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Abstract The bidirectional effect of hyperuricemia on chronic kidney disease (CKD) underscores the importance of hyperuricemia as a risk factor for CKD. We evaluated the effect of hyperuricemia on the presence and development of CKD after considering genetic background by calculating polygenic risk scores (PRSs). We employed genome-wide association study summary statistics—excluding the United Kingdom Biobank (UKB) datasets among published CKD Gen Consortium papers—to calculate the PRSs for CKD in white background subjects. To validate PRS performance, we divided the UKB into two datasets to validate and test the data. We used logistic regression analysis to evaluate the association between hyperuricemia and CKD, and performed Kaplan–Meier survival analysis exclusively for subjects with available follow-up data. In total, 438,253 clinical data and 4,307,940 single nucleotide polymorphisms from 459,155 samples were included. We observed a significant positive association between PRS and CKD and the presence and development of CKD. Hyperuricemia significantly increased CKD risk (adjusted odds ratio 1.55, 95% confidence interval 1.48–1.61). The impact of hyperuricemia on CKD was maintained irrespective of PRS range. In addition, negative interaction between hyperuricemia and PRS for CKD was found. Survival analysis indicates that the presence of hyperuricemia significantly increased the risk of CKD development. The PRS for CKD thoroughly reflects the risk of CKD development. Hyperuricemia is a significant indicator of CKD risk, even after incorporating the genetic risk score for CKD. Irrespective of genetic risk, patients with a prospective risk of developing CKD require uric acid monitoring and management.

Abstract Background Linkage errors that occur according to linkage levels can adversely affect the accuracy and reliability of analysis results. This study aimed to identify the differences in results according to personally identifiable information linkage level, sample size, and analysis methods through empirical analysis. Methods The difference between the results of linkage in directly identifiable information (DII) and indirectly identifiable information (III) linkage levels was set as III linkage based on name, date of birth, and sex and DII linkage based on resident registration number. The datasets linked at each level were named as databaseIII (DBIII) and databaseDII (DBDII), respectively. Considering the analysis results of the DII-linked dataset as the gold standard, descriptive statistics, group comparison, incidence estimation, treatment effect, and moderation effect analysis results were assessed. Results The linkage rates for DBDII and DBIII were 71.1% and 99.7%, respectively. Regarding descriptive statistics and group comparison analysis, the difference in effect in most cases was “none” to “very little.” With respect to cervical cancer that had a relatively small sample size, analysis of DBIII resulted in an underestimation of the incidence in the control group and an overestimation of the incidence in the treatment group (hazard ratio [HR] = 2.62 [95% confidence interval (CI): 1.63–4.23] in DBIII vs. 1.80 [95% CI: 1.18–2.73] in DBDII). Regarding prostate cancer, there was a conflicting tendency with the treatment effect being over or underestimated according to the surveillance, epidemiology, and end results summary staging (HR = 2.27 [95% CI: 1.91–2.70] in DBIII vs. 1.92 [95% CI: 1.70–2.17] in DBDII for the localized stage; HR = 1.80 [95% CI: 1.37–2.36] in DBIII vs. 2.05 [95% CI: 1.67–2.52] in DBDII for the regional stage). Conclusions To prevent distortion of the analyses results in health and medical research, it is important to check that the patient population and sample size by each factor of interest (FOI) are sufficient when different data are linked using DBDII. In cases involving a rare disease or with a small sample size for FOI, there is a high likelihood that a DII linkage is unavoidable.

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 In this study, we investigated the characteristics of gut microbiome in the metabolically healthy obese (MHO) patients, and how they correlate with metabolic and inflammatory profiles. A total of 120 obese people without metabolic comorbidities were recruited, and their clinical phenotypes, metabolic and inflammatory parameters were analysed. The faecal microbial markers originating from bacterial cell and extracellular vesicle (EV) were profiled using 16S rDNA sequencing. The total study population could be classified into two distinct enterotypes (enterotype I: Prevotellaceae-predominant, enterotype II: Akkermansia/Bacteroides-predominant), based on their stool EV-derived microbiome profile. When comparing the metabolic and inflammatory profiles, subjects in enterotype I had higher levels of serum IL-1β [false discovery rate (FDR) q = 0.050] and had a lower level of microbial diversity than enterotype II (Wilcoxon rank-sum test p

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.

Heavy metals are commonly released into the environment through industrial processes such as mining and refining. The rapid industrialization that occurred in South Korea during the 1960s and 1970s contributed significantly to the economy of the country; however, the associated mining and refining led to considerable environmental pollution, and although mining is now in decline in South Korea, the detrimental effects on residents inhabiting the surrounding areas remain. The bioaccumulation of toxic heavy metals leads to metabolic alterations in human homeostasis, with disruptions in this balance leading to various health issues. This study used metabolomics to explore metabolomic alterations in the plasma samples of residents living in mining and refining areas. The results showed significant increases in metabolites involved in glycolysis and the surrounding metabolic pathways, such as glucose-6-phosphate, phosphoenolpyruvate, lactate, and inosine monophosphate, in those inhabiting polluted areas. An investigation of the associations between metabolites and blood clinical parameters through meet-in-the-middle analysis indicated that female residents were more affected by heavy metal exposure, resulting in more metabolomic alterations. For women, inhabiting the abandoned mine area, metabolites in the glycolysis and pentose phosphate pathways, such as ribose-5-phosphate and 3-phosphoglycerate, have shown a negative correlation with albumin and calcium. Finally, Mendelian randomization(MR) was used to determine the causal effects of these heavy metal exposure-related metabolites on heavy metal exposure-related clinical parameters. Metabolite biomarkers could provide insights into altered metabolic pathways related to exposure to toxic heavy metals and improve our understanding of the molecular mechanisms underlying the health effects of toxic heavy metal exposure.

Background: Drug-induced hypersensitivity such as anaphylaxis is an important cause of drug-related morbidity and mortality. Cefaclor is a leading cause of drug induced type I hypersensitivity in Korea, but little is yet known about genetic biomarkers to predict this hypersensitivity reaction. We aimed to evaluate the possible involvement of genes in cefaclor induced type I hypersensitivity. Methods: Whole exome sequencing (WES) and HLA genotyping were performed in 43 patients with cefaclor induced type I hypersensitivity. In addition, homology modeling was performed to identify the binding forms of cefaclor to HLA site. Results: Anaphylaxis was the most common phenotype of cefaclor hypersensitivity (90.69%). WES results show that rs62242177 and rs62242178 located in LIMD1 region were genome-wide significant at the 5 × 10−8 significance level. Cefaclor induced type I hypersensitivity was significantly associated with HLA-DRB1∗04:03 (OR 4.61 [95% CI 1.51–14.09], P

Abstract In radiomics research, the issue of different instruments being used is significant. In this study, we compared three correction methods to reduce the batch effects in radiogenomic data from fluorodeoxyglucose (FDG) PET/CT images of lung cancer patients. Texture features of the FDG PET/CT images and genomic data were retrospectively obtained. The features were corrected with different methods: phantom correction, ComBat method, and Limma method. Batch effects were estimated using three analytic tools: principal component analysis (PCA), the k-nearest neighbor batch effect test (kBET), and the silhouette score. Finally, the associations of features and gene mutations were compared between each correction method. Although the kBET rejection rate and silhouette score were lower in the phantom-corrected data than in the uncorrected data, a PCA plot showed a similar variance. ComBat and Limma methods provided correction with low batch effects, and there was no significant difference in the results of the two methods. In ComBat- and Limma-corrected data, more texture features exhibited a significant association with the TP53 mutation than in those in the phantom-corrected data. This study suggests that correction with ComBat or Limma methods can be more effective or equally as effective as the phantom method in reducing batch effects.

