Risk prediction and interaction analysis using polygenic risk score of type 2 diabetes in a Korean population.

Joint modelling of genetic and environmental risk factors can provide important information to predict the risk of type 2 diabetes (T2D). Therefore, to predict the genetic risk of T2D, we constructed a polygenic risk score (PRS) using genotype data of one Korean cohort, KARE (745 cases and 2549 controls), and the genome-wide association study summary statistics of Biobank Japan. We evaluated the performance of PRS in an independent Korean cohort, HEXA (5684 cases and 35,703 controls). Individuals with T2D had a significantly higher mean PRS than controls (0.492 vs. - 0.078, p ≈ 0 ). PRS predicted the risk of T2D with an AUC of 0.658 (95% CI 0.651-0.666). We also evaluated interaction between PRS and waist circumference (WC) in the HEXA cohort. PRS exhibited a significant sub-multiplicative interaction with WC (ORinteraction 0.991, 95% CI 0.987-0.995, pinteraction = 4.93 × 10-6) in T2D. The effect of WC on T2D decreased as PRS increased. The sex-specific analyses produced similar interaction results, revealing a decreased WC effect on T2D as the PRS increased. In conclusion, the risk of WC for T2D may differ depending on PRS and those with a high PRS might develop T2D with a lower WC threshold. Our findings are expected to improve risk prediction for T2D and facilitate the identification of individuals at an increased risk of T2D.

Evolution of Cell-Type-Specific RNA Aptamers via Live Cell-Based SELEX.

Live cell-based SELEX (Systematic Evolution of Ligand EXponential enrichment) is a promising approach for identifying aptamers that can selectively bind to a cell-surface receptor or recognize a particular target cell population. In particular, it offers a facile selection strategy for some special cell-surface proteins that are originally glycosylated or heavily posttranslationally modified and are unavailable in their native/active conformation after in vitro expression and purification. In this chapter, we describe a generalized procedure for evolution of cell type-specific RNA aptamers targeting a cell membrane bound target by combining the live cell-based SELEX strategy with high-throughput sequencing (HTS) and bioinformatics analysis.

Structured time-dependent inverse regression (STIR).

We propose and study structured time-dependent inverse regression (STIR), a novel sufficient dimension reduction model, to analyze longitudinally measured, correlated biomarkers in relation to an outcome. The time structure is accommodated in an inverse regression model for the markers that can be applied both to equally and unequally spaced time points for each sample. The inverse regression structure also naturally accommodates retrospectively sampled markers, that is, markers measured in case-control studies. We estimate the corresponding linear combinations of the markers, the reduction, using least squares. We show that under additional distributional assumptions the reduction contains sufficient information about the outcome. In extensive simulations the STIR linear combinations perform well in predictive models based on samples of realistic size. A Wald-type test for association of a particular marker with outcome at any time point based on the STIR reduction has better power overall than assessing associations based on logistic or linear regression models that include all longitudinally measured markers as independent predictors. As illustrations we estimate the STIR reductions for a cohort study of diabetes and hyperlipidemia and a case-control study of brain cancer with multiple longitudinally measured biomarkers. We assess the STIR reductions' predictive performance and identify outcome-associated biomarkers.

Factors Influencing Frontline Screening Nurses' Depression as a Long-Term Impact of COVID-19.

Frontline screening nurses experienced exhaustion and depressive symptoms as a long-term impact of COVID-19. This study aimed to explore fatigue, depression, and empowerment among frontline screening nurses and examine the factors influencing depression. This was a descriptive cross-sectional study. The study included 140 frontline screening nurses in South Korea recruited from February to March 2021. The measures included a fatigue scale, the Text of Items Measuring Empowerment (TIME), and the Center for Epidemiological Studies Depression Scale (CES-D). The STROBE checklist was used for reporting aspects of the cross-sectional design. Frontline screening nurses showed high fatigue scores (M = 3.47, SD = 0.55), and 55.7% (n = 78) of them were depressed and had low empowerment scores (M = 3.53, SD = 0.69). Empowerment and fatigue were predictors of depression. Increased empowerment and decreased fatigue were important in decreasing depression. Therefore, efforts to provide sufficient staffing, screening for depression, and listening to nurses' voices are necessary.

