GeneHancer: genome-wide integration of enhancers and target genes in GeneCards

Direction-aware functional class scoring enrichment analysis of infinium DNA methylation data

Infinium Methylation BeadChip arrays remain one of the most popular platforms for epigenome-wide association studies, but tools for downstream pathway analysis have their limitations. Functional class scoring (FCS) is a group of pathway enrichment techniques that involve the ranking of genes and evaluation of their collective regulation in biological systems, but the implementations described for Infinium methylation array data do not retain direction information, which is important for mechanistic understanding of genomic regulation. Here, we evaluate several candidate FCS methods that retain directional information. According to simulation results, the best-performing method involves the mean aggregation of probe limma t-statistics by gene followed by a rank-ANOVA enrichment test using the mitch package. This method, which we call 'LAM,' outperformed an existing over-representation analysis method in simulations, and showed higher sensitivity and robustness in an analysis of real lung tumour-normal paired datasets. Using matched RNA-seq data, we examine the relationship of methylation differences at promoters and gene bodies with RNA expression at the level of pathways in lung cancer. To demonstrate the utility of our approach, we apply it to three other contexts where public data were available. First, we examine the differential pathway methylation associated with chronological age. Second, we investigate pathway methylation differences in infants conceived with in vitro fertilization. Lastly, we analyse differential pathway methylation in 19 disease states, identifying hundreds of novel associations. These results show LAM is a powerful method for the detection of differential pathway methylation complementing existing methods. A reproducible vignette is provided to illustrate how to implement this method.

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

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

Cucurbitacin B targets STAT3 to induce ferroptosis in non-small cell lung cancer

Cucurbitacin B (CuB) is a compound found in plants like Cucurbitaceae that has shown promise in fighting cancer, particularly in lung cancer. However, the specific impact of CuB on ferroptosis and how it works in lung cancer cells has not been fully understood. Our research has discovered that CuB can effectively slow down the growth of non-small cell lung cancer (NSCLC) cells. Even in small amounts, it was able to inhibit the growth of various NSCLC cell lines. This inhibitory effect was reversed when ferroptosis inhibitors DFO, Lip-1 and Fer-1 were introduced. CuB was found to increase the levels of reactive oxygen species (ROS), lipid ROS, MDA, and ferrous ions within H358 lung cancer cells, leading to a decrease in GSH, mitochondrial membrane potential (MMP) and changes in ferroptosis-related proteins in a dose-dependent manner. These findings were also confirmed in A549 lung cancer cells. In A549 cells, different concentrations of CuB induced the accumulation of intracellular lipid ROS, ferrous ions and changes in ferroptosis-related indicators in a concentration-dependent manner. Meanwhile, the cytotoxic effect induced by CuB in A549 cells was counteracted by ferroptosis inhibitors DFO and Fer-1. Through network pharmacology, we identified potential targets related to ferroptosis in NSCLC cells treated with CuB, with STAT3 targets showing high scores. Further experiments using molecular docking and cell thermal shift assay (CETSA) revealed that CuB interacts with the STAT3 protein. Western blot and immunofluorescence staining demonstrated that CuB inhibits the phosphorylation of STAT3 (P-STAT3) in H358 cells. Silencing STAT3 enhanced CuB-induced accumulation of lipid ROS and iron ions, as well as the expression of ferroptosis-related proteins. On the other hand, overexpression of STAT3 reversed the effects of CuB-induced ferroptosis. The results indicate that CuB has the capability to suppress STAT3 activation, resulting in ferroptosis, and could be a promising treatment choice for NSCLC.

Implications of noncoding regulatory functions in the development of insulinomas

Insulinomas are rare neuroendocrine tumors arising from pancreatic β cells, characterized by aberrant proliferation and altered insulin secretion, leading to glucose homeostasis failure. With the aim of uncovering the role of noncoding regulatory regions and their aberrations in the development of these tumors, we coupled epigenetic and transcriptome profiling with whole-genome sequencing. As a result, we unraveled somatic mutations associated with changes in regulatory functions. Critically, these regions impact insulin secretion, tumor development, and epigenetic modifying genes, including polycomb complex components. Chromatin remodeling is apparent in insulinoma-selective domains shared across patients, containing a specific set of regulatory sequences dominated by the SOX17 binding motif. Moreover, many of these regions are H3K27me3 repressed in β cells, suggesting that tumoral transition involves derepression of polycomb-targeted domains. Our work provides a compendium of aberrant cis-regulatory elements affecting the function and fate of β cells in their progression to insulinomas and a framework to identify coding and noncoding driver mutations.

Transcriptome- and proteome-wide association studies identify genes associated with renal cell carcinoma

We performed a series of integrative analyses including transcriptome-wide association studies (TWASs) and proteome-wide association studies (PWASs) of renal cell carcinoma (RCC) to nominate and prioritize molecular targets for laboratory investigation. On the basis of a genome-wide association study (GWAS) of 29,020 affected individuals and 835,670 control individuals and prediction models trained in transcriptomic reference models, our TWAS across four kidney transcriptomes (GTEx kidney cortex, kidney tubules, TCGA-KIRC [The Cancer Genome Atlas kidney renal clear-cell carcinoma], and TCGA-KIRP [TCGA kidney renal papillary cell carcinoma]) identified 38 gene associations (false-discovery rate <5%) in at least two of four transcriptomic panels and identified 12 genes that were independent of GWAS susceptibility regions. Analyses combining TWAS associations across 48 tissues from GTEx identified associations that were replicable in tumor transcriptomes for 23 additional genes. Analyses by the two major histologic types (clear-cell RCC and papillary RCC) revealed subtype-specific associations, although at least three gene associations were common to both subtypes. PWAS identified 13 associated proteins, all mapping to GWAS-significant loci. TWAS-identified genes were enriched for active enhancer or promoter regions in RCC tumors and hypoxia-inducible factor binding sites in relevant cell lines. Using gene expression correlation, common cancers (breast and prostate) and RCC risk factors (e.g., hypertension and BMI) display genetic contributions shared with RCC. Our work identifies potential molecular targets for RCC susceptibility for downstream functional investigation.

Prevalence of and gene regulatory constraints on transcriptional adaptation in single cells

BACKGROUND

Cells and tissues have a remarkable ability to adapt to genetic perturbations via a variety of molecular mechanisms. Nonsense-induced transcriptional compensation, a form of transcriptional adaptation, has recently emerged as one such mechanism, in which nonsense mutations in a gene trigger upregulation of related genes, possibly conferring robustness at cellular and organismal levels. However, beyond a handful of developmental contexts and curated sets of genes, no comprehensive genome-wide investigation of this behavior has been undertaken for mammalian cell types and conditions. How the regulatory-level effects of inherently stochastic compensatory gene networks contribute to phenotypic penetrance in single cells remains unclear.

RESULTS

We analyze existing bulk and single-cell transcriptomic datasets to uncover the prevalence of transcriptional adaptation in mammalian systems across diverse contexts and cell types. We perform regulon gene expression analyses of transcription factor target sets in both bulk and pooled single-cell genetic perturbation datasets. Our results reveal greater robustness in expression of regulons of transcription factors exhibiting transcriptional adaptation compared to those of transcription factors that do not. Stochastic mathematical modeling of minimal compensatory gene networks qualitatively recapitulates several aspects of transcriptional adaptation, including paralog upregulation and robustness to mutation. Combined with machine learning analysis of network features of interest, our framework offers potential explanations for which regulatory steps are most important for transcriptional adaptation.

CONCLUSIONS

Our integrative approach identifies several putative hits-genes demonstrating possible transcriptional adaptation-to follow-up on experimentally and provides a formal quantitative framework to test and refine models of transcriptional adaptation.

PD-1 blockade plus COX inhibitors in dMMR metastatic colorectal cancer: Clinical, genomic, and immunologic analyses from the PCOX trial

BACKGROUND

Approximately 20% of patients with DNA mismatch repair deficiency (dMMR) metastatic colorectal cancer do not respond to anti-programmed death-1 (PD-1) ligand therapy, and baseline biomarkers of response are lacking.

METHODS

We conducted a phase 2 study to evaluate the efficacy of cyclooxygenase (COX) inhibitors in combination with anti-PD-1 therapy in patients with dMMR metastatic colorectal cancer. The primary endpoint was objective response rate. The secondary endpoints included progression-free survival (PFS), overall survival (OS), disease control rate, duration of response, and safety.

FINDINGS

A total of 30 patients were enrolled, and the objective response rate was 73.3%, meeting the predefined endpoint of 68%. The median PFS and median OS were not reached at a median follow-up period of 50.8 months. Disease control was achieved in 28 patients (93.3%). The median duration of response was not reached. The combination was well tolerated. Multiomics analysis revealed that the antigen processing and presentation pathway was positively associated with treatment response and PFS. Higher TAPBP expression was predictive of better PFS (log-rank p = 0.003), and this prognostic significance was confirmed in an immunotherapy validation cohort.