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.

Abstract Background The Rey Complex Figure Test (RCFT) has been widely used to evaluate the neurocognitive functions in various clinical groups with a broad range of ages. However, despite its usefulness, the scoring method is as complex as the figure. Such a complicated scoring system can lead to the risk of reducing the extent of agreement among raters. Although several attempts have been made to use RCFT in clinical settings in a digitalized format, little attention has been given to develop direct automatic scoring that is comparable to experienced psychologists. Therefore, we aimed to develop an artificial intelligence (AI) scoring system for RCFT using a deep learning (DL) algorithm and confirmed its validity. Methods A total of 6680 subjects were enrolled in the Gwangju Alzheimer’s and Related Dementia cohort registry, Korea, from January 2015 to June 2021. We obtained 20,040 scanned images using three images per subject (copy, immediate recall, and delayed recall) and scores rated by 32 experienced psychologists. We trained the automated scoring system using the DenseNet architecture. To increase the model performance, we improved the quality of training data by re-examining some images with poor results (mean absolute error (MAE) $$\ge$$ ≥ 5 [points]) and re-trained our model. Finally, we conducted an external validation with 150 images scored by five experienced psychologists. Results For fivefold cross-validation, our first model obtained MAE = 1.24 [points] and R-squared ( $${R}^{2}$$ R 2 ) = 0.977. However, after evaluating and updating the model, the performance of the final model was improved (MAE = 0.95 [points], $${R}^{2}$$ R 2 = 0.986). Predicted scores among cognitively normal, mild cognitive impairment, and dementia were significantly different. For the 150 independent test sets, the MAE and $${R}^{2}$$ R 2 between AI and average scores by five human experts were 0.64 [points] and 0.994, respectively. Conclusion We concluded that there was no fundamental difference between the rating scores of experienced psychologists and those of our AI scoring system. We expect that our AI psychologist will be able to contribute to screen the early stages of Alzheimer’s disease pathology in medical checkup centers or large-scale community-based research institutes in a faster and cost-effective way.

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.

AimsCardiovascular diseases (CVDs) are the most common cause of death, but they can be effectively managed through appropriate prevention and treatment. An important aspect in preventing CVDs is assessing each individual's comprehensive risk profile, for which various risk engines have been developed. The important keys to CVD risk engines are high reliability and accuracy, which show differences in predictability depending on disease status or race. Framingham risk score (FRS) and the atherosclerotic cardiovascular disease risk equations (ASCVD) were applied to the Korean population to assess their suitability.MethodsA retrospective cohort study was conducted using National Health Insurance Corporation sample cohort from 2003 to 2015. The enrolled participants over 30 years of age and without CVD followed-up for 10 years. We compared the prediction performance of FRS and ASCVD and calculated the relative importance of each covariate.ResultsThe AUCs of FRS (men: 0.750; women: 0.748) were higher than those of ASCVD (men: 0.718; women: 0.727) for both sexes (Delong test P ConclusionWhen applying existing tools to Korean women, there was a noticeable underestimation. To accurately predict the risk of CVD, it was more appropriate to use FRS with men's coefficient in women. Moreover, hypertension was found to be a main risk factor for CVD.

Abstract Background Although preserved ratio impaired spirometry (PRISm) has been determined to have poor prognosis, it is a heterogeneous state, and studies regarding its prognosis in Asians are limited. This study investigated the long-term all-cause and cardiovascular mortality of patients with PRISm compared with those of patients with chronic obstructive pulmonary disease (COPD) and normal individuals in the Korean middle-aged general population. Methods Participants were recruited between 2001 and 2002 from a community-based prospective cohort in South Korea. Mortality data were collected over a 16.5-year mean follow-up period. The all-cause and cardiovascular mortality risks of PRISm were compared between patients with COPD and healthy controls. Results The PRISm group had a mean age of 53.4 years and mean body mass index of 24.9 kg/m2; furthermore, 55.2% of the PRISm patients had never smoked, and the prevalence of comorbidities was not higher than that in the other groups. Compared with normal individuals, PRISm patients did not show increased all-cause mortality, whereas COPD patients showed increased all-cause mortality (PRISm: adjusted hazard ratio [aHR], 1.19; 95% confidence interval [CI], 0.85–1.65; COPD: aHR, 1.34, 95% CI, 1.07–1.69). Furthermore, the PRISm patients did not show increased cardiovascular mortality compared with normal individuals (PRISm: aHR, 1.65; 95% CI, 0.92–2.95; COPD: aHR, 1.83; 95% CI, 1.09–3.07). Conclusion In our population-based cohort, all-cause and cardiovascular mortality risk did not increase in individuals with PRISm compared with normal individuals. Further studies are needed to distinguish a lower-risk subgroup of PRISm with certain characteristics, such as middle-aged, light-smoking Asians without additional cardiovascular risk.

Abstract Exposure to phthalates has been shown to impede the human endocrine system, resulting in deleterious effects on pregnant women and their children. Phthalates modify DNA methylation patterns in infant cord blood. We examined the association between prenatal phthalate exposure and DNA methylation patterns in cord blood in a Korean birth cohort. Phthalate levels were measured in 274 maternal urine samples obtained during late pregnancy and 102 neonatal urine samples obtained at birth, and DNA methylation levels were measured in cord blood samples. For each infant in the cohort, associations between CpG methylation and both maternal and neonate phthalate levels were analyzed using linear mixed models. The results were combined with those from a meta-analysis of the levels of phthalates in maternal and neonatal urine samples, which were also analyzed for MEOHP, MEHHP, MnBP, and DEHP. This meta-analysis revealed significant associations between the methylation levels of CpG sites near the CHN2 and CUL3 genes, which were also associated with MEOHP and MnBP in neonatal urine. When the data were stratified by the sex of the infant, MnBP concentration was found to be associated with one CpG site near the OR2A2 and MEGF11 genes in female infants. In contrast, the concentrations of the three maternal phthalates showed no significant association with CpG site methylation. Furthermore, the data identified distinct differentially methylated regions in maternal and neonatal urine samples following exposure to phthalates. The CpGs with methylation levels that were positively associated with phthalate levels (particularly MEOHP and MnBP) were found to be enriched genes and related pathways. These results indicate that prenatal phthalate exposure is significantly associated with DNA methylation at multiple CpG sites. These alterations in DNA methylation may serve as biomarkers of maternal exposure to phthalates in infants and are potential candidates for investigating the mechanisms by which phthalates impact maternal and neonatal health.

