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Abstract Patients with severe eosinophilic asthma often require systemic medication, including corticosteroids and anti-type 2 (T2) cytokine biologics, to control the disease. While anti-IL5 and anti-IL4Rα antibodies suppress the effects of IL-4, IL-5 and IL-13, the molecular pathways modified by these biologics that are associated with clinical improvement remain unclear. Therefore, we aimed to describe the effects of T2-targeting biologics on the gene expression of blood immune cells. We conducted single-cell RNA sequencing (scRNA-seq) of peripheral blood mononuclear cells (PBMCs) from eight patients with severe eosinophilic asthma treated with mepolizumab, reslizumab, or dupilumab. PBMCs were obtained before the initiation of biologics and at 1- and 6-month timepoints after the initiation of treatment to elucidate treatment-induced changes. During treatment, the proportions of T cells/natural killer (NK) cells, myeloid cells, and B cells did not change. However, the composition of classical monocytes (CMs) changed: IL1B + CMs were reduced, and S100A + CMs were increased. The subsets of T cells also changed, and significant downregulation of the NF-κB pathway was observed. The genes related to the NF-κB pathway were suppressed across T/NK, myeloid, and B cells. The transcriptional landscape did not significantly change after the first month of treatment, but marked changes occurred at six-month intervals. In conclusion, regardless of the type of biologics used, suppression of T2-mediated pathways ultimately reduces the expression of genes related to NF-κB signaling in circulating immune cells. Further studies are warranted to identify potential biomarkers related to treatment response and long-term outcomes. Clinical trial registration number: NCT05164939

Conflicting findings have been reported regarding the association between Agent Orange (AO) exposure and type 2 diabetes. This study aimed to examine whether AO exposure is associated with the development of type 2 diabetes and to verify the causal relationship between AO exposure and type 2 diabetes by combining DNA methylation with DNA genotype analyses. An epigenome-wide association study and DNA genotype analyses of the blood of AO-exposed and AO-unexposed individuals with type 2 diabetes and that of healthy controls were performed. Methylation quantitative trait locus and Mendelian randomisation analyses were performed to evaluate the causal effect of AO-exposure-identified CpGs on type 2 diabetes. AO-exposed individuals with type 2 diabetes were associated with six hypermethylated CpG sites (cg20075319, cg21757266, cg05203217, cg20102280, cg26081717, and cg21878650) and one hypo-methylated CpG site (cg07553761). Methylation quantitative trait locus analysis showed the methylation levels of some CpG sites (cg20075319, cg20102280, and cg26081717) to be significantly different. Mendelian randomisation analysis showed that CpG sites that were differentially methylated in AO-exposed individuals were causally associated with type 2 diabetes; the reverse causal effect was not significant. These findings reflect the need for further epigenetic studies on the causal relationship between AO exposure and type 2 diabetes.

Abstract Although depression is an emerging disorder affecting many people worldwide, most genetic studies have been performed in European descent populations. Herein, a genome-wide association study (GWAS) was conducted in Korean population to elucidate the genomic loci associated with depressive symptoms. Two independent cohorts were used as discovery datasets, which consisted of 6474 (1484 cases and 4990 controls) and 1654 (557 cases and 1097 controls) Korean participants, respectively. The participants were divided into case and control groups based on the Beck Depression Inventory (BDI). Meta-analysis using the two cohorts revealed that rs6945590 was significantly associated with the risk of depressive symptoms [P = 2.83 × 10−8; odds ratio (OR) = 1.23; 95% confidence interval (CI): 1.15–1.33]. This association was validated in other independent cohorts which were another Korean cohort (258 cases and 1757 controls) and the East Asian study of the Psychiatric Genomics Consortium (PGC) (12,455 cases and 85,548 controls). The predicted expression levels of thromboxane A synthase 1 gene (TBXAS1), which encodes the enzyme thromboxane A synthase 1 and participates in the arachidonic acid (AA) cascade, was significantly decreased in the whole blood tissues of the participants with depressive symptoms. Furthermore, Mendelian randomization (MR) analysis showed a causal association between TBXAS1 expression and the risk of depressive symptoms. In conclusion, as the number of risk alleles (A) of rs6945590 increased, TBXAS1 expression decreased, which subsequently caused an increase in the risk of depressive symptoms.

