MR-GGI: accurate inference of gene-gene interactions using Mendelian randomization.

Background: Researchers have long studied the regulatory processes of genes to uncover their functions. Gene regulatory network analysis is one of the popular approaches for understanding these processes, requiring accurate identification of interactions among the genes to establish the gene regulatory network. Advances in genome-wide association studies and expression quantitative trait loci studies have led to a wealth of genomic data, facilitating more accurate inference of gene-gene interactions.

Elucidating immunological characteristics of the adenoma-carcinoma sequence in colorectal cancer patients in South Korea using a bioinformatics approach.

Colorectal cancer (CRC) is one of the top five most common and life-threatening malignancies worldwide. Most CRC develops from advanced colorectal adenoma (ACA), a precancerous stage, through the adenoma-carcinoma sequence. However, its underlying mechanisms, including how the tumor microenvironment changes, remain elusive.

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).

A rigorous benchmarking of alignment-based HLA typing algorithms for RNA-seq data.

Accurate identification of human leukocyte antigen (HLA) alleles is essential for various clinical and research applications, such as transplant matching and drug sensitivities. Recent advances in RNA-seq technology have made it possible to impute HLA types from sequencing data, spurring the development of a large number of computational HLA typing tools. However, the relative performance of these tools is unknown, limiting the ability for clinical and biomedical research to make informed choices regarding which tools to use.

A scalable approach to characterize pleiotropy across thousands of human diseases and complex traits using GWAS summary statistics.

Genome-wide association studies (GWASs) across thousands of traits have revealed the pervasive pleiotropy of trait-associated genetic variants. While methods have been proposed to characterize pleiotropic components across groups of phenotypes, scaling these approaches to ultra-large-scale biobanks has been challenging. Here, we propose FactorGo, a scalable variational factor analysis model to identify and characterize pleiotropic components using biobank GWAS summary data.

Novel insight into the etiology of ischemic stroke gained by integrative multiome-wide association study.

Stroke, characterized by sudden neurological deficits, is the second leading cause of death worldwide. Although genome-wide association studies (GWAS) have successfully identified many genomic regions associated with ischemic stroke (IS), the genes underlying risk and their regulatory mechanisms remain elusive. Here, we integrate a large-scale GWAS (N = 1 296 908) for IS together with molecular QTLs data, including mRNA, splicing, enhancer RNA (eRNA), and protein expression data from up to 50 tissues (total N = 11 588).

A scalable variational approach to characterize pleiotropic components across thousands of human diseases and complex traits using GWAS summary statistics.

Genome-wide association studies (GWAS) across thousands of traits have revealed the pervasive pleiotropy of trait-associated genetic variants. While methods have been proposed to characterize pleiotropic components across groups of phenotypes, scaling these approaches to ultra large-scale biobanks has been challenging. Here, we propose FactorGo, a scalable variational factor analysis model to identify and characterize pleiotropic components using biobank GWAS summary data.

Novel insight into the etiology of ischemic stroke gained by integrative transcriptome-wide association study.

Stroke, characterized by sudden neurological deficits, is the second leading cause of death worldwide. Although genome-wide association studies (GWAS) have successfully identified many genomic regions associated with ischemic stroke (IS), the genes underlying risk and their regulatory mechanisms remain elusive. Here, we integrate a large-scale GWAS (N=1,296,908) for IS together with mRNA, splicing, enhancer RNA (eRNA) and protein expression data (N=11,588) from 50 tissues.

An approach to studying a very rare neurodegenerative disease using a disease with higher prevalence with shared pathways and genes: Cerebral adrenoleukodystrophy and Alzheimer's disease.

Cerebral adrenoleukodystrophy (cALD) is a rare neurodegenerative disease characterized by inflammatory demyelination in the central nervous system. Another neurodegenerative disease with a high prevalence, Alzheimer's disease (AD), shares many common features with cALD such as cognitive impairment and the alleviation of symptoms by erucic acid. We investigated cALD and AD in parallel to study the shared pathological pathways between a rare disease and a more common disease.

Integrative transcriptome-wide analysis of atopic dermatitis for drug repositioning.

Atopic dermatitis (AD) is one of the most common inflammatory skin diseases, which significantly impact the quality of life. Transcriptome-wide association study (TWAS) was conducted to estimate both transcriptomic and genomic features of AD and detected significant associations between 31 expression quantitative loci and 25 genes. Our results replicated well-known genetic markers for AD, as well as 4 novel associated genes.

A Deep Learning Approach with Data Augmentation to Predict Novel Spider Neurotoxic Peptides.

As major components of spider venoms, neurotoxic peptides exhibit structural diversity, target specificity, and have great pharmaceutical potential. Deep learning may be an alternative to the laborious and time-consuming methods for identifying these peptides. However, the major hurdle in developing a deep learning model is the limited data on neurotoxic peptides.

Rare loss-of-function variants in type I IFN immunity genes are not associated with severe COVID-19.

A recent report found that rare predicted loss-of-function (pLOF) variants across 13 candidate genes in TLR3- and IRF7-dependent type I IFN pathways explain up to 3.5% of severe COVID-19 cases. We performed whole-exome or whole-genome sequencing of 1,864 COVID-19 cases (713 with severe and 1,151 with mild disease) and 15,033 ancestry-matched population controls across 4 independent COVID-19 biobanks.

MARS: leveraging allelic heterogeneity to increase power of association testing.