Background Genome-wide association studies (GWAS) on type 2 diabetes mellitus (T2DM) have identified more than 400 distinct genetic loci associated with diabetes and nearly 120 loci for fasting plasma glucose (FPG) and fasting insulin level to date. However, genetic risk factors for the longitudinal deterioration of FPG have not been thoroughly evaluated. We aimed to identify genetic variants associated with longitudinal change of FPG over time. Methods We used two prospective cohorts in Korean population, which included a total of 10,528 individuals without T2DM. GWAS of repeated measure of FPG using linear mixed model was performed to investigate the interaction of genetic variants and time, and meta-analysis was conducted. Genome-wide complex trait analysis was used for heritability calculation. In addition, expression quantitative trait loci (eQTL) analysis was performed using the Genotype-Tissue Expression project. Results A small portion (4%) of the genome-wide single nucleotide polymorphism (SNP) interaction with time explained the total phenotypic variance of longitudinal change in FPG. A total of four known genetic variants of FPG were associated with repeated measure of FPG levels. One SNP (rs11187850) showed a genome-wide significant association for genetic interaction with time. The variant is an eQTL for NOC3 like DNA replication regulator (NOC3L) gene in pancreas and adipose tissue. Furthermore, NOC3L is also differentially expressed in pancreatic β-cells between subjects with or without T2DM. However, this variant was not associated with increased risk of T2DM nor elevated FPG level. Conclusion We identified rs11187850, which is an eQTL of NOC3L, to be associated with longitudinal change of FPG in Korean population.

Abstract Background The longitudinal relationship between adiposity and lung function is controversial. We aimed to investigate the long-term association between adiposity changes and lung function in a middle-aged general Asian population. Methods In total, 5011 participants (average age, 54 years; 45% men) were enrolled from a community-based prospective cohort. During the follow-up period (median 8 years), both spirometry and bio-electrical impedance analysis were performed biannually. Individual slopes of the fat mass index (FMI; fat mass divided by the square of height in meters) and waist-to-hip ratio (WHR) were calculated using linear regression analysis. Multivariate linear mixed regression analysis was used to determine the long-term association between adiposity changes and lung function. Results The FMI was inversely associated with forced vital capacity (FVC) (estimated: − 31.8 mL in men, − 27.8 mL in women) and forced expiratory volume in 1 s (FEV1) (estimated: − 38.2 mL in men, − 17.8 mL in women) after adjusting for baseline age, height, residential area, smoking exposure (pack-years, men only), initial adiposity indices, and baseline lung function. The WHR was also inversely associated with FVC (estimated = − 1242.2 mL) and FEV1 (estimated = − 849.8 mL) in men. The WHR-increased group showed a more rapid decline in lung function than the WHR-decreased group in both the fat-gain and fat-loss groups. Conclusion Adiposity was associated with the long-term impairment of lung function. Central obesity was the main driver of lung function impairment in the middle-aged general Asian population, regardless of fat mass changes.

Abstract Background The pathogenesis of diabetic kidney disease (DKD) is complex, involving metabolic and hemodynamic factors. Although DKD has been established as a heritable disorder and several genetic studies have been conducted, the identification of unique genetic variants for DKD is limited by its multiplex classification based on the phenotypes of diabetes mellitus (DM) and chronic kidney disease (CKD). Thus, we aimed to identify the genetic variants related to DKD that differentiate it from type 2 DM and CKD. Methods We conducted a large-scale genome-wide association study mega-analysis, combining Korean multi-cohorts using multinomial logistic regression. A total of 33,879 patients were classified into four groups—normal, DM without CKD, CKD without DM, and DKD—and were further analyzed to identify novel single-nucleotide polymorphisms (SNPs) associated with DKD. Additionally, fine-mapping analysis was conducted to investigate whether the variants of interest contribute to a trait. Conditional analyses adjusting for the effect of type 1 DM (T1D)-associated HLA variants were also performed to remove confounding factors of genetic association with T1D. Moreover, analysis of expression quantitative trait loci (eQTL) was performed using the Genotype-Tissue Expression project. Differentially expressed genes (DEGs) were analyzed using the Gene Expression Omnibus database (GSE30529). The significant eQTL DEGs were used to explore the predicted interaction networks using search tools for the retrieval of interacting genes and proteins. Results We identified three novel SNPs [rs3128852 (P = 8.21×10−25), rs117744700 (P = 8.28×10−10), and rs28366355 (P = 2.04×10−8)] associated with DKD. Moreover, the fine-mapping study validated the causal relationship between rs3128852 and DKD. rs3128852 is an eQTL for TRIM27 in whole blood tissues and HLA-A in adipose-subcutaneous tissues. rs28366355 is an eQTL for HLA-group genes present in most tissues. Conclusions We successfully identified SNPs (rs3128852, rs117744700, and rs28366355) associated with DKD and verified the causal association between rs3128852 and DKD. According to the in silico analysis, TRIM27 and HLA-A can define DKD pathophysiology and are associated with immune response and autophagy. However, further research is necessary to understand the mechanism of immunity and autophagy in the pathophysiology of DKD and to prevent and treat DKD.

Abstract Asthma and chronic obstructive pulmonary disease (COPD) are two distinct diseases that are associated with chronic inflammation. They share common features in terms of their advanced stages and genetic factors. This study aimed to identify novel genes underlying both asthma and COPD using genome-wide association study (GWAS) to differentiate between the two diseases. We performed a GWAS of asthma and COPD in 7828 Koreans from three hospitals. In addition, we investigated genetic correlations. The UK Biobank dataset was used for the replication studies. We found that rs2961757, located near neuromedin U receptor 2 (NMUR2) on chromosome 5, was genome-wide significant ( $${\upbeta }_{\mathrm{Asthma}-\mathrm{COPD}}$$ β Asthma - COPD = 0.44, P-valueAsthma-COPD = 3.41 × 10−8), and significant results were replicated with the UK Biobank data ( $${\upbeta }_{\mathrm{Asthma}-\mathrm{COPD}}$$ β Asthma - COPD = 0.04, P-valueAsthma-COPD = 0.0431). A positive genetic correlation was observed between asthma and COPD (39.8% in the Korean dataset and 49.8% in the UK Biobank dataset). In this study, 40–45% of the genetic effects were common to asthma and COPD. Moreover, NMUR2 increases the risk of asthma development and suppresses COPD development. This indicates that NMUR2 allows for better differentiation of both diseases, which can facilitate tailored medical therapy.

