenicity compared to other AIDs. In multi-ancestry HLA typing, B*45:01 is more prevalent in African JIA patients than in European JIA patients, whereas DQA1*01:01, DQA1*03:01, and DRB1*04:01 exhibit a higher frequency in European JIA patients. Using single-cell immune repertoire analysis, we identify clonally expanded T cell subpopulations in JIA patients, including CXCL13+BHLHE40+ TH cells which are significantly associated with JIA risks.

CONCLUSION

Our findings shed new light on the pathogenesis of JIA and provide a strong foundation for future mechanistic studies aimed at uncovering the molecular drivers of JIA.

Global analysis of iron metabolism-related genes identifies potential mechanisms of gliomagenesis and reveals novel targets

AIMS

This study aimed to investigate key regulators of aberrant iron metabolism in gliomas, and evaluate their effect on biological functions and clinical translational relevance.

METHODS

We used transcriptomic data from multiple cross-platform glioma cohorts to identify key iron metabolism-related genes (IMRGs) based on a series of bioinformatic and machine learning methods. The associations between IMRGs and prognosis, mesenchymal phenotype, and genomic alterations were analyzed in silico. The performance of the IMRGs-based signature in predicting temozolomide (TMZ) treatment sensitivity was evaluated. In vitro and in vivo experiments were used to explore the biological functions of these key IMRGs.

RESULTS

HMOX1, LTF, and STEAP3 were identified as the most essential IMRGs in gliomas. The expression levels of these genes were strongly related to clinicopathological and molecular features. The robust IMRG-based gene signature could be used for prognosis prediction. These genes facilitate mesenchymal transformation, driver gene mutations, and oncogenic alterations in gliomas. The gene signature was also associated with TMZ resistance. HMOX1, LTF, and STEAP3 knockdown in glioma cells significantly reduced cell proliferation, colony formation, migration, and malignant invasion.

CONCLUSION

The study presented a comprehensive view of key regulators underpinning iron metabolism in gliomas and provided new insights into novel therapeutic approaches.

Parameterization of asymmetric sigmoid functions in weighted gene co-expression network analysis

In most the biological contexts, examining gene expressions at the genomic level gives more accurate results than examining genes individually. It can improve understanding of the molecular mechanisms that cause molecular alterations. Weighted gene co-expression network analysis (WGCNA), which has recently been widely used to cluster transcriptomic datasets, implements a soft thresholding procedure using power function. However, these functions may sometimes exaggerate minor differences in expression correlations. We have previously proposed to use asymmetric sigmoid functions in soft thresholding as an alternative solution. However, the number of variables in asymmetric sigmoid functions may vary and parameterization can be problematic. In this study, we have introduced a systematic procedure for parameterizing asymmetric sigmoid function to ease using it as an alternative soft-thresholding solution in WGCNA. The efficiency of the employment was shown on four different COVID-19 datasets, on a yeast dataset, and on an E.Coli dataset. The results indicate that this approach provides biologically plausible associations for the resulting modules.

Disentangling specific and unspecific components of innate immune memory in a copepod-tapeworm system

Evidence that the innate immune system can respond with forms of memory upon reinfection has been accumulating over the past few years. These phenomena of "immune priming" in invertebrates, and "trained immunity" in vertebrates, are contrary to previous belief that immune memory and specificity are restricted to the adaptive immune system. However, while trained immunity is usually a response with rather low specificity, immune priming has shown highly specific responses in certain species. To date, it is largely unknown how specificity in innate immune memory can be achieved in response to different parasite types. Here, we revisited a system where an exceptionally high degree of innate immune specificity had been demonstrated for the first time, consisting of the copepod Macrocyclops albidus and its natural parasite, the tapeworm Schistocephalus solidus. Using homologous (same family) vs. heterologous (different family) priming-challenge experiments, we first confirm that copepods exposed to the same parasite family benefit from reduced secondary infections. We further focused on exposed-but-not-infected copepods in primary exposure to employ a transcriptomic approach, distinguishing between immunity that was either specific or unspecific regarding the discrimination between tapeworm types. A weighted gene co-expression network (WGCN) revealed differences between specific and unspecific immunity; while both involved histone modification regulation, specific immunity involved gene-splicing factors, whereas unspecific immunity was primarily involved in metabolic shift. We found a functional enrichment in spliceosome in specific immunity, whereas oxidative phosphorylation and carbon metabolism were enriched in unspecific immunity. Our findings allow discrimination of specific and unspecific components of an innate immune memory, based on gene expression networks, and deepen our understanding of basic aspects of immune systems.