CONCLUSIONS

Thus, COX inhibitors combined with PD-1 blockade may be effective and safe treatment options for patients with dMMR metastatic colorectal cancer, and TAPBP may serve as a biomarker for immune checkpoint inhibitor therapy (this study was registered at ClinicalTrials.gov: NCT03638297).

FUNDING

Funded by the National Natural Science Foundation of China (81974369) and the program of Guangdong Provincial Clinical Research Center for Digestive Diseases (2020B1111170004).

Genetic determinants and phenotypic consequences of blood T-cell proportions in 207,000 diverse individuals

T-cells play a critical role in multiple aspects of human health and disease. However, to date the genetic determinants of human T-cell abundance have not been studied at scale because assays quantifying T-cell abundance are not widely used in clinical or research settings. The complete blood count clinical assay quantifies lymphocyte abundance which includes T-cells, B-cells, and NK-cells. To address this gap, we directly estimate T-cell fractions from whole genome sequencing data in over 200,000 individuals from the multi-ethnic TOPMed and All of Us studies. We identified 27 loci associated with T-cell fraction. Interrogating electronic health records identified clinical phenotypes associated with T-cell fraction, including notable changes in T-cell proportions that were highly dynamic over the course of pregnancy. In summary, by estimating T-cell fraction, we obtained new insights into the genetic regulation of T-cells and identified disease consequences of T-cell fractions across the human phenome.

Dual targeting of histone deacetylases and MYC as potential treatment strategy for H3-K27M pediatric gliomas

Diffuse midline gliomas (DMGs) are aggressive and fatal pediatric tumors of the central nervous system that are highly resistant to treatments. Lysine to methionine substitution of residue 27 on histone H3 (H3-K27M) is a driver mutation in DMGs, reshaping the epigenetic landscape of these cells to promote tumorigenesis. H3-K27M gliomas are characterized by deregulation of histone acetylation and methylation pathways, as well as the oncogenic MYC pathway. In search of effective treatment, we examined the therapeutic potential of dual targeting of histone deacetylases (HDACs) and MYC in these tumors. Treatment of H3-K27M patient-derived cells with Sulfopin, an inhibitor shown to block MYC-driven tumors in vivo, in combination with the HDAC inhibitor Vorinostat, resulted in substantial decrease in cell viability. Moreover, transcriptome and epigenome profiling revealed synergistic effect of this drug combination in downregulation of prominent oncogenic pathways such as mTOR. Finally, in vivo studies of patient-derived orthotopic xenograft models showed significant tumor growth reduction in mice treated with the drug combination. These results highlight the combined treatment with PIN1 and HDAC inhibitors as a promising therapeutic approach for these aggressive tumors.

Antihypertensive Drugs for the Prevention of Atrial Fibrillation: A Drug Target Mendelian Randomization Study

BACKGROUND

We investigated the potential impact of antihypertensive drugs for atrial fibrillation (AF) prevention through a drug target Mendelian randomization study to avoid the potential limitations of clinical studies.

METHODS

Validated published single-nucleotide polymorphisms (SNPs) that mimic the action of 12 antihypertensive drug classes, including alpha-adrenoceptor blockers, adrenergic neuron blockers, angiotensin-converting enzyme inhibitors, angiotensin-II receptor blockers, beta-adrenoceptor blockers, centrally acting antihypertensive drugs, calcium channel blockers, loop diuretics, potassium-sparing diuretics and mineralocorticoid receptor antagonists, renin inhibitors, thiazides and related diuretic agents, and vasodilators were used. We estimated, via their corresponding gene and protein targets, the downstream effect of these drug classes to prevent AF via systolic blood pressure using 2-sample Mendelian randomization analyses. The SNPs were extracted from 2 European genome-wide association studies for the drug classes (n=317 754; n=757 601) and 1 European genome-wide association study for AF (n=1 030 836).

RESULTS

Drug target Mendelian randomization analyses supported the significant preventive causal effects of lowering systolic blood pressure per 10 mm Hg via alpha-adrenoceptor blockers (n=11 SNPs; odds ratio [OR], 0.34 [95% CI, 0.21-0.56]; P=2.74×10-05), beta-adrenoceptor blockers (n=17 SNPs; OR, 0.52 [95% CI, 0.35-0.78]; P=1.62×10-03), calcium channel blockers (n=49 SNPs; OR, 0.50 [95% CI, 0.36-0.70]; P=4.51×10-05), vasodilators (n=19 SNPs; OR, 0.53 [95% CI, 0.34-0.84]; P=7.03×10-03), and all 12 antihypertensive drug classes combined (n=158 SNPs; OR, 0.64 [95% CI, 0.54-0.77]; P=8.50×10-07) on AF risk.

CONCLUSIONS

Our results indicated that lowering systolic blood pressure via protein targets of various antihypertensive drugs seems promising for AF prevention. Our findings inform future clinical trials and have implications for repurposing antihypertensive drugs for AF prevention.

NFAT activation by FKBP52 promotes cancer cell proliferation by suppressing p53

FK506-binding protein 52 (FKBP52) is a member of the FKBP family of proline isomerases. FKBP52 is up-regulated in various cancers and functions as a positive regulator of steroid hormone receptors. Depletion of FKBP52 is known to inhibit cell proliferation; however, the detailed mechanism remains poorly understood. In this study, we found that FKBP52 depletion decreased MDM2 transcription, leading to stabilization of p53, and suppressed cell proliferation. We identified NFATc1 and NFATc3 as transcription factors that regulate MDM2 We also found that FKBP52 associated with NFATc3 and facilitated its nuclear translocation. In addition, calcineurin, a well-known Ca2+ phosphatase essential for activation of NFAT, plays a role in MDM2 transcription. Supporting this notion, MDM2 expression was found to be regulated by intracellular Ca2+ Taken together, these findings reveal a new role of FKBP52 in promoting cell proliferation via the NFAT-MDM2-p53 axis, and indicate that inhibition of FKBP52 could be a new therapeutic tool to activate p53 and inhibit cell proliferation.

RUNX1::ETO and CBFβ::MYH11 converge on aberrant activation of BCAT1 to confer a therapeutic vulnerability in core-binding factor-acute myeloid leukaemia

Effectively targeting transcription factors in therapeutic interventions remains challenging, especially in core-binding factor-acute myeloid leukaemia (CBF-AML) characterized by RUNX1::ETO and CBFβ::MYH11 fusions. However, recent studies have drawn attention towards aberrant amino acid metabolisms as actionable therapeutic targets. Here, by integrating the expression profile and genetic makeup in AML cohort, we found higher BCAT1 expression in CBF-AML patients compared with other subtypes. Metabolic profiling revealed that high BCAT1 expression led to reprogrammed branch amino acid metabolism in CBF-AML and was associated with sphingolipid pathway relating to the fitness of leukaemia cells, supported by transcriptomic profiling. Mechanistically, we demonstrated in cell lines and primary patient samples that BCAT1 was directly activated by RUNX1::ETO and CBFβ::MYH11 fusion proteins similarly in a RUNX1-dependent manner through rewiring chromatin conformation at the BCAT1 gene locus. Furthermore, BCAT1 inhibition resulted in blunted cell cycle, enhanced apoptosis and myeloid differentiation of CBF-AML cells in vitro, and alleviated leukaemia burden and prolonged survival in vivo. Importantly, pharmacological inhibition of BCAT1 using the specific inhibitor Gabapentin demonstrated therapeutic effects, as evidenced by delayed leukaemia progression and improved survival in vivo. In conclusion, our study uncovers BCAT1 as a genetic vulnerability and a promising targeted therapeutic opportunity for CBF-AML.

Unlocking the potential of edible Ulva sp. seaweeds: Metabolomic profiling, neuroprotective mechanisms, and implications for Parkinson's disease management

Green seaweed (Ulva sp.) is frequently used as a food component and nutraceutical agent because of its high polysaccharide and natural fiber content in Asian countries. This study investigates both metabolomic profiling of Ulva sp. and the neuroprotective efficacy of its ethanol extract and its underlying mechanisms in a rotenone-induced rat model of neurodegeneration, mimicking Parkinson's disease (PD) in humans. Metabolomic profiling of Ulva sp. extract was done using liquid chromatography high resolution electrospray ionization mass spectrometry and led to the identification of 22 compounds belonging to different chemical classes.Catenin Beta Additionally, this study demonstrated the neuroprotective properties against rotenone-induced PD, which was achieved through the suppression of elevated levels of tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), and IL-6 together with the inhibition of reactive oxygen species (ROS) generation, apoptosis, inflammatory mediators, and the phosphoinositide 3-kinases/serine/threonine protein kinase (PI3K/AKT) pathway. Using a protein-protein interaction network, AKT1, GAPDH, TNF-α, IL-6, caspase 3, signal transducer and activator of transcription 3, Catenin Beta 1, epidermal growth factor receptor, B-cell lymphoma -2, and HSP90AA1 were identified as the top 10 most significant genes. Finally, molecular docking results showed that compounds 1, 3, and 7 might possess a promising anti-parkinsonism effect by binding to active sites of selected hub genes. Therefore, it is hypothesized that the Ulva sp. extract has the potential to be further developed as a potential therapeutic agent for the treatment of PD.