Abstract Intrinsic immunologic disparity of psoriasis itself, along with chronic inflammation and immunomodulatory anti-psoriatic treatments could be associated with increased risk of malignancy. We aimed to estimate the risk of malignancy in patients with psoriasis by treatment modality compared with that in individuals without psoriasis in Korea. We conducted a nationwide cohort study using the claims database of the National Health Insurance Service from January 2005 to December 2018. A total of 255,471 patients with psoriasis, and age- and sex-matched non-psoriasis participants (1:1 ratio) were enrolled. The adjusted hazard ratios (aHRs) [95% confidence intervals (CIs)] for malignancy without nonmelanoma skin cancer (NMSC) were 1.10 [1.08–1.12] in patients with psoriasis, 1.13 [1.00–1.27], 1.05 [0.97–1.13], and 1.24 [0.84–1.83] in phototherapy, non-biologic systemics, and biologics cohort, respectively. Among the non-biologic systemics cohort, patients treated with cyclosporin showed higher risk of malignancy without NMSC (aHR [95% CI], 1.20 [1.04–1.39]). The risk of malignancy without NMSC in patients with psoriasis was higher than that in individuals without psoriasis. Phototherapy and biologics were not associated with significant increase of risk; however, cyclosporin appeared to increase its risk. Dermatologists should be vigilant about this potential risk while managing patients with psoriasis.

Introduction: Type 2 diabetes (T2D) is associated with severe mental illnesses (SMIs), such as schizophrenia, bipolar disorder, and depression. However, causal relationships between SMIs and T2D remain unclear owing to potential bias in observational studies. We aimed to characterize the causal effect of SMI liability on T2D using two-sample Mendelian randomization (MR).Methods: The causality between liability to SMI and T2D was investigated using the inverse-variance weighted (IVW), MREgger, MR-Egger with a simulation extrapolation, weighted median, and the MR pleiotropy residual sum and outlier method. Similarly, we performed additional MR which can detect the reverse causation effect by switching exposure and outcome for T2D liability for SMI. To further consider pleiotropic effects between SMIs, multivariable MR analysis was performed after accounting for the other traits.Results: In the univariable IVW method, depression showed a causal effect on T2D (odds ratio [OR]: 1.128, 95% confidence interval [CI]: 1.024–1.245, p = 0.014). Multinomial MR more strongly supported these results (IVW OR: 1.197, 95% CI: 1.069, 1.340, p = 0.002; MR-Egger OR: 1.198, 95% CI: 1.062, 1.349, p = 0.003). Bidirectional MR showed absence of reversecausality between depression and T2D. However, causal relationship of bipolar and schizophrenia on T2D was not detected.Discussion: Careful attention is needed for patients with depression regarding T2D prevention and treatment.

BackgroundWe aimed to investigate the incidence of dementia by age and year as well as the population-attributable fractions (PAFs) for known dementia risk factors in Republic of Korea.MethodsA 12-year, nationwide, population-based, retrospective cohort study was conducted. We used customized health information from the National Health Insurance Service (NHIS) data from 2002 to 2017. We analyzed age- and sex-adjusted incidence rates and PAF of dementia for each risk factor such as depression, diabetes, hemorrhagic stroke, ischemic stroke, hypertension, osteoporosis and physical inactivity using Levin’s formula.ResultsOf the 794,448 subjects in the dementia-free cohort, 49,524 (6.2%) developed dementia. Dementia incidence showed annual growth from 1.56 per 1,000 person-years in 2006 to 6.94 per 1,000 person-years in 2017. Of all dementia cases, 34,544 subjects (69.8%) were female and 2,479 subjects (5.0%) were early onset dementia. AD dementia accounted for 66.5% of the total dementia incidence. Considering relative risk and prevalence, physical inactivity attributed the greatest to dementia (PAF, 8.1%), followed by diabetes (PAF, 4.2%), and hypertension (PAF, 2.9%). Altogether, the significant risk factors increased the risk of dementia by 18.0% (overall PAF).ConclusionWe provided the incidence of dementia and PAFs for dementia risk factors in Republic of Korea using a 12-year, nationwide cohort. Encouraging lifestyle modifications and more aggressive control of risk factors may effectively prevent dementia.

Abstract Background As the number of large-scale studies involving multiple organizations producing data has steadily increased, an integrated system for a common interoperable format is needed. In response to the coronavirus disease 2019 (COVID-19) pandemic, a number of global efforts are underway to develop vaccines and therapeutics. We are therefore observing an explosion in the proliferation of COVID-19 data, and interoperability is highly requested in multiple institutions participating simultaneously in COVID-19 pandemic research. Results In this study, a laboratory information management system (LIMS) approach has been adopted to systemically manage various COVID-19 non-clinical trial data, including mortality, clinical signs, body weight, body temperature, organ weights, viral titer (viral replication and viral RNA), and multiorgan histopathology, from multiple institutions based on a web interface. The main aim of the implemented system is to integrate, standardize, and organize data collected from laboratories in multiple institutes for COVID-19 non-clinical efficacy testings. Six animal biosafety level 3 institutions proved the feasibility of our system. Substantial benefits were shown by maximizing collaborative high-quality non-clinical research. Conclusions This LIMS platform can be used for future outbreaks, leading to accelerated medical product development through the systematic management of extensive data from non-clinical animal studies.

Abstract Sarcopenia is an age-related disorder characterised by a progressive decrease in skeletal muscle mass. As the genetic biomarkers for sarcopenia are not yet well characterised, this study aimed to investigate the genetic variations related to sarcopenia in a relatively aged cohort, using genome-wide association study (GWAS) meta-analyses of lean body mass (LBM) in 6961 subjects. Two Korean cohorts were analysed, and subgroup GWAS was conducted for appendicular skeletal muscle mass (ASM) and skeletal muscle index. The effects of significant single nucleotide polymorphisms (SNPs) on gene expression were also investigated using multiple expression quantitative trait loci datasets, differentially expressed gene analysis, and gene ontology analyses. Novel genetic biomarkers were identified for LBM (rs1187118; rs3768582) and ASM (rs6772958). Their related genes, including RPS10, NUDT3, NCF2, SMG7, and ARPC5, were differently expressed in skeletal muscle tissue, while GPD1L was not. Furthermore, the ‘mRNA destabilisation’ biological process was enriched for sarcopenia. Our study identified RPS10, NUDT3, and GPD1L as significant genetic biomarkers for sarcopenia. These genetic loci were related to lipid and energy metabolism, suggesting that genes involved in metabolic dysregulation may lead to the pathogenesis of age-related sarcopenia.