Population-based high-dimensional analyses identify multiple intrinsic characters for cancer vaccines against lung squamous cell carcinoma

In lung squamous cell carcinoma (LUSC), current cancer vaccines show promising effects, despite a lack of benefit for a large number of patients. We first identified the tumor antigens into shared and private antigens, and determined the population by clustering analysis in public datasets. For vaccine development, The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) were collected. WGCNA method was furthermore applied to construct a consensus gene co-expression network based on TCGA and CPTAC datasets. The main analyses in bulk sequencing included survival, clinical features, tumor microenvironment (TME), and pathways enrichment. In addition, single-cell RNA (scRNA) analysis of cancer epithelium dissected consensus subtype. We identified the ideal population for cancer vaccines, and candidate neoantigens including AOC1, COL5A2, LGI2, and POSTN. According to subtype analysis, Lung squamous 1 (LSQ1) type exhibited a higher tumor mutational load (TMB) and copy number but no immune infiltration, whereas lung squamous 2 (LSQ2) tumors had a higher global methylation level and more fibroblasts but had less stemness. Meanwhile, trajectory analysis further revealed that the evolution of TME influenced prognosis. We emphasized specific pathways or targets with the potential for combination immunotherapy by consensus network and single-cell RNA analyses. Anti-androgen therapy has been validated in vitro experiments of LUSC as proof of concept. In conclusion, LSQ1 was linked to immune exclusion and might be utilized for vaccination, while LSQ2 was linked to immune dysfunction and could be used for programmed cell death protein 1 (PD1) blocking therapy.

A Glucocorticoid-Sensitive Hippocampal Gene Network Moderates the Impact of Early-Life Adversity on Mental Health Outcomes

BACKGROUND

Early stress increases the risk for psychiatric disorders. Glucocorticoids are stress mediators that regulate transcriptional activity and morphology in the hippocampus, which is implicated in the pathophysiology of multiple psychiatric conditions. We aimed to establish the relevance of hippocampal glucocorticoid-induced transcriptional activity as a mediator of the effects of early life on later psychopathology in humans.

METHODS

RNA sequencing was performed with anterior and posterior hippocampal dentate gyrus from adult female macaques (n = 12/group) that were chronically treated with betamethasone (glucocorticoid receptor agonist) or vehicle. Coexpression network analysis identified a preserved gene network in the posterior hippocampal dentate gyrus that was strongly associated with glucocorticoid exposure. The single nucleotide polymorphisms in the genes in this network were used to create an expression-based polygenic score in humans.

RESULTS

The expression-based polygenic score significantly moderated the association between early adversity and psychotic disorders in adulthood (UK Biobank, women, n = 44,519) and on child peer relations (ALSPAC [Avon Longitudinal Study of Parents and Children], girls, n = 1666 for 9-year-olds and n = 1594 for 11-year-olds), an endophenotype for later psychosis. Analyses revealed that this network was enriched for glucocorticoid-induced epigenetic remodeling in human hippocampal cells. We also found a significant association between single nucleotide polymorphisms from the expression-based polygenic score and adult brain gray matter density.

CONCLUSIONS

We provide an approach for the use of transcriptomic data from animal models together with human data to study the impact of environmental influences on mental health. The results are consistent with the hypothesis that hippocampal glucocorticoid-related transcriptional activity mediates the effects of early adversity on neural mechanisms implicated in psychiatric disorders.