SMARCA4 controls state plasticity in small cell lung cancer through regulation of neuroendocrine transcription factors and REST splicing

INTRODUCTION

Small Cell Lung Cancer (SCLC) can be classified into transcriptional subtypes with distinct degrees of neuroendocrine (NE) differentiation. Recent evidence supports plasticity among subtypes with a bias toward adoption of low-NE states during disease progression or upon acquired chemotherapy resistance. Here, we identify a role for SMARCA4, the catalytic subunit of the SWI/SNF complex, as a regulator of subtype shift in SCLC.

METHODS

ATACseq and RNAseq experiments were performed in SCLC cells after pharmacological inhibition of SMARCA4. DNA binding of SMARCA4 was characterized by ChIPseq in high-NE SCLC patient derived xenografts (PDXs). Enrichment analyses were applied to transcriptomic data. Combination of FHD-286 and afatinib was tested in vitro and in a set of chemo-resistant SCLC PDXs in vivo.

RESULTS

SMARCA4 expression positively correlates with that of NE genes in both SCLC cell lines and patient tumors. Pharmacological inhibition of SMARCA4 with FHD-286 induces the loss of NE features and downregulates neuroendocrine and neuronal signaling pathways while activating non-NE factors. SMARCA4 binds to gene loci encoding NE-lineage transcription factors ASCL1 and NEUROD1 and alters chromatin accessibility, enhancing NE programs. Enrichment analysis applied to high-confidence SMARCA4 targets confirmed neuron related pathways as the top GO Biological processes regulated by SMARCA4 in SCLC. In parallel, SMARCA4 also controls REST, a known suppressor of the NE phenotype, by regulating SRRM4-dependent REST transcript splicing. Furthermore, SMARCA4 inhibition drives ERBB pathway activation in SCLC, rendering SCLC tumors sensitive to afatinib.

CONCLUSIONS

This study nominates SMARCA4 as a key regulator of the NE state plasticity and defines a novel therapeutic strategy for SCLC.

CatLearning: highly accurate gene expression prediction from histone mark

Histone modifications, known as histone marks, are pivotal in regulating gene expression within cells. The vast array of potential combinations of histone marks presents a considerable challenge in decoding the regulatory mechanisms solely through biological experimental approaches. To overcome this challenge, we have developed a method called CatLearning. It utilizes a modified convolutional neural network architecture with a specialized adaptation Residual Network to quantitatively interpret histone marks and predict gene expression. This architecture integrates long-range histone information up to 500Kb and learns chromatin interaction features without 3D information. By using only one histone mark, CatLearning achieves a high level of accuracy. Furthermore, CatLearning predicts gene expression by simulating changes in histone modifications at enhancers and throughout the genome. These findings help comprehend the architecture of histone marks and develop diagnostic and therapeutic targets for diseases with epigenetic changes.

Assessing next-generation sequencing-based computational methods for predicting transcriptional regulators with query gene sets

This article provides an in-depth review of computational methods for predicting transcriptional regulators (TRs) with query gene sets. Identification of TRs is of utmost importance in many biological applications, including but not limited to elucidating biological development mechanisms, identifying key disease genes, and predicting therapeutic targets. Various computational methods based on next-generation sequencing (NGS) data have been developed in the past decade, yet no systematic evaluation of NGS-based methods has been offered. We classified these methods into two categories based on shared characteristics, namely library-based and region-based methods. We further conducted benchmark studies to evaluate the accuracy, sensitivity, coverage, and usability of NGS-based methods with molecular experimental datasets. Results show that BART, ChIP-Atlas, and Lisa have relatively better performance. Besides, we point out the limitations of NGS-based methods and explore potential directions for further improvement.

Potential Shared Mitochondrial-Related Gene Signatures and Molecular Mechanisms Between Polycystic Ovary Syndrome (PCOS) and Major Depressive Disorder (MDD): Evidence from Transcriptome Data and Machine Learning

Polycystic ovary syndrome (PCOS) is strongly associated with major depressive disorder (MDD), but the shared pathophysiological mechanisms between them are ambiguous, and the aim of this study was to explore the shared genetic features and associated pathways between these two disorders. MDD-related genes and mitochondrial function genes were downloaded from the GeneCards database. Weighted gene co-expression network analysis of Merge Cohort (GSE80432 and GSE34526) was performed to identify PCOS-related genes. Overlaps between PCOS-related genes, MDD-related genes, and mitochondrial function genes were defined as mitochondrial function-related shared genes. Functional enrichment analysis and protein-protein interaction (PPI) network analysis were performed on the shared genes. Functional genes were then identified using Last Absolute Shrinkage and Selection Operator Regression (LASSO), and a support vector machine (SVM-RFE) was constructed to measure the accuracy of the calculations. Finally, the results were tested using the whole blood datasets GSE54250 (for PCOS) and GSE98793 (for MDD) as external validation sets. A total of 498 PCOS-related genes, 5909 MDD-related genes, and 7232 mitochondrial function genes were acquired, and totally, 40 shared genes were obtained from the overlap of the above three. The shared mitochondrial function genes were enriched for biological processes mainly involving cholesterol biosynthetic process, lipid metabolic process, triglyceride biosynthetic process, response to drug phosphatidic acid biosynthetic process, and endoplasmic reticulum membrane. Based on LASSO regression and SVM-RFE model, NPAS2 and NTS were identified as characteristic genes shared by two disorders. According to two external validation sets for PCOS and MDD, NPAS2 was finally identified as a key shared gene. Our analysis identified a mitochondrial functional gene-NPAS2-as the most critical candidate for linking PCOS and MDD. The present findings may provide new insights into the diagnosis and treatment of PCOS and MDD comorbidities.

Integration of CTCF loops, methylome, and transcriptome in differentiating LUHMES as a model for imprinting dynamics of the 15q11-q13 locus in human neurons

Human cell line models, including the neuronal precursor line LUHMES, are important for investigating developmental transcriptional dynamics within imprinted regions, particularly the 15q11-q13 Angelman (AS) and Prader-Willi (PWS) syndrome locus. AS results from loss of maternal UBE3A in neurons, where the paternal allele is silenced by a convergent antisense transcript UBE3A-ATS, a lncRNA that terminates at PWAR1 in non-neurons. qRT-PCR analysis confirmed the exclusive and progressive increase in UBE3A-ATS in differentiating LUHMES neurons, validating their use for studying UBE3A silencing. Genome-wide transcriptome analyses revealed changes to 11 834 genes during neuronal differentiation, including the upregulation of most genes within the 15q11-q13 locus. To identify dynamic changes in chromatin loops linked to transcriptional activity, we performed a HiChIP validated by 4C, which identified two neuron-specific CTCF loops between MAGEL2-SNRPN and PWAR1-UBE3A. To determine if allele-specific differentially methylated regions (DMR) may be associated with CTCF loop anchors, whole genome long-read nanopore sequencing was performed. We identified a paternally hypomethylated DMR near the SNRPN upstream loop anchor exclusive to neurons and a paternally hypermethylated DMR near the PWAR1 CTCF anchor exclusive to undifferentiated cells, consistent with increases in neuronal transcription. Additionally, DMRs near CTCF loop anchors were observed in both cell types, indicative of allele-specific differences in chromatin loops regulating imprinted transcription. These results provide an integrated view of the 15q11-q13 epigenetic landscape during LUHMES neuronal differentiation, underscoring the complex interplay of transcription, chromatin looping, and DNA methylation. They also provide insights for future therapeutic approaches for AS and PWS.

Endogenous retroviruses mediate transcriptional rewiring in response to oncogenic signaling in colorectal cancer

Cancer cells exhibit rewired transcriptional regulatory networks that promote tumor growth and survival. However, the mechanisms underlying the formation of these pathological networks remain poorly understood. Through a pan-cancer epigenomic analysis, we found that primate-specific endogenous retroviruses (ERVs) are a rich source of enhancers displaying cancer-specific activity. In colorectal cancer and other epithelial tumors, oncogenic MAPK/AP1 signaling drives the activation of enhancers derived from the primate-specific ERV family LTR10. Functional studies in colorectal cancer cells revealed that LTR10 elements regulate tumor-specific expression of multiple genes associated with tumorigenesis, such as ATG12 and XRCC4. Within the human population, individual LTR10 elements exhibit germline and somatic structural variation resulting from a highly mutable internal tandem repeat region, which affects AP1 binding activity. Our findings reveal that ERV-derived enhancers contribute to transcriptional dysregulation in response to oncogenic signaling and shape the evolution of cancer-specific regulatory networks.