Multiplexed Ultrasensitive Sample-to-Answer RT-LAMP Chip for the Identification of SARS-CoV-2 and Influenza Viruses.

Prompt on-site diagnosis of SARS-CoV-2 with other respiratory infections will have minimized the global impact of the COVID-19 pandemic through rapid, effective management. However, no such multiplex point-of-care (POC) chip has satisfied a suitable sensitivity of gold-standard nucleic acid amplification tests (NAATs). Here, a rapid multiplexed ultrasensitive sample-to-answer loop-mediated isothermal amplification (MUSAL) chip operated by simple LED-driven photothermal amplification to detect six targets from single-swab sampling is presented. First, the MUSAL chip allows ultrafast on-chip sample preparation with ≈500-fold preconcentration at a rate of 1.2 mL min-1 . Second, the chip enables contamination-free amplification using autonomous target elution into on-chip reagents by photothermal activation. Finally, the chip accomplishes multiplexed on-chip diagnostics of SARS-CoV-2 and influenza viruses with a limit of detection (LoD) of 0.5 copies µL-1 . The rapid, ultrasensitive, cost-effective sample-to-answer chip with a multiplex capability will allow timely management of various pandemics situations that may be faced shortly.

The Effect of Dicer Knockout on RNA Interference Using Various Dicer Substrate Small Interfering RNA (DsiRNA) Structures.

Small interfering RNAs (siRNAs) are artificial molecules used to silence genes of interest through the RNA interference (RNAi) pathway, mediated by the endoribonuclease Dicer. Dicer-substrate small interfering RNAs (DsiRNAs) are an alternative to conventional 21-mer siRNAs, with an increased effectiveness of up to 100-fold compared to traditional 21-mer designs. DsiRNAs have a novel asymmetric design that allows them to be processed by Dicer into the desired conventional siRNAs. DsiRNAs are a useful tool for sequence-specific gene silencing, but the molecular mechanism underlying their increased efficacy is not precisely understood. In this study, to gain a deeper understanding of Dicer function in DsiRNAs, we designed nicked DsiRNAs with and without tetra-loops to target a specific mRNA sequence, established a Dicer knockout in the HCT116 cell line, and analyzed the efficacy of various DsiRNAs on RNAi-mediated gene silencing activity. The gene silencing activity of all DsiRNAs was reduced in Dicer knockout cells. We demonstrated that tetra-looped DsiRNAs exhibited increased efficacy for gene silencing, which was mediated by Dicer protein. Thus, this study improves our understanding of Dicer function, a key component of RNAi silencing, which will inform RNAi research and applications.

KIM-1/TIM-1 is a Receptor for SARS-CoV-2 in Lung and Kidney.

SARS-CoV-2 precipitates respiratory distress by infection of airway epithelial cells and is often accompanied by acute kidney injury. We report that Kidney Injury Molecule-1/T cell immunoglobulin mucin domain 1 (KIM-1/TIM-1) is expressed in lung and kidney epithelial cells in COVID-19 patients and is a receptor for SARS-CoV-2. Human and mouse lung and kidney epithelial cells express KIM-1 and endocytose nanoparticles displaying the SARS-CoV-2 spike protein (virosomes). Uptake was inhibited by anti-KIM-1 antibodies and TW-37, a newly discovered inhibitor of KIM-1-mediated endocytosis. Enhanced KIM-1 expression by human kidney tubuloids increased uptake of virosomes. KIM-1 binds to the SARS-CoV-2 Spike protein in vitro . KIM-1 expressing cells, not expressing angiotensin-converting enzyme 2 (ACE2), are permissive to SARS-CoV-2 infection. Thus, KIM-1 is an alternative receptor to ACE2 for SARS-CoV-2. KIM-1 targeted therapeutics may prevent and/or treat COVID-19.

Sub-multiplicative interaction between polygenic risk score and household coal use in relation to lung adenocarcinoma among never-smoking women in Asia.