Abstract We sought to determine the minimum number of observations needed to determine hand hygiene (HH) compliance among healthcare workers. The study was conducted at a referral hospital in South Korea. We retrospectively analyzed the result of HH monitoring from January to December 2018. HH compliance was calculated by dividing the number of observed HH actions by the total number of opportunities. Optimal HH compliance rates were calculated based on adherence to the six-step technique recommended by the World Health Organization. The minimum number of required observations (n) was calculated by the following equation using overall mean value (ρ), absolute precision (d), and confidence interval (CI) (1 − α) [the equation: $${\text{n}} \ge Z_{\alpha /2}^{2} \times \rho \times \left( {1 - \rho } \right)/d^{2}$$ n ≥ Z α / 2 2 × ρ × 1 - ρ / d 2 ]. We considered ds of 5%, 10%, 20%, and 30%, with CIs of 99%, 95%, and 90%. During the study period, 8791 HH opportunities among 1168 healthcare workers were monitored. Mean HH compliance and optimal HH compliance rates were 80.3% and 59.7%, respectively. The minimum number of observations required to determine HH compliance rates ranged from 2 ( $$d$$ d : 30%, CI: 90%) to 624 ( $$d$$ d : 5%, CI: 99%), and that for optimal HH compliance ranged from 5 ( $$d$$ d : 30%, CI: 90%) to 642 ( $$d$$ d : 5%, CI: 99%). Therefore, we found that our hospital required at least five observations to determine optimal HH compliance.

Background Epidemiological data have shown that vitamin D deficiency is highly prevalent in Korea. Genetic factors influencing vitamin D deficiency in humans have been studied in Europe but are less known in East Asian countries, including Korea. We aimed to investigate the genetic factors related to vitamin D levels in Korean people using a genome-wide association study (GWAS). Methods We included 12,642 subjects from three different genetic cohorts consisting of Korean participants. The GWAS was performed on 7,590 individuals using linear or logistic regression meta- and mega-analyses. After identifying significant single nucleotide polymorphisms (SNPs), we calculated heritability and performed replication and rare variant analyses. In addition, expression quantitative trait locus (eQTL) analysis for significant SNPs was performed. Results rs12803256, in the actin epsilon 1, pseudogene (ACTE1P) gene, was identified as a novel polymorphism associated with vitamin D deficiency. SNPs, such as rs11723621 and rs7041, in the group-specific component gene (GC) and rs11023332 in the phosphodiesterase 3B (PDE3B) gene were significantly associated with vitamin D deficiency in both meta- and mega-analyses. The SNP heritability of the vitamin D concentration was estimated to be 7.23%. eQTL analysis for rs12803256 for the genes related to vitamin D metabolism, including glutamine-dependent NAD(+) synthetase (NADSYN1) and 7-dehydrocholesterol reductase (DHCR7), showed significantly different expression according to alleles. Conclusion The genetic factors underlying vitamin D deficiency in Korea included polymorphisms in the GC, PDE3B, NADSYN1, and ACTE1P genes. The biological mechanism of a non-coding SNP (rs12803256) for DHCR7/NADSYN1 on vitamin D concentrations is unclear, warranting further investigations.

The gut microbiome influences the development of allergic diseases during early childhood. However, there is a lack of comprehensive understanding of microbiome-host crosstalk. Here, we analyzed the influence of gut microbiome dynamics in early childhood on atopic dermatitis (AD) and the potential interactions between host and microbiome that control this homeostasis. We analyzed the gut microbiome in 346 fecal samples (6–36 months; 112 non-AD, 110 mild AD, and 124 moderate to severe AD) from the Longitudinal Cohort for Childhood Origin of Asthma and Allergic Disease birth cohort. The microbiome-host interactions were analyzed in animal and in vitro cell assays. Although the gut microbiome maturated with age in both AD and non-AD groups, its development was disordered in the AD group. Disordered colonization of short-chain fatty acids (SCFA) producers along with age led to abnormal SCFA production and increased IgE levels. A butyrate deficiency and downregulation of GPR109A and PPAR-γ genes were detected in AD-induced mice. Insufficient butyrate decreases the oxygen consumption rate of host cells, which can release oxygen to the gut and perturb the gut microbiome. The disordered gut microbiome development could aggravate balanced microbiome-host interactions, including immune responses during early childhood with AD.

Abstract Asthma is a complex disease that is reportedly associated with insomnia. However, the causal directionality of this association is still unclear. We used asthma and insomnia-associated single nucleotide polymorphisms (SNPs) and genome-wide association study (GWAS) summary statistics to test the causal directionality between insomnia and asthma via Mendelian randomization (MR) analysis. We also performed a cross-trait meta-analysis using UK Biobank GWAS summary statistics and a gene–environment interaction study using data from UK Biobank. The interaction of genetic risk score for asthma (GRSasthma) with insomnia on asthma was tested by logistic regression. Insomnia was a risk factor for the incidence of asthma, as revealed by three different methods of MR analysis. However, asthma did not act as a risk factor for insomnia. The cross-trait meta-analysis identified 28 genetic loci shared between asthma and insomnia. In the gene–environment interaction study, GRSasthma interacted with insomnia to significantly affect the risk of asthma. The results of this study highlight the importance of insomnia as a risk factor of asthma, and warrant further analysis of the mechanism through which insomnia affects the risk of asthma.

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 This study investigated whether achieving a higher degree of knee flexion after TKA promoted the ability to perform high-flexion activities, as well as patient satisfaction and quality of life. Methods Clinical data on 912 consecutive primary TKA cases involving a single high-flexion posterior stabilized fixed-bearing prosthesis were retrospectively analyzed. Demographic and clinical data were collected, including knee flexion angle, the ability to perform high-flexion activities, and patient satisfaction and quality of life. Results Of the cases, 619 (68%) achieved > 130° of knee flexion after TKA (high flexion group). Knee flexion angle and clinical scores showed significant annual changes, with the maximum improvement seen at 5 years and slight deterioration observed at 10 years postoperatively. In the high flexion group, more than 50% of the patients could not kneel or squat, and 35% could not stand up from on the floor. Multivariate analysis revealed that > 130° of knee flexion, the ability to perform high-flexion activities (sitting cross-legged and standing up from the floor), male gender, and bilateral TKA were significantly associated with patient satisfaction after TKA, while the ability to perform high-flexion activities (sitting cross-legged and standing up from the floor), male gender, and bilateral TKA were significantly associated with patient quality of life after TKA. Conclusions High knee flexion angle (> 130°) after TKA increased the ease of high-flexion activities and patient satisfaction. The ease of high-flexion activities also increased quality of life after TKA in our Asian patients, who frequently engage in these activities in daily life.