CREdb: A comprehensive database of Cis-Regulatory Elements and their activity in human cells and tissues

BACKGROUND

Cis-regulatory elements (CREs) play a pivotal role in gene expression regulation, allowing cells to serve diverse functions and respond to external stimuli. Understanding CREs is essential for personalized medicine and disease research, as an increasing number of genetic variants associated with phenotypes and diseases overlap with CREs. However, existing databases often focus on subsets of regulatory elements and present each identified instance of element individually, confounding the effort to obtain a comprehensive view. To address this gap, we have created CREdb, a comprehensive database with over 10 million human regulatory elements across 1,058 cell types and 315 tissues harmonized from different data sources. We curated and aligned the cell types and tissues to standard ontologies for efficient data query.

RESULTS

Data from 11 sources were curated and mapped to standard ontological terms. 11,223,434 combined elements are present in the final database, and these were merged into 5,666,240 consensus elements representing the combined ranges of the individual elements informed by their overlap. Each consensus element contains curated metadata including the number of elements supporting it and a hash linking to the source databases. The inferred activity of each consensus element in various cell-type and tissue context is also provided. Examples presented here show the potential utility of CREdb in annotating non-coding genetic variants and informing chromatin accessibility profiling analysis.

CONCLUSIONS

We developed CREdb, a comprehensive database of CREs, to simplify the analysis of CREs by providing a unified framework for researchers. CREdb compiles consensus ranges for each element by integrating the information from all instances identified across various source databases. This unified database facilitates the functional annotation of non-coding genetic variants and complements chromatin accessibility profiling analysis. CREdb will serve as an important resource in expanding our knowledge of the epigenome and its role in human diseases.

NanoRanger enables rapid single-base-pair resolution of genomic disorders

BACKGROUND

Delineating base-resolution breakpoints of complex rearrangements is crucial for an accurate clinical understanding of pathogenic variants and for carrier screening within family networks or the broader population. However, despite advances in genetic testing using short-read sequencing (SRS), this task remains costly and challenging.

METHODS

This study addresses the challenges of resolving missing disease-causing breakpoints in complex genomic disorders with suspected homozygous rearrangements by employing multiple long-read sequencing (LRS) strategies, including a novel and efficient strategy named nanopore-based rapid acquisition of neighboring genomic regions (NanoRanger). NanoRanger does not require large amounts of ultrahigh-molecular-weight DNA and stands out for its ease of use and rapid acquisition of large genomic regions of interest with deep coverage.

FINDINGS

We describe a cohort of 16 familial cases, each harboring homozygous rearrangements that defied breakpoint determination by SRS and optical genome mapping (OGM). NanoRanger identified the breakpoints with single-base-pair resolution, enabling accurate determination of the carrier status of unaffected family members as well as the founder nature of these genomic lesions and their frequency in the local population. The resolved breakpoints revealed that repetitive DNA, gene regulatory elements, and transcription activity contribute to genome instability in these novel recessive rearrangements.

CONCLUSIONS

Our data suggest that NanoRanger greatly improves the success rate of resolving base-resolution breakpoints of complex genomic disorders and expands access to LRS for the benefit of patients with Mendelian disorders.

FUNDING

M.L. is supported by KAUST Baseline Award no. BAS/1/1080-01-01 and KAUST Research Translation Fund Award no. REI/1/4742-01.

Multi-omics analysis reveals epigenetically regulated processes and patient classification in lung adenocarcinoma

Aberrant DNA methylation is a hallmark of many cancer types. Despite our knowledge of epigenetic and transcriptomic alterations in lung adenocarcinoma (LUAD), we lack robust multi-modal molecular classifications for patient stratification. This is partly because the impact of epigenetic alterations on lung cancer development and progression is still not fully understood. To that end, we identified disease-associated processes under epigenetic regulation in LUAD. We performed a genome-wide expression-methylation Quantitative Trait Loci (emQTL) analysis by integrating DNA methylation and gene expression data from 453 patients in the TCGA cohort. Using a community detection algorithm, we identified distinct communities of CpG-gene associations with diverse biological processes. Interestingly, we identified a community linked to hormone response and lipid metabolism; the identified CpGs in this community were enriched in enhancer regions and binding regions of transcription factors such as FOXA1/2, GRHL2, HNF1B, AR, and ESR1. Furthermore, the CpGs were connected to their associated genes through chromatin interaction loops. These findings suggest that the expression of genes involved in hormone response and lipid metabolism in LUAD is epigenetically regulated through DNA methylation and enhancer-promoter interactions. By applying consensus clustering on the integrated expression-methylation pattern of the emQTL-genes and CpGs linked to hormone response and lipid metabolism, we further identified subclasses of patients with distinct prognoses. This novel patient stratification was validated in an independent patient cohort of 135 patients and showed increased prognostic significance compared to previously defined molecular subtypes.

SMCHD1 activates the expression of genes required for the expansion of human myoblasts

SMCHD1 is an epigenetic regulatory protein known to modulate the targeted repression of large chromatin domains. Diminished SMCHD1 function in muscle fibers causes Facioscapulohumeral Muscular Dystrophy (FSHD2) through derepression of the D4Z4 chromatin domain, an event which permits the aberrant expression of the disease-causing gene DUX4. Given that SMCHD1 plays a broader role in establishing the cellular epigenome, we examined whether loss of SMCHD1 function might affect muscle homeostasis through additional mechanisms. Here we show that acute depletion of SMCHD1 results in a DUX4-independent defect in myoblast proliferation. Genomic and transcriptomic experiments determined that SMCHD1 associates with enhancers of genes controlling cell cycle to activate their expression. Amongst these cell cycle regulatory genes, we identified LAP2 as a key target of SMCHD1 required for the expansion of myoblasts, where the ectopic expression of LAP2 rescues the proliferation defect of SMCHD1-depleted cells. Thus, the epigenetic regulator SMCHD1 can play the role of a transcriptional co-activator for maintaining the expression of genes required for muscle progenitor expansion. This DUX4-independent role for SMCHD1 in myoblasts suggests that the pathology of FSHD2 may be a consequence of defective muscle regeneration in addition to the muscle wasting caused by spurious DUX4 expression.

Single cell transcriptomes and multiscale networks from persons with and without Alzheimer's disease

The emergence of single nucleus RNA sequencing (snRNA-seq) offers to revolutionize the study of Alzheimer's disease (AD). Integration with complementary multiomics data such as genetics, proteomics and clinical data provides powerful opportunities to link cell subpopulations and molecular networks with a broader disease-relevant context. We report snRNA-seq profiles from superior frontal gyrus samples from 101 well characterized subjects from the Banner Brain and Body Donation Program in combination with whole genome sequences. We report findings that link common AD risk variants with CR1 expression in oligodendrocytes as well as alterations in hematological parameters. We observed an AD-associated CD83(+) microglial subtype with unique molecular networks and which is associated with immunoglobulin IgG4 production in the transverse colon. Our major observations were replicated in two additional, independent snRNA-seq data sets. These findings illustrate the power of multi-tissue molecular profiling to contextualize snRNA-seq brain transcriptomics and reveal disease biology.

Network pharmacology, molecular docking and experimental validation to elucidate the anti-T2DM mechanism of Lanxangia tsaoko

Lanxangia tsaoko (L. tsaoko) is a natural medicine which could be used to treat type 2 diabetes mellitus (T2DM). However, there is no systematic and comprehensive research on the its active compounds and mechanism. This study aimed to investigate the active ingredients and potential mechanism of L. tsaoko for the treatment of T2DM. The chemical constituents of L. tsaoko were identified by UPLC-Q-Exactive Orbitrap/MS. The active compounds and mechanism of L. tsaoko were predicted by network pharmacology. Then the docking modes of key components and core targets were analyzed by molecular docking. Finally, animal experiments were conducted to verify the efficacy and targets of L. tsaoko in T2DM treatment. 70 compounds from L. tsaoko were identified. We obtained 37 active components, including quercetin, genistein and kaempferol, 5 core targets were AKT1, INS, TP53, TNF and IL-6. Mainly involved in PI3K/Akt, MAPK, RAGE/AGE, HIF-1, FoxO signaling pathways. Molecular docking results showed that the L. tsaoko had good binding potential to TNF. Therefore, we took the inflammatory mechanism as the prediction target for experimental verification. Animal experiments showed that L. tsaoko could alleviated colon injury of T2DM mice, improve glucose metabolism and decrease inflammatory levels. L. tsaoko exerted therapeutic effects on T2DM through multi-component, multi-target and multi-pathway regulation. Its action mechanisms were related to PI3K/Akt, MAPK, RAGE/AGE, HIF-1 and FoxO signaling pathways. This study provided new insights for the clinical treatment of T2DM.