Gene expression signatures of stepwise progression of Hepatocellular Carcinoma

The molecular pathogenesis of Hepatocellular Carcinoma (HCC) is a complex process progressing from premalignant stages to cancer in a stepwise manner. Mostly, HCC is detected at advanced stages, leading to high mortality rates. Hence, characterising the molecular underpinnings of HCC from normal to cancer state through precancerous state may help in early detection and improve its prognosis and treatment. In this work, we analysed the transcriptomic profile of tumour and premalignant samples from HCC or chronic liver disease patients, who had undergone either total or partial hepatectomy. The normal samples from patients with metastatic cancer/polycystic liver disease/ cholangiocarcinoma were also included. A gene co-expression network approach was applied to identify hierarchical changes: modules, pathways, and genes related to different trajectories of HCC and patient survival. Our analysis shows that the progression from premalignant conditions to tumour is accompanied by differences in the downregulation of genes associated with HNF4A activity and the immune system and upregulation of cell cycle genes, bringing about variability in patient outcomes. However, an increase in immune and cell cycle activity is observed in premalignant samples. Interestingly, co-expression modules and genes from premalignant stages are associated with survival. THBD, a classical marker for dendritic cells, is a predictor of survival at the premalignant stage. Further, genes linked to microtubules, kinetochores, and centromere are altered in both premalignant and tumour conditions and are associated with survival. Our analysis revealed a three-way molecular axis of liver function, immune pathways, and cell cycle driving HCC pathogenesis.

Transcriptomic meta-analysis reveals ERRα-mediated oxidative phosphorylation is downregulated in Fuchs' endothelial corneal dystrophy

BACKGROUND

Late-onset Fuchs' endothelial corneal dystrophy (FECD) is a degenerative disease of cornea and the leading indication for corneal transplantation. Genetically, FECD patients can be categorized as with (RE+) or without (RE-) the CTG trinucleotide repeat expansion in the transcription factor 4 gene. The molecular mechanisms underlying FECD remain unclear, though there are plausible pathogenic models proposed for RE+ FECD.

METHOD

In this study, we performed a meta-analysis on RNA sequencing datasets of FECD corneal endothelium including 3 RE+ datasets and 2 RE- datasets, aiming to compare the transcriptomic profiles of RE+ and RE- FECD. Gene differential expression analysis, co-expression networks analysis, and pathway analysis were conducted.

RESULTS

There was a striking similarity between RE+ and RE- transcriptomes. There were 1,184 genes significantly upregulated and 1,018 genes significantly downregulated in both RE+ and RE- cases. Pathway analysis identified multiple biological processes significantly enriched in both-mitochondrial functions, energy-related processes, ER-nucleus signaling pathway, demethylation, and RNA splicing were negatively enriched, whereas small GTPase mediated signaling, actin-filament processes, extracellular matrix organization, stem cell differentiation, and neutrophil mediated immunity were positively enriched. The translational initiation process was downregulated in the RE+ transcriptomes. Gene co-expression analysis identified modules with relatively distinct biological processes enriched including downregulation of mitochondrial respiratory chain complex assembly. The majority of oxidative phosphorylation (OXPHOS) subunit genes, as well as their upstream regulator gene estrogen-related receptor alpha (ESRRA), encoding ERRα, were downregulated in both RE+ and RE- cases, and the expression level of ESRRA was correlated with that of OXPHOS subunit genes.

CONCLUSION

Meta-analysis increased the power of detecting differentially expressed genes. Integrating differential expression analysis with co-expression analysis helped understand the underlying molecular mechanisms. FECD RE+ and RE- transcriptomic profiles are much alike with the hallmark of downregulation of genes in pathways related to ERRα-mediated OXPHOS.

Therapeutic effect of microRNA-21 on differentially expressed hub genes in gastric cancer based on systems biology