Abstract Multiple environmental factors could interact with a single genetic factor to affect disease phenotypes. We used Struct-LMM to identify genetic variants that interacted with environmental factors related to body mass index (BMI) using data from the Korea Association Resource. The following factors were investigated: alcohol consumption, education, physical activity metabolic equivalent of task (PAMET), income, total calorie intake, protein intake, carbohydrate intake, and smoking status. Initial analysis identified 7 potential single nucleotide polymorphisms (SNPs) that interacted with the environmental factors (P value

Abstract Medical costs have recently increased in South Korea due to the rising rate of asthma. Primary clinics serve an important role in asthma management, as they are the first stop for patients presenting with symptoms. The Health Insurance Review and Assessment Service (HIRA) in South Korea has assessed asthma-management quality since 2013, but studies are lacking on whether these assessments have been performed properly and contribute toward reducing asthma exacerbations. Therefore, we investigated whether the HIRA’s quality assessments have decreased asthma exacerbations using national health insurance claims data from 2013 to 2017 of 83,375 primary-clinic and 15,931 tertiary-hospital patients with asthma. These patients were classified into four groups based on disease severity according to the monthly prescribed amount of asthma medication using K-means clustering. The associations between HIRA assessments and asthma exacerbation were analyzed using a generalized estimating equation. Our results showed that exacerbation odds gradually decreased as the HIRA assessments progressed, especially in the mild-severity group, and that exacerbation risk among patients with asthma decreased in the order of assessment grades: “Unsatisfactory,” “Satisfactory,” and “Tertiary.” Therefore, we may conclude that asthma exacerbations may decrease with high quality asthma management; appropriate quality assessment could be helpful in reducing asthma exacerbations.

Abstract Background Healthcare-associated pneumonia (HCAP) is a heterogeneous disease. We redefined nursing-home- and hospital-associated infections (NHAI) group by revising existing HCAP risk factors. The NHAI group comprised nursing home residents with a poor functional status, or recent (past 90 days) hospitalization or recent (past 180 days) antibiotic therapy. Our aim was to determine whether respiratory microbiota profiles are related to newly defined NHAI group in critically ill patients on mechanical ventilation. Methods The 180 endotracheal aspirates (ETAs) from 60 mechanically ventilated ICU patients (NHAI group, n = 24; non-NHAI group, n = 36) were prospectively collected on days 1, 3 and 7 in a university hospital. The bacterial community profiles of the ETAs were explored by 16S rRNA gene sequencing. A phylogenetic-tree-based microbiome association test (TMAT), generalized linear mixed models (GLMMs), the Wilcoxon test and the reference frame method were used to analyze the association between microbiome abundance and disease phenotype. Results The relative abundance of the genus Corynebacterium was significantly higher in the pneumonia than in the non-pneumonia group. The microbiome analysis revealed significantly lower α-diversity in the NHAI group than in the non-NHAI group. In the analysis of β-diversity, the structure of the microbiome also differed significantly between the two groups (weighted UniFrac distance, Adonis, p

Introduction: Obesity results from an imbalance in the intake and expenditure of calories that leads to lifestyle-related diseases. Although genome-wide association studies (GWAS) have revealed many obesity-related genetic factors, the interactions of these factors and calorie intake remain unknown. This study aimed to investigate interactions between calorie intake and the polygenic risk score (PRS) of BMI. Methods: Three cohorts, i.e., from the Korea Association REsource (KARE; n = 8,736), CArdioVAscular Disease Association Study (CAVAS; n = 9,334), and Health EXAminee (HEXA; n = 28,445), were used for this study. BMI-related genetic loci were selected from previous GWAS. Two scores, PRS, and association (a)PRS, were used; the former was determined from 193 single-nucleotide polymorphisms (SNPs) from 5 GWAS datasets, and the latter from 62 SNPs (potentially associated) from 3 Korean cohorts (meta-analysis, p < 0.01). Results: PRS and aPRS were significantly associated with BMI in all 3 cohorts but did not exhibit a significant interaction with total calorie intake. Similar results were obtained for obesity. PRS and aPRS were significantly associated with obesity but did not show a significant interaction with total calorie intake. We further analyzed the interaction with protein, fat, and carbohydrate intake. The results were similar to those for total calorie intake, with PRS and aPRS found to not be associated with the interaction of any of the 3 nutrition components for either BMI or obesity. Discussion: The interaction of BMI PRS with calorie intake was investigated in 3 independent Korean cohorts (total n = 35,094) and no interactions were found between PRS and calorie intake for obesity.

Abstract Background Histidine-rich protein-2 (HRP2)-based rapid diagnostic tests (RDTs) are the only RDTs recommended for malaria diagnosis in Uganda. However, the emergence of Plasmodium falciparum histidine rich protein 2 and 3 (pfhrp2 and pfhrp3) gene deletions threatens their usefulness as malaria diagnostic and surveillance tools. The pfhrp2 and pfhrp3 gene deletions surveillance was conducted in P. falciparum parasite populations in Uganda. Methods Three-hundred (n = 300) P. falciparum isolates collected from cross-sectional malaria surveys in symptomatic individuals in 48 districts of eastern and western Uganda were analysed for the presence of pfhrp2 and pfhrp3 genes. Presence of parasite DNA was confirmed by PCR amplification of the 18s rRNA gene, msp1 and msp2 single copy genes. Presence or absence of deletions was confirmed by amplification of exon1 and exon2 of pfhrp2 and pfhrp3 using gene specific PCR. Results Overall, pfhrp2 and pfhrp3 gene deletions were detected in 29/300 (9.7%, 95% CI 6.6–13.6%) parasite isolates. The pfhrp2 gene was deleted in 10/300 (3.3%, 95% CI 1.6–6.0%) isolates, pfhrp3 in 9/300 (3.0%, 95% CI 1.4–5.6%) while both pfhrp2 and pfhrp3 were deleted in 10/300 (3.3%, 95% CI 1.6–6.0%) parasite isolates. Proportion of pfhrp2/3 deletions was higher in the eastern 14.7% (95% CI 9.7–20.0%) compared to the western region 3.1% (95% CI 0.8–7.7%), p = 0.001. Geographical location was associated with gene deletions aOR 6.25 (2.02–23.55), p = 0.003. Conclusions This is the first large-scale survey reporting the presence of pfhrp2/3 gene deletions in P. falciparum isolates in Uganda. Roll out of RDTs for malaria diagnosis should take into consideration the existence of pfhrp2/3 gene deletions particularly in areas where they were detected. Periodic pfhrp2/3 surveys are recommended to inform future decisions for deployment of alternative RDTs.

Background/AimsThe survival rate of gastric cancer (GC) is known to be higher in patients with a family history (FH) of GC. There is an association between a polymorphism in the transforming growth factor-β1 (TGFB1) gene and the risk of GC in patients with first-degree relatives with GC. This study was performed to investigate whether a FH affects GC outcomes according to the TGFB1 C-509T polymorphism.Methods : TGFB1 was genotyped by the polymerase chain reaction-restriction fragment length polymorphism method in 1,143 GC patients, including 216 patients (18.9%) with first-degree relatives with GC.Results : The proportion of stage I–II GCs was significantly higher in patients with a FH than in those without a FH of GC (83.8 vs 74.9%, p=0.005). The association between a FH of GC and stage I–II GC was not significant in subgroups divided based on the TGFB1 C-509T polymorphism and sex. A FH did not affect the overall survival rate of GC in patient with all stages and each stage. The overall survival rates were not significantly different between patients with the CC and CT/TT genotypes of the TGFB1-509 polymorphism.Conclusion : sPatient with a FH of GC had lower cancer stage (I–II) at diagnosis than those without a FH of GC, but there was no significant difference in overall survival between the patients with and without a FH of GC. A FH did not influence the tumor stage or overall survival in patients stratified by the presence of the TGFB1 C-509T polymorphism.