Multi-scale signaling and tumor evolution in high-grade gliomas

Although genomic anomalies in glioblastoma (GBM) have been well studied for over a decade, its 5-year survival rate remains lower than 5%. We seek to expand the molecular landscape of high-grade glioma, composed of IDH-wildtype GBM and IDH-mutant grade 4 astrocytoma, by integrating proteomic, metabolomic, lipidomic, and post-translational modifications (PTMs) with genomic and transcriptomic measurements to uncover multi-scale regulatory interactions governing tumor development and evolution. Applying 14 proteogenomic and metabolomic platforms to 228 tumors (212 GBM and 16 grade 4 IDH-mutant astrocytoma), including 28 at recurrence, plus 18 normal brain samples and 14 brain metastases as comparators, reveals heterogeneous upstream alterations converging on common downstream events at the proteomic and metabolomic levels and changes in protein-protein interactions and glycosylation site occupancy at recurrence. Recurrent genetic alterations and phosphorylation events on PTPN11 map to important regulatory domains in three dimensions, suggesting a central role for PTPN11 signaling across high-grade gliomas.

Epigenetic alterations affecting hematopoietic regulatory networks as drivers of mixed myeloid/lymphoid leukemia

Leukemias with ambiguous lineage comprise several loosely defined entities, often without a clear mechanistic basis. Here, we extensively profile the epigenome and transcriptome of a subgroup of such leukemias with CpG Island Methylator Phenotype. These leukemias exhibit comparable hybrid myeloid/lymphoid epigenetic landscapes, yet heterogeneous genetic alterations, suggesting they are defined by their shared epigenetic profile rather than common genetic lesions. Gene expression enrichment reveals similarity with early T-cell precursor acute lymphoblastic leukemia and a lymphoid progenitor cell of origin. In line with this, integration of differential DNA methylation and gene expression shows widespread silencing of myeloid transcription factors. Moreover, binding sites for hematopoietic transcription factors, including CEBPA, SPI1 and LEF1, are uniquely inaccessible in these leukemias. Hypermethylation also results in loss of CTCF binding, accompanied by changes in chromatin interactions involving key transcription factors. In conclusion, epigenetic dysregulation, and not genetic lesions, explains the mixed phenotype of this group of leukemias with ambiguous lineage. The data collected here constitute a useful and comprehensive epigenomic reference for subsequent studies of acute myeloid leukemias, T-cell acute lymphoblastic leukemias and mixed-phenotype leukemias.

Integration of chromosome locations and functional aspects of enhancers and topologically associating domains in knowledge graphs enables versatile queries about gene regulation

Knowledge about transcription factor binding and regulation, target genes, cis-regulatory modules and topologically associating domains is not only defined by functional associations like biological processes or diseases but also has a determinative genome location aspect. Here, we exploit these location and functional aspects together to develop new strategies to enable advanced data querying. Many databases have been developed to provide information about enhancers, but a schema that allows the standardized representation of data, securing interoperability between resources, has been lacking. In this work, we use knowledge graphs for the standardized representation of enhancers and topologically associating domains, together with data about their target genes, transcription factors, location on the human genome, and functional data about diseases and gene ontology annotations. We used this schema to integrate twenty-five enhancer datasets and two domain datasets, creating the most powerful integrative resource in this field to date. The knowledge graphs have been implemented using the Resource Description Framework and integrated within the open-access BioGateway knowledge network, generating a resource that contains an interoperable set of knowledge graphs (enhancers, TADs, genes, proteins, diseases, GO terms, and interactions between domains). We show how advanced queries, which combine functional and location restrictions, can be used to develop new hypotheses about functional aspects of gene expression regulation.

DNA methylation of exercise-responsive genes differs between trained and untrained men

BACKGROUND

Physical activity is well known for its multiple health benefits and although the knowledge of the underlying molecular mechanisms is increasing, our understanding of the role of epigenetics in long-term training adaptation remains incomplete. In this intervention study, we included individuals with a history of > 15 years of regular endurance or resistance training compared to age-matched untrained controls performing endurance or resistance exercise. We examined skeletal muscle DNA methylation of genes involved in key adaptation processes, including myogenesis, gene regulation, angiogenesis and metabolism.

RESULTS

A greater number of differentially methylated regions and differentially expressed genes were identified when comparing the endurance group with the control group than in the comparison between the strength group and the control group at baseline. Although the cellular composition of skeletal muscle samples was generally consistent across groups, variations were observed in the distribution of muscle fiber types. Slow-twitch fiber type genes MYH7 and MYL3 exhibited lower promoter methylation and elevated expression in endurance-trained athletes, while the same group showed higher methylation in transcription factors such as FOXO3, CREB5, and PGC-1α. The baseline DNA methylation state of those genes was associated with the transcriptional response to an acute bout of exercise. Acute exercise altered very few of the investigated CpG sites.

CONCLUSIONS

Endurance- compared to resistance-trained athletes and untrained individuals demonstrated a different DNA methylation signature of selected skeletal muscle genes, which may influence transcriptional dynamics following a bout of acute exercise. Skeletal muscle fiber type distribution is associated with methylation of fiber type specific genes. Our results suggest that the baseline DNA methylation landscape in skeletal muscle influences the transcription of regulatory genes in response to an acute exercise bout.

Genome-wide Studies Reveal Genetic Risk Factors for Hepatic Fat Content

Genetic susceptibility to metabolic associated fatty liver disease (MAFLD) is complex and poorly characterized. Accurate characterization of the genetic background of hepatic fat content would provide insights into disease etiology and causality of risk factors. We performed genome-wide association study (GWAS) on two noninvasive definitions of hepatic fat content: magnetic resonance imaging proton density fat fraction (MRI-PDFF) in 16,050 participants and fatty liver index (FLI) in 388,701 participants from the United Kingdom (UK) Biobank (UKBB). Heritability, genetic overlap, and similarity between hepatic fat content phenotypes were analyzed, and replicated in 10,398 participants from the University Medical Center Groningen (UMCG) Genetics Lifelines Initiative (UGLI). Meta-analysis of GWASs of MRI-PDFF in UKBB revealed five statistically significant loci, including two novel genomic loci harboring CREB3L1 (rs72910057-T, P = 5.40E-09) and GCM1 (rs1491489378-T, P = 3.16E-09), respectively, as well as three previously reported loci: PNPLA3, TM6SF2, and APOE. GWAS of FLI in UKBB identified 196 genome-wide significant loci, of which 49 were replicated in UGLI, with top signals in ZPR1 (P = 3.35E-13) and FTO (P = 2.11E-09). Statistically significant genetic correlation (rg) between MRI-PDFF (UKBB) and FLI (UGLI) GWAS results was found (rg = 0.5276, P = 1.45E-03). Novel MRI-PDFF genetic signals (CREB3L1 and GCM1) were replicated in the FLI GWAS. We identified two novel genes for MRI-PDFF and 49 replicable loci for FLI. Despite a difference in hepatic fat content assessment between MRI-PDFF and FLI, a substantial similar genetic architecture was found. FLI is identified as an easy and reliable approach to study hepatic fat content at the population level.

A proximal enhancer regulates RORA expression during early human Th17 cell differentiation

Gene regulatory elements, such as enhancers, greatly influence cell identity by tuning the transcriptional activity of specific cell types. Dynamics of enhancer landscape during early human Th17 cell differentiation remains incompletely understood. Leveraging ATAC-seq-based profiling of chromatin accessibility and comprehensive analysis of key histone marks, we identified a repertoire of enhancers that potentially exert control over the fate specification of Th17 cells. We found 23 SNPs associated with autoimmune diseases within Th17-enhancers that precisely overlapped with the binding sites of transcription factors actively engaged in T-cell functions. Among the Th17-specific enhancers, we identified an enhancer in the intron of RORA and demonstrated that this enhancer positively regulates RORA transcription. Moreover, CRISPR-Cas9-mediated deletion of a transcription factor binding site-rich region within the identified RORA enhancer confirmed its role in regulating RORA transcription. These findings provide insights into the potential mechanism by which the RORA enhancer orchestrates Th17 differentiation.

Noninvasive Lung Cancer Subtype Classification Using Tumor-Derived Signatures and cfDNA Methylome

Accurate diagnosis of lung cancer is important for treatment decision-making. Tumor biopsy and histologic examination are the standard for determining histologic lung cancer subtypes. Liquid biopsy, particularly cell-free DNA (cfDNA), has recently shown promising results in cancer detection and classification. In this study, we investigate the potential of cfDNA methylome for the noninvasive classification of lung cancer histologic subtypes. We focused on the two most prevalent lung cancer subtypes, lung adenocarcinoma and lung squamous cell carcinoma. Using a fragment-based marker discovery approach, we identified robust subtype-specific methylation markers from tumor samples. These markers were successfully validated in independent cohorts and associated with subtype-specific transcriptional activity. Leveraging these markers, we constructed a subtype classification model using cfDNA methylation profiles, achieving an AUC of 0.808 in cross-validation and an AUC of 0.747 in the independent validation. Tumor copy-number alterations inferred from cfDNA methylome analysis revealed potential for treatment selection. In summary, our study demonstrates the potential of cfDNA methylome analysis for noninvasive lung cancer subtyping, offering insights for cancer monitoring and early detection.

SIGNIFICANCE

This study explores the use of cfDNA methylomes for the classification of lung cancer subtypes, vital for effective treatment. By identifying specific methylation markers in tumor tissues, we developed a robust classification model achieving high accuracy for noninvasive subtype detection. This cfDNA methylome approach offers promising avenues for early detection and monitoring.