Gastric cancer (GC) is a leading cause of mortality for many people. Cancer's initiating factors are poorly understood. miR-21 has a crucial function in several malignancies, particularly GC. Furthermore, it has been shown that miR-21 is critical for the emergence and advancement of GC. This work intends to identify new genes which expression is associated with the activity of mir-21 in GC and to investigate the effect of downregulation of mir-21 on these genes and gastric tumorigenesis. We utilized the gene expression profiles of GCs from an Array database (GSE13911) from the Gene Expression Omnibus (GEO) dataset to find differentially expressed genes (DEGs) between control and gastric cancer groups. Using weighted gene correlation network analysis (WGCNA) in R, the Gene co-expression network was reconstructed. The microRNA-mRNA network was then reconstructed using the miRWalk database, and by investigating the microRNA-mRNA network, the genes that have an association with mir-21 were found. To implement the functional investigation, MKN and AGS cell lines were transfected with anti-miR-21 next. Subsequently, MTT proliferation was utilized to assess the cell's vitality. qRT-PCR was then used to evaluate the anticipated levels of gene expression in both GC cell lines. This study discovered and predicted CCL28, NR3C2, and SNYPO2 as the targets of miR-21 (GC), which are downregulated through gastric tumorigenesis, showing great potential as therapeutic and diagnostic targets. The suppression of miR-21 in gastric GC cells led to the inhibition of cell proliferation and decreased expression of CCL28, NR3C2, and SNYPO2 genes. This study established that miR-21, via downregulating these genes, contributes significantly to the development of GC. In addition, systems biology techniques identified CCL28, NR3C2, and SNYPO2 genes as possible GC surveillance and therapy components.

The role of mitochondria in sex- and age-specific gene expression in a species without sex chromosomes

Mitochondria perform an array of functions, many of which involve interactions with gene products encoded by the nucleus. These mitochondrial functions, particularly those involving energy production, can be expected to differ between sexes and across ages. Here we measured mitochondrial effects on sex- and age-specific gene expression in parental and reciprocal F1 hybrids between allopatric populations of Tigriopus californicus with over 20% mitochondrial DNA divergence. Because the species lacks sex chromosomes, sex-biased mitochondrial effects are not confounded by the effects of sex chromosomes. Using single-individual RNA sequencing, sex differences were found to explain more than 80% of the variance in gene expression. Males had higher expression of mitochondrial genes and mitochondrially targeted proteins (MTPs) involved in oxidative phosphorylation (OXPHOS), while females had elevated expression of non-OXPHOS MTPs, indicating strongly sex-dimorphic energy metabolism at the whole organism level. Comparison of reciprocal F1 hybrids allowed insights into the nature of mito-nuclear interactions, showing both mitochondrial effects on nuclear expression, as well as nuclear effects on mitochondrial expression. Across both sexes, increases in mitochondrial expression with age were associated with longer life. Network analyses identified nuclear components of strong mito-nuclear interactions, and found them to be sexually dimorphic. These results highlight the profound impact of mitochondria and mito-nuclear interactions on sex- and age-specific gene expression.

Functional response of microbial communities in lab-controlled oil-contaminated marine sediment

Crude oil contamination is one of the biggest problems in modern society. As oil enters into contact with the environment, especially if the point of contact is a body of water, it begins a weathering process by mixing and spreading. This is dangerous to local living organisms' communities and can impact diversity. However, despite unfavorable conditions, some microorganisms in these environments can survive using hydrocarbons as a nutrient source. Thus, understanding the local community dynamics of contaminated areas is essential. In this work, we analyzed the 16S rRNA amplicon sequencing and metatranscriptomic data of uncontaminated versus contaminated shallow marine sediment from publicly available datasets. We investigated the local population's taxonomic composition, species diversity, and fluctuations over time. Co-expression analysis coupled with functional enrichment showed us a prevalence of hydrocarbon-degrading functionality while keeping a distinct transcriptional profile between the late stages of oil contamination and the uncontaminated control. Processes related to the degradation of aromatic compounds and the metabolism of propanoate and butanoate were coupled with evidence of enhanced activity such as flagellar assembly and two-component system. Many enzymes of the anaerobic toluene degradation pathways were also enriched in our results. Furthermore, our diversity and taxonomical analyses showed a prevalence of the class Desulfobacteria, indicating interesting targets for bioremediation applications on marine sediment.

Illuminating (HTLV-1)-induced adult T-cell leukemia/lymphoma transcriptomic signature: A systems virology approach

BACKGROUND

Adult T-cell leukemia/lymphoma (ATLL) is a poor prognosis malignancy of peripheral T-cells caused by human T-cell leukemia virus type 1 (HTLV-1). The low survival rates observed in the patients are the result of the lack of sufficient knowledge about the disease pathogenesis.