We previously identified 10 lung adenocarcinoma susceptibility loci in a genome-wide association study (GWAS) conducted in the Female Lung Cancer Consortium in Asia (FLCCA), the largest genomic study of lung cancer among never-smoking women to date. Furthermore, household coal use for cooking and heating has been linked to lung cancer in Asia, especially in Xuanwei, China. We investigated the potential interaction between genetic susceptibility and coal use in FLCCA. We analyzed GWAS-data from Taiwan, Shanghai, and Shenyang (1472 cases; 1497 controls), as well as a separate study conducted in Xuanwei (152 cases; 522 controls) for additional analyses. We summarized genetic susceptibility using a polygenic risk score (PRS), which was the weighted sum of the risk-alleles from the 10 previously identified loci. We estimated associations between a PRS, coal use (ever/never), and lung adenocarcinoma with multivariable logistic regression models, and evaluated potential gene-environment interactions using likelihood ratio tests. There was a strong association between continuous PRS and lung adenocarcinoma among never coal users (Odds Ratio (OR) = 1.69 (95% Confidence Interval (CI) = 1.53, 1.87), p=1 × 10-26). This effect was attenuated among ever coal users (OR = 1.24 (95% CI: 1.03, 1.50), p = 0.02, p-interaction = 6 × 10-3). We observed similar attenuation among coal users from Xuanwei. Our study provides evidence that genetic susceptibility to lung adenocarcinoma among never-smoking Asian women is weaker among coal users. These results suggest that lung cancer pathogenesis may differ, at least partially, depending on exposure to coal combustion products. Notably, these novel findings are among the few instances of sub-multiplicative gene-environment interactions in the cancer literature.

Comparing two health literacy measurements used for assessing older adults' medication adherence.

AIMS AND OBJECTIVES: To compare two health literacy measurements' ability to assess older adults' medication adherence by using the Korean Health Literacy Screening Questions (KHLSQ) and the Modified Korean Functional Health Literacy Test (M-KFHLT), and to identify an appropriate health literacy measurement. BACKGROUND: Lower health literacy has been associated with poorer medication adherence. Thus, health professionals should evaluate the available health literacy assessment instruments they are using and choose an appropriate instrument to assess health literacy to increase older adults' medication adherence. DESIGN: Following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist, a descriptive, cross-sectional study was conducted. METHODS: From November 2017-May 2018, 116 community-dwelling older adults were recruited in South Korea. Questionnaires were completed during a face-to-face interview with each participant in a private room; health literacy was assessed using the KHLSQ and the M-KFHLT and medication adherence using the Morisky Medication Adherence Scale. RESULTS: Health literacy assessed using the KHLSQ was found to be a predictor of medication adherence, but was not a predictor when measured by the M-KFHLT. Having low income, multiple chronic diseases and vision problems were also significant factors related to medication adherence. CONCLUSIONS: This study suggests that health literacy was negatively associated with medication adherence. Furthermore, KHLSQ is an appropriate tool for healthcare providers to use when assessing health literacy to predict older adults' medication adherence. RELEVANCE TO CLINICAL PRACTICE: This finding indicated that healthcare providers should select an appropriate health literacy measurement that suits their purposes and the population they serve, particularly for older adults.

Tuberculosis infection and lung adenocarcinoma: Mendelian randomization and pathway analysis of genome-wide association study data from never-smoking Asian women.

We investigated whether genetic susceptibility to tuberculosis (TB) influences lung adenocarcinoma development among never-smokers using TB genome-wide association study (GWAS) results within the Female Lung Cancer Consortium in Asia. Pathway analysis with the adaptive rank truncated product method was used to assess the association between a TB-related gene-set and lung adenocarcinoma using GWAS data from 5512 lung adenocarcinoma cases and 6277 controls. The gene-set consisted of 31 genes containing known/suggestive associations with genetic variants from previous TB-GWAS. Subsequently, we followed-up with Mendelian Randomization to evaluate the association between TB and lung adenocarcinoma using three genome-wide significant variants from previous TB-GWAS in East Asians. The TB-related gene-set was associated with lung adenocarcinoma (p = 0.016). Additionally, the Mendelian Randomization showed an association between TB and lung adenocarcinoma (OR = 1.31, 95% CI: 1.03, 1.66, p = 0.027). Our findings support TB as a causal risk factor for lung cancer development among never-smoking Asian women.