Genetically determined blood pressure, antihypertensive drug classes, and frailty: A Mendelian randomization study

Observational studies have suggested that the use of antihypertensive drugs was associated with the risk of frailty; however, these findings may be biased by confounding and reverse causality. This study aimed to explore the effect of genetically predicted lifelong lowering blood pressure (BP) through different antihypertensive medications on frailty. One-sample Mendelian randomization (MR) and summary data-based MR (SMR) were applied. We utilized two kinds of genetic instruments to proxy the antihypertensive medications, including genetic variants within or nearby drugs target genes associated with systolic/diastolic BP, and expression level of the corresponding gene. Among 298,618 UK Biobank participants, one-sample MR analysis observed that genetically proxied BB use (relative risk ratios, 0.76; 95% CI, 0.65-0.90; p = 0.001) and CCB use (0.83; 0.72-0.95; p = 0.007), equivalent to a 10-mm Hg reduction in systolic BP, was significantly associated with lower risk of pre-frailty. In addition, although not statistically significant, the effect directions of systolic BP through ACEi variants (0.72; 0.39-1.33; p = 0.296) or thiazides variants (0.74; 0.53-1.03; p = 0.072) on pre-frailty were also protective. Similar results were obtained in analyses for diastolic BP. SMR of expression in artery showed that decreased expression level of KCNH2, a target gene of BBs, was associated with lower frailty index (beta -0.02, p = 2.87 × 10-4). This MR analysis found evidence that the use of BBs and CCBs was potentially associated with reduced frailty risk in the general population, and identified KCNH2 as a promising target for further clinical trials to prevent manifestations of frailty.

Effect of the Blood Pressure and Antihypertensive Drugs on Cerebral Small Vessel Disease: A Mendelian Randomization Study

BACKGROUND

Previous studies yielded conflicting results about the influence of blood pressure (BP) and antihypertensive treatment on cerebral small vessel disease. Here, we conducted a Mendelian randomization study to investigate the effect of BP and antihypertensive drugs on cerebral small vessel disease.

METHODS

We extracted single-nucleotide polymorphisms for systolic BP and diastolic BP from a genome-wide association study (N=757 601) and screened single-nucleotide polymorphisms associated with calcium channel blockers, thiazides, angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, and β-blockers from public resources as instrumental variables. Then, we chose the genome-wide association study of white matter hyperintensity (WMH; N=18 381), cerebral microbleed (3556 cases, 22 306 controls), white matter perivascular space (9317 cases, 29 281 controls), basal ganglia perivascular space (BGPVS; 8950 cases, 29 953 controls), hippocampal perivascular space (HIPPVS; 9163 cases, 29 708 controls), and lacunar stroke (6030 cases, 248 929 controls) as outcome data sets. Subsequently, we conducted a 2-sample Mendelian randomization analysis.

RESULTS

We found that elevated systolic BP significantly increases the risk of BGPVS (odds ratio [OR], 1.05 [95% CI, 1.04-1.07]; P=1.72×10-12), HIPPVS (OR, 1.04 [95% CI, 1.02-1.05]; P=2.71×10-7), and lacunar stroke (OR, 1.41 [95% CI, 1.30-1.54]; P=4.97×10-15). There was suggestive evidence indicating that elevated systolic BP is associated with higher WMH volume (β=0.061 [95% CI, 0.018-0.105]; P=5.58×10-3) and leads to an increased risk of cerebral microbleed (OR, 1.16 [95% CI, 1.04-1.29]; P=7.17×10-3). Elevated diastolic BP was significantly associated with higher WMH volume (β=0.087 [95% CI, 0.049-0.124]; P=5.23×10-6) and significantly increased the risk of BGPVS (OR, 1.05 [95% CI, 1.04-1.06]; P=1.20×10-16), HIPPVS (OR, 1.03 [95% CI, 1.02-1.04]; P=2.96×10-6), and lacunar stroke (OR, 1.31 [95% CI, 1.21-1.41]; P=2.67×10-12). The use of calcium channel blocker to lower BP was significantly associated with lower WMH volume (β=-0.287 [95% CI, -0.408 to -0.165]; P=4.05×10-6) and significantly reduced the risk of BGPVS (OR, 0.85 [95% CI, 0.81-0.89]; P=8.41×10-19) and HIPPVS (OR, 0.88 [95% CI, 0.85-0.92]; P=6.72×10-9).

CONCLUSIONS

Our findings contribute to a better understanding of the pathogenesis of cerebral small vessel disease. Additionally, the utilization of calcium channel blockers to decrease BP can effectively reduce the likelihood of WMH, BGPVS, and HIPPVS. These findings offer valuable insights for the management and prevention of cerebral small vessel disease.

Post-GWAS multiomic functional investigation of the TNIP1 locus in Alzheimer's disease highlights a potential role for GPX3

INTRODUCTION

Recent genome-wide association studies (GWAS) have reported a genetic association with Alzheimer's disease (AD) at the TNIP1/GPX3 locus, but the mechanism is unclear.

METHODS

We used cerebrospinal fluid (CSF) proteomics data to test (n = 137) and replicate (n = 446) the association of glutathione peroxidase 3 (GPX3) with CSF biomarkers (including amyloid and tau) and the GWAS-implicated variants (rs34294852 and rs871269).

RESULTS

CSF GPX3 levels decreased with amyloid and tau positivity (analysis of variance P = 1.5 × 10-5) and higher CSF phosphorylated tau (p-tau) levels (P = 9.28 × 10-7). The rs34294852 minor allele was associated with decreased GPX3 (P = 0.041). The replication cohort found associations of GPX3 with amyloid and tau positivity (P = 2.56 × 10-6) and CSF p-tau levels (P = 4.38 × 10-9).

DISCUSSION

These results suggest variants in the TNIP1 locus may affect the oxidative stress response in AD via altered GPX3 levels.

HIGHLIGHTS

Cerebrospinal fluid (CSF) glutathione peroxidase 3 (GPX3) levels decreased with amyloid and tau positivity and higher CSF phosphorylated tau. The minor allele of rs34294852 was associated with lower CSF GPX3. levels when also controlling for amyloid and tau category. GPX3 transcript levels in the prefrontal cortex were lower in Alzheimer's disease than controls. rs34294852 is an expression quantitative trait locus for GPX3 in blood, neutrophils, and microglia.

Comprehensive Analysis of angiogenesis associated genes and tumor microenvironment infiltration characterization in cervical cancer

Background

Cervical cancer is among the most prevalent malignancies worldwide. This study explores the relationships between angiogenesis-related genes (ARGs) and immune infiltration, and assesses their implications for the prognosis and treatment of cervical cancer. Additionally, it develops a diagnostic model based on angiogenesis-related differentially expressed genes (ARDEGs).

Methods

We systematically evaluated 15 ARDEGs using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), and Gene Set Variation Analysis (GSVA). Immune cell infiltration was assessed using a single-sample gene-set enrichment analysis (ssGSEA) algorithm. We then constructed a diagnostic model for ARDEGs using Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis and evaluated the diagnostic value of this model and the hub genes in predicting clinical outcomes and immunotherapy responses in cervical cancer.

Results

A set of ARDEGs was identified from the Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and UCSC Xena database. We performed KEGG, GO, and GSEA analyses on these genes, revealing significant involvement in cell proliferation, differentiation, and apoptosis. The ARDEGs diagnostic model, constructed using LASSO regression analysis, showed high predictive accuracy in cervical cancer patients. We developed a reliable nomogram and decision curve analysis to evaluate the clinical utility of the ARDEG diagnostic model. The 15 ARDEGs in the model were associated with clinicopathological features, prognosis, and immune cell infiltration. Notably, ITGA5 expression and the abundance of immune cell infiltration (specifically mast cell activation) were highly correlated.

Conclusion

This study identifies the prognostic characteristics of ARGs in cervical cancer patients, elucidating aspects of the tumor microenvironment. It enhances the predictive accuracy of immunotherapy outcomes and establishes new strategies for immunotherapeutic interventions.

A genome scale transcriptional regulatory model of the human placenta

Gene regulation is essential to placental function and fetal development. We built a genome-scale transcriptional regulatory network (TRN) of the human placenta using digital genomic footprinting and transcriptomic data. We integrated 475 transcriptomes and 12 DNase hypersensitivity datasets from placental samples to globally and quantitatively map transcription factor (TF)-target gene interactions. In an independent dataset, the TRN model predicted target gene expression with an out-of-sample R2 greater than 0.25 for 73% of target genes. We performed siRNA knockdowns of four TFs and achieved concordance between the predicted gene targets in our TRN and differences in expression of knockdowns with an accuracy of >0.7 for three of the four TFs. Our final model contained 113,158 interactions across 391 TFs and 7712 target genes and is publicly available. We identified 29 TFs which were significantly enriched as regulators for genes previously associated with preterm birth, and eight of these TFs were decreased in preterm placentas.