Abstract Background More than 200 asthma-associated genetic variants have been identified in genome-wide association studies (GWASs). Expression quantitative trait loci (eQTL) data resources can help identify causal genes of the GWAS signals, but it can be difficult to find an eQTL that reflects the disease state because most eQTL data are obtained from normal healthy subjects. Methods We performed a blood eQTL analysis using transcriptomic and genotypic data from 433 Korean asthma patients. To identify asthma-related genes, we carried out colocalization, Summary-based Mendelian Randomization (SMR) analysis, and Transcriptome-Wide Association Study (TWAS) using the results of asthma GWASs and eQTL data. In addition, we compared the results of disease eQTL data and asthma-related genes with two normal blood eQTL data from Genotype-Tissue Expression (GTEx) project and a Japanese study. Results We identified 340,274 cis-eQTL and 2,875 eGenes from asthmatic eQTL analysis. We compared the disease eQTL results with GTEx and a Japanese study and found that 64.1% of the 2,875 eGenes overlapped with the GTEx eGenes and 39.0% with the Japanese eGenes. Following the integrated analysis of the asthmatic eQTL data with asthma GWASs, using colocalization and SMR methods, we identified 15 asthma-related genes specific to the Korean asthmatic eQTL data. Conclusions We provided Korean asthmatic cis-eQTL data and identified asthma-related genes by integrating them with GWAS data. In addition, we suggested these asthma-related genes as therapeutic targets for asthma. We envisage that our findings will contribute to understanding the etiological mechanisms of asthma and provide novel therapeutic targets.

Background: In previous studies, several asthma phenotypes were identified using clinical and demographic parameters. Transcriptional phenotypes were mainly identified using sputum and bronchial cells. Objective: We aimed to investigate asthma phenotypes via clustering analysis using clinical variables and compare the transcription levels among clusters using gene expression profiling of the blood. Methods: Clustering analysis was performed using 6 parameters: age of asthma onset, body mass index, pack-years of smoking, forced expiratory volume in 1 s (FEV1), FEV1/forced vital capacity, and blood eosinophil counts. Peripheral blood mononuclear cells (PBMCs) were isolated from whole blood samples and RNA was extracted from selected PBMCs. Transcriptional profiles were generated (Illumina NovaSeq 6000) and analyzed using the reference genome and gene annotation files (hg19.refGene.gft). Pathway enrichment analysis was conducted using GO, KEGG, and REACTOME databases. Results: In total, 355 patients with asthma were included in the analysis, of whom 72 (20.3%) had severe asthma. Clustering of the 6 parameters revealed 4 distinct subtypes. Cluster 1 (n = 63) had lower predicted FEV1 % and higher pack-years of smoking and neutrophils in sputum. Cluster 2 (n = 43) had a higher proportion and number of eosinophils in sputum and blood, and severe airflow limitation. Cluster 3 (n = 110) consisted of younger subjects with atopic features. Cluster 4 (n = 139) included features of late-onset mild asthma. Differentially expressed genes between clusters 1 and 2 were related to inflammatory responses and cell activation. Th17 cell differentiation and interferon gamma-mediated signaling pathways were related to neutrophilic inflammation in asthma. Conclusion: Four clinical clusters were differentiated based on clinical parameters and blood eosinophils in adult patients with asthma form the Cohort for Reality and Evolution of Adult Asthma in Korea (COREA) cohort. Gene expression profiling and molecular pathways are novel means of classifying asthma phenotypes.