Nanophotonic Cell Lysis and Polymerase Chain Reaction with Gravity-Driven Cell Enrichment for Rapid Detection of Pathogens.

Rapid and precise detection of pathogens is a critical step in the prevention and identification of emergencies related to health and biosafety as well as the clinical management of community-acquired urinary tract infections or sexually transmitted diseases. However, a conventional culture-based pathogen diagnostic method is time-consuming, permitting physicians to use antibiotics without ample clinical data. Here, we present a nanophotonic Light-driven Integrated cell lysis and polymerase chain reaction (PCR) on a chip with Gravity-driven cell enrichment Health Technology (LIGHT) for rapid precision detection of pathogens (<20 min). We created the LIGHT, which has the three functions of (1) selective enrichment of pathogens, (2) photothermal cell lysis, and (3) photonic PCR on a chip. We designed the gravity-driven cell enrichment via a nanoporous membrane on a chip that allows an effective bacterial enrichment of 40 000-fold from a 1 mL sample in 2 min. We established a light-driven photothermal lysis of preconcentrated bacteria within 1 min by designing the network of nanoplasmonic optical antenna on a chip for ultrafast light-to-heat conversion, created the nanoplasmonic optical antenna network-based ultrafast photonic PCR on a chip, and identified Escherichia coli. Finally, we demonstrated the end-point detection of up to 103 CFU/mL of E. coli in 10 min. We believe that our nanophotonic LIGHT will provide rapid and precise identification of pathogens in both developing and developed countries.

Development of Web-Based Nomograms to Predict Treatment Response and Prognosis of Epithelial Ovarian Cancer.

PURPOSE: Discovery of models predicting the exact prognosis of epithelial ovarian cancer (EOC) is necessary as the first step of implementation of individualized treatment. This study aimed to develop nomograms predicting treatment response and prognosis in EOC. MATERIALS AND METHODS: We comprehensively reviewed medical records of 866 patients diagnosed with and treated for EOC at two tertiary institutional hospitals between 2007 and 2016. Patients' clinico-pathologic characteristics, details of primary treatment, intra-operative surgical findings, and survival outcomes were collected. To construct predictive nomograms for platinum sensitivity, 3-year progression-free survival (PFS), and 5-year overall survival (OS), we performed stepwise variable selection by measuring the area under the receiver operating characteristic curve (AUC) with leave-one-out cross-validation. For model validation, 10-fold cross-validation was applied. RESULTS: The median length of observation was 42.4 months (interquartile range, 25.7 to 69.9 months), during which 441 patients (50.9%) experienced disease recurrence. The median value of PFS was 32.6 months and 3-year PFS rate was 47.8% while 5-year OS rate was 68.4%. The AUCs of the newly developed nomograms predicting platinum sensitivity, 3-year PFS, and 5-year OS were 0.758, 0.841, and 0.805, respectively. We also developed predictive nomograms confined to the patients who underwent primary debulking surgery. The AUCs for platinum sensitivity, 3-year PFS, and 5-year OS were 0.713, 0.839, and 0.803, respectively. CONCLUSION: We successfully developed nomograms predicting treatment response and prognosis of patients with EOC. These nomograms are expected to be useful in clinical practice and designing clinical trials.

A unified genetic association test robust to latent population structure for a count phenotype.

Confounding caused by latent population structure in genome-wide association studies has been a big concern despite the success of genome-wide association studies at identifying genetic variants associated with complex diseases. In particular, because of the growing interest in association mapping using count phenotype data, it would be interesting to develop a testing framework for genetic associations that is immune to population structure when phenotype data consist of count measurements. Here, I propose a solution for testing associations between single nucleotide polymorphisms and a count phenotype in the presence of an arbitrary population structure. I consider a classical range of models for count phenotype data. Under these models, a unified test for genetic associations that protects against confounding was derived. An algorithm was developed to efficiently estimate the parameters that are required to fit the proposed model. I illustrate the proposed approach using simulation studies and an empirical study. Both simulated and real-data examples suggest that the proposed method successfully corrects population structure.