Introduction Lymphangioleiomyomatosis (LAM) is a rare low-grade metastasising disease characterised by cystic lung destruction. The genetic basis of LAM remains incompletely determined, and the disease cell-of-origin is uncertain. We analysed the possibility of a shared genetic basis between LAM and cancer, and LAM and pulmonary function. Methods The results of genome-wide association studies of LAM, 17 cancer types and spirometry measures (forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), FEV1/FVC ratio and peak expiratory flow (PEF)) were analysed for genetic correlations, shared genetic variants and causality. Genomic and transcriptomic data were examined, and immunodetection assays were performed to evaluate pleiotropic genes. Results There were no significant overall genetic correlations between LAM and cancer, but LAM correlated negatively with FVC and PEF, and a trend in the same direction was observed for FEV1. 22 shared genetic variants were uncovered between LAM and pulmonary function, while seven shared variants were identified between LAM and cancer. The LAM-pulmonary function shared genetics identified four pleiotropic genes previously recognised in LAM single-cell transcriptomes: ADAM12, BNC2, NR2F2 and SP5. We had previously associated NR2F2 variants with LAM, and we identified its functional partner NR3C1 as another pleotropic factor. NR3C1 expression was confirmed in LAM lung lesions. Another candidate pleiotropic factor, CNTN2, was found more abundant in plasma of LAM patients than that of healthy women. Conclusions This study suggests the existence of a common genetic aetiology between LAM and pulmonary function.

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.

The recent rise in the prevalence of chronic allergic diseases among children has increased disease burden and reduced quality of life, especially for children with comorbid allergic diseases. Predicting the occurrence of allergic diseases can help prevent its onset for those in high risk groups. Herein, we aimed to construct prediction models for asthma, atopic dermatitis (AD), and asthma-AD comorbidity (also known as atopic march) using a genome-wide association study (GWAS) and family history data from patients of Korean heritage. Among 973 patients and 481 healthy controls, we evaluated single nucleotide polymorphism (SNP) heritability for each disease using genome-based restricted maximum likelihood (GREML) analysis. We then compared the performance of prediction models constructed using Least Absolute Shrinkage and Selection Operator (LASSO) and penalized ridge regression methods. Our results indicate that the addition of family history risk scores to the prediction model greatly increase the predictability of asthma and asthma-AD comorbidity. However, prediction of AD was mostly attributable to GWAS SNPs.

Chronic rhinosinusitis (CRS) is characterized according to the presence or absence of nasal polyps (NPs) and displays nasal microbiota dysbiosis. However, optimal sampling methods of the nasal microbiome in CRS have not been identified. We aimed to assess the microbial composition in patients with CRS, comparing different sampling methods (swab and tissue biopsy), tissue types (uncinate tissue and NP), and disease subtypes. Samples were obtained by swabbing the middle meatus and taking a biopsy of uncinate tissue (UT) in patients with CRS with (CRSwNP, N = 8) or without NP (CRSsNP, N = 6) and controls (N = 8). NPs were also harvested in CRSwNP. DNAs were extracted from fifty-two samples and analyzed by 16S rRNA gene amplicon sequencing. As a result, a great interpersonal variance was observed in nasal swabs, while UT samples presented distinct microbiome with low inter-personal differences. Moreover, the UT microbiomes were further differentiated into three clusters which are associated with disease status (control, CRSsNP, and CRSwNP). Compared to UT, NP revealed a unique microbiome profile with significantly less bacterial diversity. Prevotella was the genus whose abundance was negatively correlated with disease severity in NP. In conclusion, tissue samples are better specimens than nasal swabs for assessing the microbiomes of CRS patients. Several bacteria in UT and NP tissues revealed an association with clinical severity of CRSwNP.

Multiple studies have demonstrated the effects of type 2 diabetes (T2D) on various human diseases; however, most of these were observational epidemiological studies that suffered from many potential biases including reported confounding and reverse causations. In this article, we investigated whether cancer and vascular disease can be affected by T2D-related traits, including fasting plasma glucose (FPG), 2-h postprandial glucose (2h-PG), and glycated hemoglobin A1c (HbA1c) levels, by using Mendelian randomization (MR). The summary statistics for FPG, 2h-PG, and HbA1c level were obtained through meta-analyses of large-scale genome-wide association studies that included data from 133,010 nondiabetic individuals from collaborating Meta-analysis of Glucose and Insulin Related Traits Consortium studies. Thereafter, based on the statistical assumptions for MR analyses, the most reliable approaches including inverse-variance-weighted (IVW), MR-Egger, MR-Egger with a simulation extrapolation (SIMEX), weighted median, and MR-pleiotropy residual sum and outlier (MR-PRESSO) methods were applied to identify traits affected by FPG, 2h-PG, and HbAlc. We found that coronary artery disease is affected by FPG, as per the IVW [log odds ratio (logOR): 0.21; P = 0.012], MR-Egger (SIMEX) (logOR: 0.22; P = 0.014), MR-PRESSO (logOR: 0.18; P = 0.045), and weighted median (logOR: 0.29; P < 0.001) methods but not as per the MR-Egger (logOR: 0.13; P = 0.426) approach. Furthermore, low-density lipoprotein cholesterol levels are affected by HbA1c, as per the IVW [beta (B): 0.23; P = 0.015), MR-Egger (B: 0.45; P = 0.046), MR-Egger (SIMEX) (B: 0.27; P = 0.007), MR-PRESSO (B; 0.14; P = 0.010), and the weighted median (B: 0.15; P = 0.012] methods. Further studies of the associated biological mechanisms are required to validate and understand the disease-specific differences identified in the TD2-related causal effects of each trait.

Heterogeneity of lung function levels and risk for developing chronic obstructive pulmonary disease (COPD) among people exposed to the same environmental risk factors, such as cigarette smoking, suggest an important role of genetic factors in COPD susceptibility. To investigate the possible role of different genetic factors in COPD susceptibility across ethnicities. We used a population-stratified analysis for: (i) identifying ethnic-specific genetic susceptibility loci, (ii) developing ethnic-specific polygenic risk prediction models using those SNPs, and (iii) validating the models with an independent dataset. We elucidated substantial differences in SNP heritability and susceptibility loci for the disease across ethnicities. Furthermore, the application of three ethnic-specific prediction models to an independent dataset showed that the best performance is achieved when the prediction model is applied to a dataset with the matched ethnic sample. Our study validates the necessity of considering ethnic differences in COPD risk; understanding these differences might help in preventing COPD and developing therapeutic strategies.

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.