METHODS

In the present study, we first identified differentially expressed genes in ATLL patients and the cellular signaling pathways affected by them. Then, genes of these pathways were subjected to more comprehensive evaluations, including WGCNA and module validation studies on five external datasets. Finally, potential biomarkers were selected for qRT-PCR validation.

RESULTS

Thirteen signaling pathways, including Apoptosis, Human T-cell leukemia virus 1 infection, IL-17 signaling pathway, pathways in cancer, T cell receptor signaling pathway, Th1 and Th2 cell differentiation, and seven others were selected for deeper investigations. Results of our in-depth bioinformatics evaluations, highlighted pathways related to regulation of immune responses, T-cell receptor and activation, regulation of cell signaling receptors and messengers, Wnt signaling pathway, and apoptosis as key players in ATLL pathogenesis. MAPK3, PIK3CD, KRAS, NFKB1, TNF, PLCB3, PLCB2, PLCB1, MAPK11, JUN, ITPR1, ADCY1, GNAQ, ADCY3, ADCY4, CHEK1, CCND1, SOS2, BAX, FOS and GNA12 were identified as possible biomarkers. Upregulation of ADCY1 and ADCY3 genes was confirmed via qRT-PCR.

CONCLUSIONS

In this study, we performed a deep bioinformatic examination on a limited set of genes with high probabilities of involvement in the pathogenesis of ATLL. Our results highlighted signaling pathways and genes with potential key roles in disease formation and resistance against current treatment strategies. Further studies are required to test the possible benefits of highlighted genes as biomarkers and targets of treatment.

Identification of novel N7-methylguanine-related gene signatures associated with ulcerative colitis and the association with biological therapy

OBJECTIVE

Ulcerative colitis (UC) is an inflammatory disease characterized by recurrent episodes of chronic intestinal inflammation. It is closely associated with immune dysregulation in the intestines. However, the mechanisms underlying the role of immune-related N7-methylguanosine (m7G) internal modification in UC remain unclear.

METHODS

We conducted a screening of differentially expressed genes (DEGs) associated with m7G and performed immune infiltration analysis. We then investigated the correlation between m7G-related DEGs and immune cells or pathways. To further explore the functional implications, we conducted functional enrichment analysis to identify gene modules that strongly correlated with hub gene expression. In addition, we constructed a miRNA regulatory network for the hub genes in UC. Furthermore, we examined the association between hub genes and disease remission in UC patients undergoing biologic therapy.

RESULTS

We obtained 13 m7G-related DEGs and conducted an in-depth analysis of immune infiltration. Among them, we identified five hub genes (NUDT7, NUDT12, POLR2H, QKI, and PRKCB) that showed diagnostic potential for UC. Through WGCNA and KEGG analysis, we found that gene modules strongly correlated with m7G hub gene expression were enriched in inflammation-related pathways. Furthermore, Kaplan-Meier survival analysis revealed a significant association between changes in hub gene expression levels and disease remission in UC patients undergoing biologic therapy.

CONCLUSION

The findings of this study demonstrate that five m7G-related DEGs, including the m7G-modified recognition protein QKI, play a key role in the occurrence and progression of UC intestinal inflammation, which is closely related to intestinal immunity. These results provide valuable insights into the mechanisms of m7G modification in UC development and offer new perspectives for exploring novel therapeutic targets for UC.

Identification of Key Osteoporosis Genes Through Comparative Analysis of Men's and Women's Osteoblast Transcriptomes