Joint associations of a polygenic risk score and environmental risk factors for breast cancer in the Breast Cancer Association Consortium.

Background: Polygenic risk scores (PRS) for breast cancer can be used to stratify the population into groups at substantially different levels of risk. Combining PRS and environmental risk factors will improve risk prediction; however, integrating PRS into risk prediction models requires evaluation of their joint association with known environmental risk factors. Methods: Analyses were based on data from 20 studies; datasets analysed ranged from 3453 to 23 104 invasive breast cancer cases and similar numbers of controls, depending on the analysed environmental risk factor. We evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS with reproductive history, alcohol consumption, menopausal hormone therapy (MHT), height and body mass index (BMI). We tested the null hypothesis of multiplicative joint associations for PRS and each of the environmental factors, and performed global and tail-based goodness-of-fit tests in logistic regression models. The outcomes were breast cancer overall and by estrogen receptor (ER) status. Results: The strongest evidence for a non-multiplicative joint associations with the 77-SNP PRS was for alcohol consumption (P-interaction = 0.009), adult height (P-interaction = 0.025) and current use of combined MHT (P-interaction = 0.038) in ER-positive disease. Risk associations for these factors by percentiles of PRS did not follow a clear dose-response. In addition, global and tail-based goodness of fit tests showed little evidence for departures from a multiplicative risk model, with alcohol consumption showing the strongest evidence for ER-positive disease (P = 0.013 for global and 0.18 for tail-based tests). Conclusions: The combined effects of the 77-SNP PRS and environmental risk factors for breast cancer are generally well described by a multiplicative model. Larger studies are required to confirm possible departures from the multiplicative model for individual risk factors, and assess models specific for ER-negative disease.

Using imputed genotype data in the joint score tests for genetic association and gene-environment interactions in case-control studies.

Genome-wide association studies (GWAS) are now routinely imputed for untyped single nucleotide polymorphisms (SNPs) based on various powerful statistical algorithms for imputation trained on reference datasets. The use of predicted allele counts for imputed SNPs as the dosage variable is known to produce valid score test for genetic association. In this paper, we investigate how to best handle imputed SNPs in various modern complex tests for genetic associations incorporating gene-environment interactions. We focus on case-control association studies where inference for an underlying logistic regression model can be performed using alternative methods that rely on varying degree on an assumption of gene-environment independence in the underlying population. As increasingly large-scale GWAS are being performed through consortia effort where it is preferable to share only summary-level information across studies, we also describe simple mechanisms for implementing score tests based on standard meta-analysis of "one-step" maximum-likelihood estimates across studies. Applications of the methods in simulation studies and a dataset from GWAS of lung cancer illustrate ability of the proposed methods to maintain type-I error rates for the underlying testing procedures. For analysis of imputed SNPs, similar to typed SNPs, the retrospective methods can lead to considerable efficiency gain for modeling of gene-environment interactions under the assumption of gene-environment independence. Methods are made available for public use through CGEN R software package.

Molecular mechanisms of Dicer: endonuclease and enzymatic activity.

The enzyme Dicer is best known for its role as a riboendonuclease in the small RNA pathway. In this canonical role, Dicer is a critical regulator of the biogenesis of microRNA and small interfering RNA, as well as a growing number of additional small RNAs derived from various sources. Emerging evidence demonstrates that Dicer's endonuclease role extends beyond the generation of small RNAs; it is also involved in processing additional endogenous and exogenous substrates, and is becoming increasingly implicated in regulating a variety of other cellular processes, outside of its endonuclease function. This review will describe the canonical and newly identified functions of Dicer.

Association between GWAS-identified lung adenocarcinoma susceptibility loci and EGFR mutations in never-smoking Asian women, and comparison with findings from Western populations.