Discovery of genomic and transcriptomic pleiotropy between kidney function and soluble receptor for advanced glycation end products using correlated meta-analyses: The Long Life Family Study

Patients with chronic kidney disease (CKD) have increased oxidative stress and chronic inflammation, which may escalate the production of advanced glycation end-products (AGEs). High soluble receptor for AGE (sRAGE) and low estimated glomerular filtration rate (eGFR) levels are associated with CKD and aging. We evaluated whether eGFR calculated from creatinine and cystatin C share pleiotropic genetic factors with sRAGE. We employed whole-genome sequencing and correlated meta-analyses on combined genome-wide association study (GWAS) p-values in 4182 individuals (age range: 24-110) from the Long Life Family Study (LLFS). We also conducted transcriptome-wide association studies (TWAS) on whole blood in a subset of 1209 individuals. We identified 59 pleiotropic GWAS loci (p < 5 × 10-8) and 17 TWAS genes (Bonferroni-p < 2.73 × 10-6) for eGFR traits and sRAGE. TWAS genes, LSP1 and MIR23AHG, were associated with eGFR and sRAGE located within GWAS loci, lncRNA-KCNQ1OT1 and CACNA1A/CCDC130, respectively. GWAS variants were eQTLs in the kidney glomeruli and tubules, and GWAS genes predicted kidney carcinoma. TWAS genes harbored eQTLs in the kidney, predicted kidney carcinoma, and connected enhancer-promoter variants with kidney function-related phenotypes at p < 5 × 10-8. Additionally, higher allele frequencies of protective variants for eGFR traits were detected in LLFS than in ALFA-Europeans and TOPMed, suggesting better kidney function in healthy-aging LLFS than in general populations. Integrating genomic annotation and transcriptional gene activity revealed the enrichment of genetic elements in kidney function and aging-related processes. The identified pleiotropic loci and gene expressions for eGFR and sRAGE suggest their underlying shared genetic effects and highlight their roles in kidney- and aging-related signaling pathways.

Lianhua Qingwen exerts anti-liver cancer effects and synergistic efficacy with sorafenib through PI3K/AKT pathway: Integrating network pharmacology, molecular docking, and experimental validation

Liver cancer is one of the most lethal malignancies and sorafenib resistance is the main treatment obstacle for patients with advanced liver cancer. Developing drugs that sensitize liver cancer patients to sorafenib is of great importance. Lianhua Qingwen (LHQW), a sort of Traditional Chinese Medicine (TCM) approved by the Chinese Food and Drug Administration (CFDA), is reported to exert synergistic effects with oseltamivir against Influenza virus. However, whether LHQW could exhibit anti-liver cancer effects and enhance the efficacy of sorafenib against liver cancer have not been reported. In the present study, the potential anti-liver cancer effects of LHQW and its synergistic effects with sorafenib were investigated via applying network pharmacology, molecular docking, and in vitro experiments. An "ingredient-compound- target-liver cancer" network was constructed which included 12 ingredients, 164 compounds, and 402 targets. AKT1 was identified as the most hub gene and the PI3K/AKT pathway was revealed as the most enriched pathway. Subsequently, the molecular docking results showed that kaempferol, luteolin, and quercetin were screened as the top 3 compounds which showed the tightest binding to AKT1. Further, the in vitro experiments verified that LHQW significantly inhibited liver cancer cell proliferation and induced apoptosis. Western blot assays confirmed that LHQW could attenuate the PI3K/AKT pathway. Interestingly, LHQW showed a synergistic effect with sorafenib against liver cancer via reducing cell viability, inducing apoptosis, and down- regulating PI3K/AKT pathway. This study broadens the potential application of LHQW and provides insights for liver cancer treatment.

Rare pathogenic structural variants show potential to enhance prostate cancer germline testing for African men

Prostate cancer (PCa) is highly heritable, with men of African ancestry at greatest risk and associated lethality. Lack of representation in genomic data means germline testing guidelines exclude for African men. Established that structural variations (SVs) are major contributors to human disease and prostate tumourigenesis, their role is under-appreciated in familial and therapeutic testing. Utilising a clinico-methodologically matched African (n = 113) versus European (n = 57) deep-sequenced PCa resource, we interrogated 42,966 high-quality germline SVs using a best-fit pathogenicity prediction workflow. We identified 15 potentially pathogenic SVs representing 12.4% African and 7.0% European patients, of which 72% and 86% met germline testing standard-of-care recommendations, respectively. Notable African-specific loss-of-function gene candidates include DNA damage repair MLH1 and BARD1 and tumour suppressors FOXP1, WASF1 and RB1. Representing only a fraction of the vast African diaspora, this study raises considerations with respect to the contribution of kilo-to-mega-base rare variants to PCa pathogenicity and African associated disparity.

Expanding and Enriching the LncRNA Gene-Disease Landscape Using the GeneCaRNA Database

The GeneCaRNA human gene database is a member of the GeneCards Suite. It presents ~280,000 human non-coding RNA genes, identified algorithmically from ~690,000 RNAcentral transcripts. This expands by ~tenfold the ncRNA gene count relative to other sources. GeneCaRNA thus contains ~120,000 long non-coding RNAs (LncRNAs, >200 bases long), including ~100,000 novel genes. The latter have sparse functional information, a vast terra incognita for future research. LncRNA genes are uniformly represented on all nuclear chromosomes, with 10 genes on mitochondrial DNA. Data obtained from MalaCards, another GeneCards Suite member, finds 1547 genes associated with 1 to 50 diseases. About 15% of the associations portray experimental evidence, with cancers tending to be multigenic. Preliminary text mining within GeneCaRNA discovers interactions of lncRNA transcripts with target gene products, with 25% being ncRNAs and 75% proteins. GeneCaRNA has a biological pathways section, which at present shows 131 pathways for 38 lncRNA genes, a basis for future expansion. Finally, our GeneHancer database provides regulatory elements for ~110,000 lncRNA genes, offering pointers for co-regulated genes and genetic linkages from enhancers to diseases. We anticipate that the broad vista provided by GeneCaRNA will serve as an essential guide for further lncRNA research in disease decipherment.

miRNA signatures underlie chemoresistance in the gemcitabine-resistant pancreatic ductal adenocarcinoma cell line MIA PaCa-2 GR

Introduction: Chemotherapy resistance remains a significant challenge in the treatment of pancreatic adenocarcinoma (PDAC), particularly in relation to gemcitabine (Gem), a commonly used chemotherapeutic agent. MicroRNAs (miRNAs) are known to influence cancer progression and chemoresistance. This study investigates the association between miRNA expression profiles and gemcitabine resistance in PDAC. Methods: The miRNA expression profiles of a gemcitabine-sensitive (GS) PDAC cell line, MIA PaCa-2, and its gemcitabine-resistant (GR) progeny, MIA PaCa-2 GR, were analyzed. miRNA sequencing (miRNA-seq) was employed to identify miRNAs expressed in these cell lines. Differential expression analysis was performed, and Ingenuity Pathway Analysis (IPA) was utilized to elucidate the biological functions of the differentially expressed miRNAs. Results: A total of 1867 miRNAs were detected across both cell lines. Among these, 97 (5.2%) miRNAs showed significant differential expression between the GR and GS cell lines, with 65 (3.5%) miRNAs upregulated and 32 (1.7%) miRNAs downregulated in the GR line. The most notably altered miRNAs were implicated in key biological processes such as cell proliferation, migration, invasion, chemosensitization, alternative splicing, apoptosis, and angiogenesis. A subset of these miRNAs was further analyzed in patient samples to identify potential markers for recurrent tumors. Discussion: The differential miRNA expression profiles identified in this study highlight the complex regulatory roles of miRNAs in gemcitabine resistance in PDAC. These findings suggest potential targets for improving prognosis and tailoring treatment strategies in PDAC patients, particularly those showing resistance to gemcitabine. Future research should focus on validating these miRNAs as biomarkers for resistance and exploring their therapeutic potential in overcoming chemoresistance.

Tau propagation in the brain olfactory circuits is associated with smell perception changes in aging

The direct access of olfactory afferents to memory-related cortical systems has inspired theories about the role of the olfactory pathways in the development of cortical neurodegeneration in Alzheimer's disease (AD). In this study, we used baseline olfactory identification measures with longitudinal flortaucipir and PiB PET, diffusion MRI of 89 cognitively normal older adults (73.82 ± 8.44 years; 56% females), and a transcriptomic data atlas to investigate the spatiotemporal spreading and genetic vulnerabilities of AD-related pathology aggregates in the olfactory system. We find that odor identification deficits are predominantly associated with tau accumulation in key areas of the olfactory pathway, with a particularly strong predictive power for longitudinal tau progression. We observe that tau spreads from the medial temporal lobe structures toward the olfactory system, not the reverse. Moreover, we observed a genetic background of odor perception-related genes that might confer vulnerability to tau accumulation along the olfactory system.