BackgroundPlasmodium falciparum histidine-rich protein 2 (HRP2)-based rapid diagnostic tests (RDTs) are exclusively recommended for malaria diagnosis in Uganda; however, their functionality can be affected by parasite-related factors that have not been investigated in field settings.MethodsUsing a cross-sectional design, we analysed 219 RDT-/microscopy+ and 140 RDT+/microscopy+ dried blood spots obtained from symptomatic children aged 2-10 years from 48 districts in Uganda between 2017 and 2019. We aimed to investigate parasite-related factors contributing to false RDT results by molecular characterization of parasite isolates. ArcGIS software was used to map the geographical distribution of parasites. Statistical analysis was performed using chi-square or Fisher's exact tests, with P ≤ 0.05 indicating significance. Odds ratios (ORs) were used to assess associations, while logistic regression was performed to explore possible factors associated with false RDT results.ResultsThe presence of parasite DNA was confirmed in 92.5% (332/359) of the blood samples. The levels of agreement between the HRP2 RDT and PCR assay results in the (RDT+/microscopy+) and (RDT-/microscopy+) sample subsets were 97.8% (137/140) and 10.9% (24/219), respectively. Factors associated with false-negative RDT results in the (RDT-/microscopy+) samples were parasite density (ConclusionThis is the first evaluation and report of the contributions of pfhrp2/3 gene deletion, non-P. falciparum species, and low-density infections to false-negative RDT results under field conditions in Uganda. In view of these findings, the use of HRP2 RDTs should be reconsidered; possibly, switching to combination RDTs that target alternative antigens, particularly in affected areas, may be beneficial. Future evaluations should consider larger and more representative surveys covering other regions of Uganda.

Abstract Background Metabolic syndrome is a risk factor for type 2 diabetes and cardiovascular disease. We identified common genetic variants that alter the risk for metabolic syndrome in the Korean population. To isolate these variants, we conducted a multiple-genotype and multiple-phenotype genome-wide association analysis using the family-based quasi-likelihood score (MFQLS) test. For this analysis, we used 7211 and 2838 genotyped study subjects for discovery and replication, respectively. We also performed a multiple-genotype and multiple-phenotype analysis of a gene-based single-nucleotide polymorphism (SNP) set. Results We found an association between metabolic syndrome and an intronic SNP pair, rs7107152 and rs1242229, in SIDT2 gene at 11q23.3. Both SNPs correlate with the expression of SIDT2 and TAGLN, whose products promote insulin secretion and lipid metabolism, respectively. This SNP pair showed statistical significance at the replication stage. Conclusions Our findings provide insight into an underlying mechanism that contributes to metabolic syndrome.

Abstract Background A Mendelian transmission produces phenotypic and genetic relatedness between family members, giving family-based analytical methods an important role in genetic epidemiological studies—from heritability estimations to genetic association analyses. With the advance in genotyping technologies, whole-genome sequence data can be utilized for genetic epidemiological studies, and family-based samples may become more useful for detecting de novo mutations. However, genetic analyses employing family-based samples usually suffer from the complexity of the computational/statistical algorithms, and certain types of family designs, such as incorporating data from extended families, have rarely been used. Results We present a Workbench for Integrated Superfast Association studies for Related Data (WISARD) programmed in C/C++. WISARD enables the fast and a comprehensive analysis of SNP-chip and next-generation sequencing data on extended families, with applications from designing genetic studies to summarizing analysis results. In addition, WISARD can automatically be run in a fully multithreaded manner, and the integration of R software for visualization makes it more accessible to non-experts. Conclusions Comparison with existing toolsets showed that WISARD is computationally suitable for integrated analysis of related subjects, and demonstrated that WISARD outperforms existing toolsets. WISARD has also been successfully utilized to analyze the large-scale massive sequencing dataset of chronic obstructive pulmonary disease data (COPD), and we identified multiple genes associated with COPD, which demonstrates its practical value.

Abstract Background Undirected graphical models or Markov random fields have been a popular class of models for representing conditional dependence relationships between nodes. In particular, Markov networks help us to understand complex interactions between genes in biological processes of a cell. Local Poisson models seem to be promising in modeling positive as well as negative dependencies for count data. Furthermore, when zero counts are more frequent than are expected, excess zeros should be considered in the model. Methods We present a penalized Poisson graphical model for zero inflated count data and derive an expectation-maximization (EM) algorithm built on coordinate descent. Our method is shown to be effective through simulated and real data analysis. Results Results from the simulated data indicate that our method outperforms the local Poisson graphical model in the presence of excess zeros. In an application to a RNA sequencing data, we also investigate the gender effect by comparing the estimated networks according to different genders. Our method may help us in identifying biological pathways linked to sex hormone regulation and thus understanding underlying mechanisms of the gender differences. Conclusions We have presented a penalized version of zero inflated spatial Poisson regression and derive an efficient EM algorithm built on coordinate descent. We discuss possible improvements of our method as well as potential research directions associated with our findings from the RNA sequencing data.

Abstract Background Copy number variation (CNV) is known to play an important role in the genetics of complex diseases and several methods have been proposed to detect association of CNV with phenotypes of interest. Statistical methods for CNV association analysis can be categorized into two different strategies. First, the copy number is estimated by maximum likelihood and association of the expected copy number with the phenotype is tested. Second, the observed probe intensity measurements can be directly used to detect association of CNV with the phenotypes of interest. Results For each strategy we provide a statistic that can be applied to extended families. The computational efficiency of the proposed methods enables genome-wide association analysis and we show with simulation studies that the proposed methods outperform other existing approaches. In particular, we found that the first strategy is always more efficient than the second strategy no matter whether copy numbers for each individual are well identified or not. With the proposed methods, we performed genome-wide CNV association analyses of hematological trait, hematocrit, on 521 Korean family samples. Conclusions We found that statistical analysis with the expected copy number is more powerful than the statistic with the probe intensity measurements regardless of the accuracy of the estimation of copy numbers.

Over the past decade, the detection of gene-gene interactions has become more and more popular in the field of genome-wide association studies (GWASs). The goal of the GWAS is to identify genetic susceptibility to complex diseases by assaying and analyzing hundreds of thousands of single-nucleotide polymorphisms. However, such tests are computationally demanding and methodologically challenging. Recently, a simple but powerful method, named “BOolean Operation-based Screening and Testing” (BOOST), was proposed for genome-wide gene-gene interaction analyses. BOOST was designed with a Boolean representation of genotype data and is approximately equivalent to the log-linear model. It is extremely fast, and genome-wide gene-gene interaction analyses can be completed within a few hours. However, BOOST can not adjust for covariate effects, and its type-1 error control is not correct. Thus, we considered two-step approaches for gene-gene interaction analyses. First, we selected gene-gene interactions with BOOST and applied logistic regression with covariate adjustments to select gene-gene interactions. We applied the two-step approach to type 2 diabetes (T2D) in the Korea Association Resource (KARE) cohort and identified some promising pairs of single-nucleotide polymorphisms associated with T2D.