In standard genome-wide association studies (GWAS), the standard association test is underpowered to detect associations between loci with multiple causal variants with small effect sizes. We propose a statistical method, Model-based Association test Reflecting causal Status (MARS), that finds associations between variants in risk loci and a phenotype, considering the causal status of variants, only requiring the existing summary statistics to detect associated risk loci. Utilizing extensive simulated data and real data, we show that MARS increases the power of detecting true associated risk loci compared to previous approaches that consider multiple variants, while controlling the type I error.

An Integrative Transcriptomic Analysis of Systemic Juvenile Idiopathic Arthritis for Identifying Potential Genetic Markers and Drug Candidates.

Systemic juvenile idiopathic arthritis (sJIA) is a rare subtype of juvenile idiopathic arthritis, whose clinical features are systemic fever and rash accompanied by painful joints and inflammation. Even though sJIA has been reported to be an autoinflammatory disorder, its exact pathogenesis remains unclear. In this study, we integrated a meta-analysis with a weighted gene co-expression network analysis (WGCNA) using 5 microarray datasets and an RNA sequencing dataset to understand the interconnection of susceptibility genes for sJIA.

Fully automated web-based tool for identifying regulatory hotspots.

Background: Regulatory hotspots are genetic variations that may regulate the expression levels of many genes. It has been of great interest to find those hotspots utilizing expression quantitative trait locus (eQTL) analysis. However, it has been reported that many of the findings are spurious hotspots induced by various unknown confounding factors.

Bioaccumulation and Toxicity Studies of Lead and Mercury in Laying Hens: Effects on Laying Performance, Blood Metabolites, Egg Quality and Organ Parameters.

This study investigated bioaccumulation and toxicity derived from heavy metals in laying hens. The 160 52-week old laying hens were divided into 5 treatments with 8 replicates of 4 birds per pen. The treatments consisted of the control diet (without heavy metals), control diet with half the available dosage (AD, 5 ppm lead and 0.

Meta-Analysis of Polymyositis and Dermatomyositis Microarray Data Reveals Novel Genetic Biomarkers.

Polymyositis (PM) and dermatomyositis (DM) are both classified as idiopathic inflammatory myopathies. They share a few common characteristics such as inflammation and muscle weakness. Previous studies have indicated that these diseases present aspects of an auto-immune disorder; however, their exact pathogenesis is still unclear.

Integrative genomic and transcriptomic analysis of genetic markers in Dupuytren's disease.

Background: Dupuytren's disease (DD) is a fibroproliferative disorder characterized by thickening and contracting palmar fascia. The exact pathogenesis of DD remains unknown.

Results: In this study, we identified co-expressed gene set (DD signature) consisting of 753 genes via weighted gene co-expression network analysis.

Molecular origin of AuNPs-induced cytotoxicity and mechanistic study.

Gold nanoparticles (AuNPs) with diverse physicochemical properties are reported to affect biological systems differently, but the relationship between the physicochemical properties of AuNPs and their biological effects is not clearly understood. Here, we aimed to elucidate the molecular origins of AuNP-induced cytotoxicity and their mechanisms, focusing on the surface charge and structural properties of modified AuNPs. We prepared a library of well-tailored AuNPs exhibiting various functional groups and surface charges.

Meta- and cross-species analyses of insulin resistance based on gene expression datasets in human white adipose tissues.

Ample evidence indicates that insulin resistance (IR) is closely related to white adipose tissue (WAT), but the underlying mechanisms of IR pathogenesis are still unclear. Using 352 microarray datasets from seven independent studies, we identified a meta-signature which comprised of 1,413 genes. Our meta-signature was also enriched in overall WAT in in vitro and in vivo IR models.

Modelling APOE ɛ3/4 allele-associated sporadic Alzheimer's disease in an induced neuron.

The recent generation of induced neurons by direct lineage conversion holds promise for in vitro modelling of sporadic Alzheimer's disease. Here, we report the generation of induced neuron-based model of sporadic Alzheimer's disease in mice and humans, and used this system to explore the pathogenic mechanisms resulting from the sporadic Alzheimer's disease risk factor apolipoprotein E (APOE) ɛ3/4 allele. We show that mouse and human induced neurons overexpressing mutant amyloid precursor protein in the background of APOE ɛ3/4 allele exhibit altered amyloid precursor protein (APP) processing, abnormally increased production of amyloid-β42 and hyperphosphorylation of tau.

Electromagnetized gold nanoparticles mediate direct lineage reprogramming into induced dopamine neurons in vivo for Parkinson's disease therapy.

Electromagnetic fields (EMF) are physical energy fields generated by electrically charged objects, and specific ranges of EMF can influence numerous biological processes, which include the control of cell fate and plasticity. In this study, we show that electromagnetized gold nanoparticles (AuNPs) in the presence of specific EMF conditions facilitate an efficient direct lineage reprogramming to induced dopamine neurons in vitro and in vivo. Remarkably, electromagnetic stimulation leads to a specific activation of the histone acetyltransferase Brd2, which results in histone H3K27 acetylation and a robust activation of neuron-specific genes.

Inhibitory Effects of Novel SphK2 Inhibitors on Migration of Cancer Cells.

Background: Cell migration is an essential process for survival and differentiation of mammalian cells. Numerous diseases are induced or influenced by inappropriate regulation of cell migration, which plays a key role in cancer cell metastasis. In fact, very few anti-metastasis drugs are available on the market.