Abstract Background Correctional institution inmates have reduced access to dental care; however, a quantitative assessment of their oral health condition has not yet been performed in South Korea. Therefore, this study aimed to assess dental caries and compare the prevalence of dental caries and associated factors between inmates and the general South Korean population. Methods The dental records of two detention centers in South Korea were retrospectively analyzed to assess the clinical oral health condition of inmates using the Decayed, Missing, and Filled Teeth (DMFT) index and self-reported questionnaire. These data were compared with similar data obtained from the Korea National Health and Nutrition Examination Survey (KNHANES) for the general South Korean population. Results In total, 642 inmates were analyzed and compared with 13,345 KNHANES participants in the KNHANES. The inmate and KNHANES groups demonstrated significant intergroup differences, with a higher prevalence of untreated caries, DMFT, decayed teeth (DT), and missing teeth (MT) values among the inmates. The prevalence of untreated caries decreased according to the history of dental pain in the inmate group but increased in the KNHANES group. The decrease in DMFT with a history of dental pain was significant only in the inmate group. Furthermore, self-rated oral health was significantly associated with prevalence of untreated caries, DMFT, DT, MT, and filled teeth (FT) in the inmate group but with prevalence of untreated caries, DMFT, DT, and MT in the KNHANES group. It was found that this is because there is an interaction effect by the group. Conclusions The oral health of the inmate group was significantly poorer than that of the general group. Since DMFT, DT, MT, and FT values and prevalence of untreated caries in the inmate group were significantly related to their self-rated oral health, suggesting that self-rated oral health should be incorporated into the dental health screenings of correctional institution inmates.

Abstract Established genetic risk factors for Alzheimer’s disease (AD) account for only a portion of AD heritability. The aim of this study was to identify novel associations between genetic variants and AD-specific brain atrophy. We conducted genome-wide association studies for brain magnetic resonance imaging measures of hippocampal volume and entorhinal cortical thickness in 2643 Koreans meeting the clinical criteria for AD (n = 209), mild cognitive impairment (n = 1449) or normal cognition (n = 985). A missense variant, rs77359862 (R274W), in the SHANK-associated RH Domain Interactor (SHARPIN) gene was associated with entorhinal cortical thickness (p = 5.0 × 10−9) and hippocampal volume (p = 5.1 × 10−12). It revealed an increased risk of developing AD in the mediation analyses. This variant was also associated with amyloid-β accumulation (p = 0.03) and measures of memory (p = 1.0 × 10−4) and executive function (p = 0.04). We also found significant association of other SHARPIN variants with hippocampal volume in the Alzheimer’s Disease Neuroimaging Initiative (rs3417062, p = 4.1 × 10−6) and AddNeuroMed (rs138412600, p = 5.9 × 10−5) cohorts. Further, molecular dynamics simulations and co-immunoprecipitation indicated that the variant significantly reduced the binding of linear ubiquitination assembly complex proteins, SHPARIN and HOIL-1 Interacting Protein (HOIP), altering the downstream NF-κB signaling pathway. These findings suggest that SHARPIN plays an important role in the pathogenesis of AD.

Abstract Background Transcriptomic profiles can improve our understanding of the phenotypic molecular basis of biological research, and many statistical methods have been proposed to identify differentially expressed genes (DEGs) under two or more conditions with RNA-seq data. However, statistical analyses with RNA-seq data are often limited by small sample sizes, and global variance estimates of RNA expression levels have been utilized as prior distributions for gene-specific variance estimates, making it difficult to generalize the methods to more complicated settings. We herein proposed a Bartlett-Adjusted Likelihood-based LInear mixed model approach (BALLI) to analyze more complicated RNA-seq data. The proposed method estimates the technical and biological variances with a linear mixed-effects model, with and without adjusting small sample bias using Bartlkett’s corrections. Results We conducted extensive simulations to compare the performance of BALLI with those of existing approaches (edgeR, DESeq2, and voom). Results from the simulation studies showed that BALLI correctly controlled the type-1 error rates at various nominal significance levels and produced better statistical power and precision estimates than those of other competing methods in various scenarios. Furthermore, BALLI was robust to variation of library size. It was also successfully applied to Holstein milk yield data, illustrating its practical value. Conclusions; BALLI is statistically more efficient and valid than existing methods, and we conclude that it is useful for identifying DEGs in RNA-seq analysis.