Osteoporosis disproportionately affects older women, yet gender differences in human osteoblasts remain unexplored. Identifying mechanisms and biomarkers of osteoporosis will enable the development of preventative and therapeutic approaches. Transcriptome data of 187 osteoblast samples from men and women were compared. Differentially expressed genes (DEGs) were identified, and weighted gene co-expression network analysis (WGCNA) was used to discover co-expressed modules. Enrichment analysis was performed to annotate DEGs. Preservation analysis determined whether modules and pathways were similar between genders. Blood methylation, transcriptome data, mouse phenotype data, and drug treatment data were utilized to identify key osteoporosis genes. We identified 1460 DEGs enriched in immune response, neurogenesis, and GWAS osteoporosis-related genes. WGCNA uncovered 8 modules associated with immune response, development, collagen metabolism, mitochondrion, and amino acid synthesis. Preservation analysis indicated modules and pathways were generally similar between genders. Incorporating GWAS and mouse phenotype data revealed 9 key genes, including GMDS, SMOC2, SASH1, MMP2, AHCYL1, ARRDC2, IGHMBP2, ATP6V1A, and CTSK. These genes were differentially methylated in patient blood and differentiated high and low bone mineral density patients in pre- and postmenopausal women. Denosumab treatment in postmenopausal women down-regulated 6 key genes, up-regulated T cell proportions, and down-regulated fibroblast proportion. qRT-PCR was used to confirm the genes in postmenopausal women. We identified 9 key osteoporosis genes by comparing the transcriptome of osteoblasts in women and men. Our findings' clinical implications were confirmed by multi-omics data and qRT-PCR, and our study provides novel biomarkers and therapeutic targets for osteoporosis diagnosis and treatment.

Investigating EGF and PAG1 as necroptosis-related biomarkers for diabetic nephropathy: an in silico and in vitro validation study

The current study aims to understand the mechanisms behind regulated cell death (RCD) in diabetic nephropathy and identify related biomarkers through bioinformatics and experimental validation. Datasets of bulk and single-cell RNA sequencing were obtained from public databases and analyzed using gene set variation analysis (GSVA) with gene sets related to RCD, including autophagy, necroptosis, pyroptosis, apoptosis, and ferroptosis. RCD-related gene biomarkers were identified using weighted gene correlation network analysis (WGCNA). The results were verified through experiments with an independent cohort and in vitro experiments. The GSVA revealed higher necroptosis scores in diabetic nephropathy. Three necroptosis-related biomarkers, EGF, PAG1, and ZFP36, were identified and showed strong diagnostic ability for diabetic kidney disease. In vitro experiments showed high levels of necroptotic markers in HK-2 cells treated with high glucose. Bioinformatics and experimental validation have thus identified EGF and PAG1 as necroptosis-related biomarkers for diabetic nephropathy.

Navigating the Gene Co-Expression Network and Drug Repurposing Opportunities for Brain Disorders Associated with Neurocognitive Impairment

Neurocognitive impairment refers to a spectrum of disorders characterized by a decline in cognitive functions such as memory, attention, and problem-solving, which are often linked to structural or functional abnormalities in the brain. While its exact etiology remains elusive, genetic factors play a pivotal role in disease onset and progression. This study aimed to identify highly correlated gene clusters (modules) and key hub genes shared across neurocognition-impairing diseases, including Alzheimer's disease (AD), Parkinson's disease with dementia (PDD), HIV-associated neurocognitive disorders (HAND), and glioma. Herein, the microarray datasets AD (GSE5281), HAND (GSE35864), glioma (GSE15824), and PD (GSE7621) were used to perform Weighted Gene Co-expression Network Analysis (WGCNA) to identify highly preserved modules across the studied brain diseases. Through gene set enrichment analysis, the shared modules were found to point towards processes including neuronal transcriptional dysregulation, neuroinflammation, protein aggregation, and mitochondrial dysfunction, hallmarks of many neurocognitive disorders. These modules were used in constructing protein-protein interaction networks to identify hub genes shared across the diseases of interest. These hub genes were found to play pivotal roles in processes including protein homeostasis, cell cycle regulation, energy metabolism, and signaling, all associated with brain and CNS diseases, and were explored for their drug repurposing experiments. Drug repurposing based on gene signatures highlighted drugs including Dorzolamide and Oxybuprocaine, which were found to modulate the expression of the hub genes in play and may have therapeutic implications in neurocognitive disorders. While both drugs have traditionally been used for other medical purposes, our study underscores the potential of a combined WGCNA and drug repurposing strategy for searching for new avenues in the simultaneous treatment of different diseases that have similarities in gene co-expression networks.