A quantitative and site-specific atlas of the citrullinome reveals widespread existence of citrullination and insights into PADI4 substrates

Despite the importance of citrullination in physiology and disease, global identification of citrullinated proteins, and the precise targeted sites, has remained challenging. Here we employed quantitative-mass-spectrometry-based proteomics to generate a comprehensive atlas of citrullination sites within the HL60 leukemia cell line following differentiation into neutrophil-like cells. We identified 14,056 citrullination sites within 4,008 proteins and quantified their regulation upon inhibition of the citrullinating enzyme PADI4. With this resource, we provide quantitative and site-specific information on thousands of PADI4 substrates, including signature histone marks and transcriptional regulators. Additionally, using peptide microarrays, we demonstrate the potential clinical relevance of certain identified sites, through distinct reactivities of antibodies contained in synovial fluid from anti-CCP-positive and anti-CCP-negative people with rheumatoid arthritis. Collectively, we describe the human citrullinome at a systems-wide level, provide a resource for understanding citrullination at the mechanistic level and link the identified targeted sites to rheumatoid arthritis.

Unexpected complexity in the molecular diagnosis of spastic paraplegia 11

BACKGROUND

Spastic paraplegia 11 (SPG11) is the most prevalent form of autosomal recessive hereditary spastic paraplegia, resulting from biallelic pathogenic variants in the SPG11 gene (MIM *610844).

METHODS

The proband is a 36-year-old female referred for genetic evaluation due to cognitive dysfunction, gait impairment, and corpus callosum atrophy (brain MRI was normal at 25-years-old). Diagnostic approaches included CGH array, next-generation sequencing, and whole transcriptome sequencing.

RESULTS

CGH array revealed a 180 kb deletion located upstream of SPG11. Sequencing of SPG11 uncovered two rare single nucleotide variants: the novel variant c.3143C>T in exon 17 (in cis with the deletion), and the previously reported pathogenic variant c.6409C>T in exon 34 (in trans). Whole transcriptome sequencing revealed that the variant c.3143C>T caused exon 17 skipping.

CONCLUSION

We report a novel sequence variant in the SPG11 gene resulting in exon 17 skipping, which, along with a nonsense variant, causes Spastic Paraplegia 11 in our proband. In addition, a deletion upstream of SPG11 was identified in the patient, whose implication in the phenotype remains uncertain. Nonetheless, the deletion apparently affects cis-regulatory elements of the gene, suggesting a potential new pathogenic mechanism underlying the disease in a subset of undiagnosed patients. Our findings further support the hypothesis that the origin of thin corpus callosum in patients with SPG11 is of progressive nature.

Quantitative estimates of the regulatory influence of long non-coding RNAs on global gene expression variation using TCGA breast cancer transcriptomic data

Long non-coding RNAs (lncRNAs) have received attention in recent years for their regulatory roles in diverse biological contexts including cancer, yet large gaps remain in our understanding of their mechanisms and global maps of their targets. In this work, we investigated a basic unanswered question of lncRNA systems biology: to what extent can gene expression variation across individuals be attributed to lncRNA-driven regulation? To answer this, we analyzed RNA-seq data from a cohort of breast cancer patients, explaining each gene's expression variation using a small set of automatically selected lncRNA regulators. A key aspect of this analysis is that it accounts for confounding effects of transcription factors (TFs) as common regulators of a lncRNA-mRNA pair, to enrich the explained gene expression for lncRNA-mediated regulation. We found that for 16% of analyzed genes, lncRNAs can explain more than 20% of expression variation. We observed 25-50% of the putative regulator lncRNAs to be in 'cis' to, i.e., overlapping or located proximally to the target gene. This led us to quantify the global regulatory impact of such cis-located lncRNAs, which was found to be substantially greater than that of trans-located lncRNAs. Additionally, by including statistical interaction terms involving lncRNA-protein pairs as predictors in our regression models, we identified cases where a lncRNA's regulatory effect depends on the presence of a TF or RNA-binding protein. Finally, we created a high-confidence lncRNA-gene regulatory network whose edges are supported by co-expression as well as a plausible mechanism such as cis-action, protein scaffolding or competing endogenous RNAs. Our work is a first attempt to quantify the extent of gene expression control exerted globally by lncRNAs, especially those located proximally to their regulatory targets, in a specific biological (breast cancer) context. It also marks a first step towards systematic reconstruction of lncRNA regulatory networks, going beyond the current paradigm of co-expression networks, and motivates future analyses assessing the generalizability of our findings to additional biological contexts.

Aberrant DNA methylation distorts developmental trajectories in atypical teratoid/rhabdoid tumors

Atypical teratoid/rhabdoid tumors (AT/RTs) are pediatric brain tumors known for their aggressiveness and aberrant but still unresolved epigenetic regulation. To better understand their malignancy, we investigated how AT/RT-specific DNA hypermethylation was associated with gene expression and altered transcription factor binding and how it is linked to upstream regulation. Medulloblastomas, choroid plexus tumors, pluripotent stem cells, and fetal brain were used as references. A part of the genomic regions, which were hypermethylated in AT/RTs similarly as in pluripotent stem cells and demethylated in the fetal brain, were targeted by neural transcriptional regulators. AT/RT-unique DNA hypermethylation was associated with polycomb repressive complex 2 and linked to suppressed genes with a role in neural development and tumorigenesis. Activity of the several NEUROG/NEUROD pioneer factors, which are unable to bind to methylated DNA, was compromised via the suppressed expression or DNA hypermethylation of their target sites, which was also experimentally validated for NEUROD1 in medulloblastomas and AT/RT samples. These results highlight and characterize the role of DNA hypermethylation in AT/RT malignancy and halted neural cell differentiation.

MRAS in coronary artery disease-Unchartered territory

Genome-wide association studies (GWAS) have identified coronary artery disease (CAD) susceptibility locus on chromosome 3q22.3. This locus contains a cluster of several genes that includes muscle rat sarcoma virus (MRAS). Common MRAS variants are also associated with CAD causing risk factors such as hypertension, dyslipidemia, obesity, and type II diabetes. The MRAS gene is an oncogene that encodes a membrane-bound small GTPase. It is involved in a variety of signaling pathways, regulating cell differentiation and cell survival (mitogen-activated protein kinase [MAPK]/extracellular signal-regulated kinase and phosphatidylinositol 3-kinase) as well as acute phase response signaling (tumor necrosis factor [TNF] and interleukin 6 [IL6] signaling). In this review, we will summarize the role of genetic MRAS variants in the etiology of CAD and its comorbidities with the focus on tissue distribution of MRAS isoforms, cell type/tissue specificity, and mode of action of single nucleotide variants in MRAS associated complex traits. Finally, we postulate that CAD risk variants in the MRAS locus are specific to smooth muscle cells and lead to higher levels of MRAS, particularly in arterial and cardiac tissue, resulting in MAPK-dependent tissue hypertrophy or hyperplasia.

Cell-type-specific consequences of mosaic structural variants in hematopoietic stem and progenitor cells

The functional impact and cellular context of mosaic structural variants (mSVs) in normal tissues is understudied. Utilizing Strand-seq, we sequenced 1,133 single-cell genomes from 19 human donors of increasing age, and discovered the heterogeneous mSV landscapes of hematopoietic stem and progenitor cells. While mSVs are continuously acquired throughout life, expanded subclones in our cohort are confined to individuals >60. Cells already harboring mSVs are more likely to acquire additional somatic structural variants, including megabase-scale segmental aneuploidies. Capitalizing on comprehensive single-cell micrococcal nuclease digestion with sequencing reference data, we conducted high-resolution cell-typing for eight hematopoietic stem and progenitor cells. Clonally expanded mSVs disrupt normal cellular function by dysregulating diverse cellular pathways, and enriching for myeloid progenitors. Our findings underscore the contribution of mSVs to the cellular and molecular phenotypes associated with the aging hematopoietic system, and establish a foundation for deciphering the molecular links between mSVs, aging and disease susceptibility in normal tissues.

Identification of drug responsive enhancers by predicting chromatin accessibility change from perturbed gene expression profiles

Individual may response to drug treatment differently due to their genetic variants located in enhancers. These variants can alter transcription factor's (TF) binding strength, affect enhancer's chromatin activity or interaction, and eventually change expression level of downstream gene. Here, we propose a computational framework, PERD, to Predict the Enhancers Responsive to Drug. A machine learning model was trained to predict the genome-wide chromatin accessibility from transcriptome data using the paired expression and chromatin accessibility data collected from ENCODE and ROADMAP. Then the model was applied to the perturbed gene expression data from Connectivity Map (CMAP) and Cancer Drug-induced gene expression Signature DataBase (CDS-DB) and identify drug responsive enhancers with significantly altered chromatin accessibility. Furthermore, the drug responsive enhancers were related to the pharmacogenomics genome-wide association studies (PGx GWAS). Stepping on the traditional drug-associated gene signatures, PERD holds the promise to enhance the causality of drug perturbation by providing candidate regulatory element of those drug associated genes.