Genome-wide association studies of gastric cancer (GC) cases have revealed common gastric cancer susceptibility loci with low effect size. We investigated rare variants with high effect size via whole-exome sequencing (WES) of subjects with familial clustering of gastric cancer. WES of DNAs from the blood of 19 gastric cancer patients and 36 unaffected family members from 14 families with two or more gastric cancer patients were tested. Linkage analysis combined with association tests were performed using Pedigree Variant Annotation, Analysis, and Search Tool (pVAAST) software. Based on the logarithm of odds (LOD) and permutation-based composite likelihood ratio test (CLRT) from pVAAST, MUC4 was identified as a predisposing gene (LOD P-value = 1.9×10-5; permutation-based P-value of CLRT ≤ 9.9×10-9). In a larger cohort consisting of 597 GC patients and 9,759 healthy controls genotyped with SNP array, we discovered common variants in MUC4 regions (rs148735556, rs11717039, and rs547775645) significantly associated with GC supporting the association of MUC4 with gastric cancer. And the MUC4 variants were found in higher frequency in The Cancer Genome Atlas Study (TCGA) germline samples of patients with multiple cancer types. Immunohistochemistry indicated that MUC4 was downregulated in the noncancerous gastric mucosa of subjects with MUC4 germline missense variants, suggesting that loss of the protective function of MUC4 predisposes an individual to gastric cancer. Rare variants in MUC4 can be novel gastric cancer susceptibility loci in Koreans possessing the familial clustering of gastric cancer.

Background: Schizophrenia is a major psychotic disorder with complex genetic underpinnings. Clozapine is one of the representative antipsychotics for its unique and superior efficacy. The current understandings of clozapine' s mechanism do not fully explain the favorable therapeutic properties of clozapine, in which the differential gene activation related to the pathophysiology of schizophrenia may be involved. Therefore, studying the transcriptomic changes induced by clozapine could contribute to the advancement of schizophrenia treatments. Aims & Objectives: We aimed to investigate cell type-specific clozapine-induced transcriptional changes in mouse prefrontal cortex through single-cell RNA sequencing (scRNA-seq). The goal of this study was to provide important insights into the mechanism of action of clozapine and examine its associations with genes related to the etiology of schizophrenia. Method: In this study, clozapine was systemically injected into male C58BL/6 mice for 21 consecutive days, and single-cell RNA sequencing was applied to their prefrontal cortical tissue samples. Differentially expressed genes (DEGs) for each cell type, including microglia, astrocytes, neurons, endothelial cells, and vascular smooth muscle cells, were identified through single-cell RNA sequencing. Pathways and intercellular interactions associated with these DEGs were then analyzed. Additionally, a comparative analysis with human databases was conducted, using the toxicogenomics database (CTD), genetic loci implicated in schizophrenia, and genes with evidence of interaction with clozapine. Results: Clozapine-induced changes in gene expression were most prominent in microglia, and the cell population clusters within microglia were altered by clozapine exposure. Pathway analyses highlighted TNF-α signaling via NF-κ B, IFN-γ response, IFN-α response, and p53 pathway as particularly engaged by clozapine. Cell-cell interaction analysis demonstrated the clozapine-induced interactive changes among microglia, endothelial cells, and vascular smooth muscle cells. Comparative analysis with human data also revealed enriched clozapine-induced DEGs in microglia. As a result, eleven genes, including Nfkb1, Nfe2l2, Egr1, Fos, and Atp6v1b2, were elucidated to have convergent evidence. Discussion & Conclusion: By using scRNA-seq, we identified discrete cell types and their alterations in the mouse prefrontal cortex. While microglia are mainly impacted by clozapine exposure, other cell types also display distinct changes. Single-cell RNA sequencing could provide important insights into the mechanisms of action of clozapine, a representative antipsychotic with superior efficacy, which has links to the genetic background of pathogenetic and therapeutic mechanisms in schizophrenia. [ABSTRACT FROM AUTHOR]