To evaluate associations by EGFR mutation status for lung adenocarcinoma risk among never-smoking Asian women, we conducted a meta-analysis of 11 loci previously identified in genome-wide association studies (GWAS). Genotyping in an additional 10,780 never-smoking cases and 10,938 never-smoking controls from Asia confirmed associations with eight known single nucleotide polymorphisms (SNPs). Two new signals were observed at genome-wide significance (P < 5 × 10-8), namely, rs7216064 (17q24.3, BPTF), for overall lung adenocarcinoma risk, and rs3817963 (6p21.3, BTNL2) which is specific to cases with EGFR mutations. In further sub-analyses by EGFR status, rs9387478 (ROS1/DCBLD1) and rs2179920 (HLA-DPB1) showed stronger estimated associations in EGFR-positive compared to EGFR-negative cases. Comparison of the overall associations with published results in Western populations revealed that the majority of these findings were distinct, underscoring the importance of distinct contributing factors for smoking and non-smoking lung cancer. Our results extend the catalogue of regions associated with lung adenocarcinoma in non-smoking Asian women and highlight the importance of how the germline could inform risk for specific tumour mutation patterns, which could have important translational implications.

Integrated Microalgae Analysis Photobioreactor for Rapid Strain Selection.

Algal photosynthesis is considered to be a sustainable, alternative, and renewable solution to generating green energy. For high-productivity algaculture in diverse local environments, a high-throughput screening method is needed to select algal strains from naturally available or genetically engineered strains. Herein, we present an integrated plasmonic photobioreactor for rapid, high-throughput screening of microalgae. Our 3D nanoplasmonic optical cavity-based photobioreactor permits the amplification of a selective wavelength favorable to photosynthesis in the cavity. The hemispheric plasmonic cavity allows intercellular interaction to be promoted in the optically favorable milieu and also permits effective visual examination of algal growth. Using Chlamydomonas reinhardtii, we demonstrated a 2-fold enhanced growth rate and a 1.5-fold lipid production rate with no distinctive lag phase. By facilitating growth and biomass conversion rates, the integrated microalgae analysis platform will serve as rapid microalgae screening platforms for biofuel applications.

Meta-analysis of genome-wide association studies identifies multiple lung cancer susceptibility loci in never-smoking Asian women.

Genome-wide association studies (GWAS) of lung cancer in Asian never-smoking women have previously identified six susceptibility loci associated with lung cancer risk. To further discover new susceptibility loci, we imputed data from four GWAS of Asian non-smoking female lung cancer (6877 cases and 6277 controls) using the 1000 Genomes Project (Phase 1 Release 3) data as the reference and genotyped additional samples (5878 cases and 7046 controls) for possible replication. In our meta-analysis, three new loci achieved genome-wide significance, marked by single nucleotide polymorphism (SNP) rs7741164 at 6p21.1 (per-allele odds ratio (OR) = 1.17; P = 5.8 × 10(-13)), rs72658409 at 9p21.3 (per-allele OR = 0.77; P = 1.41 × 10(-10)) and rs11610143 at 12q13.13 (per-allele OR = 0.89; P = 4.96 × 10(-9)). These findings identified new genetic susceptibility alleles for lung cancer in never-smoking women in Asia and merit follow-up to understand their biological underpinnings.

Rapid Optical Cavity PCR.

Recent outbreaks of deadly infectious diseases, such as Ebola and Middle East respiratory syndrome coronavirus, have motivated the research for accurate, rapid diagnostics that can be administered at the point of care. Nucleic acid biomarkers for these diseases can be amplified and quantified via polymerase chain reaction (PCR). In order to solve the problems of conventional PCR--speed, uniform heating and cooling, and massive metal heating blocks--an innovative optofluidic cavity PCR method using light-emitting diodes (LEDs) is accomplished. Using this device, 30 thermal cycles between 94 °C and 68 °C can be accomplished in 4 min for 1.3 µL (10 min for 10 µL). Simulation results show that temperature differences across the 750 µm thick cavity are less than 2 °C and 0.2 °C, respectively, at 94 °C and 68 °C. Nucleic acid concentrations as low as 10(-8) ng µL(-1) (2 DNA copies per µL) can be amplified with 40 PCR thermal cycles. This simple, ultrafast, precise, robust, and low-cost optofluidic cavity PCR is favorable for advanced molecular diagnostics and precision medicine. It is especially important for the development of lightweight, point-of-care devices for use in both developing and developed countries.