Impact of circadian nuclear receptor REV-ERBα on midbrain dopamine production and mood regulation.

The circadian nature of mood and its dysfunction in affective disorders is well recognized, but the underlying molecular mechanisms are still unclear. Here, we show that the circadian nuclear receptor REV-ERBα, which is associated with bipolar disorder, impacts midbrain dopamine production and mood-related behavior in mice. Genetic deletion of the Rev-erbα gene or pharmacological inhibition of REV-ERBα activity in the ventral midbrain induced mania-like behavior in association with a central hyperdopaminergic state. Also, REV-ERBα repressed tyrosine hydroxylase (TH) gene transcription via competition with nuclear receptor-related 1 protein (NURR1), another nuclear receptor crucial for dopaminergic neuronal function, thereby driving circadian TH expression through a target-dependent antagonistic mechanism. In conclusion, we identified a molecular connection between the circadian timing system and mood regulation, suggesting that REV-ERBα could be targeting in the treatment of circadian rhythm-related affective disorders.

Co-transplantation of autologous Treg cells in a cell therapy for Parkinson's disease.

The specific loss of midbrain dopamine neurons (mDANs) causes major motor dysfunction in Parkinson's disease, which makes cell replacement a promising therapeutic approach1-4. However, poor survival of grafted mDANs remains an obstacle to successful clinical outcomes5-8. Here we show that the surgical procedure itself (referred to here as 'needle trauma') triggers a profound host response that is characterized by acute neuroinflammation, robust infiltration of peripheral immune cells and brain cell death. When midbrain dopamine (mDA) cells derived from human induced pluripotent stem (iPS) cells were transplanted into the rodent striatum, less than 10% of implanted tyrosine hydroxylase (TH)+ mDANs survived at two weeks after transplantation. By contrast, TH- grafted cells mostly survived. Notably, transplantation of autologous regulatory T (Treg) cells greatly modified the response to needle trauma, suppressing acute neuroinflammation and immune cell infiltration. Furthermore, intra-striatal co-transplantation of Treg cells and human-iPS-cell-derived mDA cells significantly protected grafted mDANs from needle-trauma-associated death and improved therapeutic outcomes in rodent models of Parkinson's disease with 6-hydroxydopamine lesions. Co-transplantation with Treg cells also suppressed the undesirable proliferation of TH- grafted cells, resulting in more compact grafts with a higher proportion and higher absolute numbers of TH+ neurons. Together, these data emphasize the importance of the initial inflammatory response to surgical injury in the differential survival of cellular components of the graft, and suggest that co-transplanting autologous Treg cells effectively reduces the needle-trauma-induced death of mDANs, providing a potential strategy to achieve better clinical outcomes for cell therapy in Parkinson's disease.

Denoiseit: denoising gene expression data using rank based isolation trees.

BACKGROUND: Selecting informative genes or eliminating uninformative ones before any downstream gene expression analysis is a standard task with great impact on the results. A carefully curated gene set significantly enhances the likelihood of identifying meaningful biomarkers. METHOD: In contrast to the conventional forward gene search methods that focus on selecting highly informative genes, we propose a backward search method, DenoiseIt, that aims to remove potential outlier genes yielding a robust gene set with reduced noise. The gene set constructed by DenoiseIt is expected to capture biologically significant genes while pruning irrelevant ones to the greatest extent possible. Therefore, it also enhances the quality of downstream comparative gene expression analysis. DenoiseIt utilizes non-negative matrix factorization in conjunction with isolation forests to identify outlier rank features and remove their associated genes. RESULTS: DenoiseIt was applied to both bulk and single-cell RNA-seq data collected from TCGA and a COVID-19 cohort to show that it proficiently identified and removed genes exhibiting expression anomalies confined to specific samples rather than a known group. DenoiseIt also showed to reduce the level of technical noise while preserving a higher proportion of biologically relevant genes compared to existing methods. The DenoiseIt Software is publicly available on GitHub at https://github.com/cobi-git/DenoiseIt.

Mutations of TP53 and genes related to homologous recombination repair in breast cancer with germline BRCA1/2 mutations.

BACKGROUND: Germline mutations of breast cancer susceptibility gene BRCA1 and BRCA2 (gBRCA1/2) are associated with elevated risk of breast cancer in young women in Asia. BRCA1 and BRCA2 proteins contribute to genomic stability through homologous recombination (HR)-mediated double-strand DNA break repair in cooperation with other HR-related proteins. In this study, we analyzed the targeted sequencing data of Korean breast cancer patients with gBRCA1/2 mutations to investigate the alterations in HR-related genes and their clinical implications. MATERIALS AND METHODS: Data of the breast cancer patients with pathogenic gBRCA1/2 mutations and qualified targeted next-generation sequencing, SNUH FiRST cancer panel, were analyzed. Single nucleotide polymorphisms, small insertions, and deletions were analyzed with functional annotations using ANNOVAR. HR-related genes were defined as ABL1, ATM, ATR, BARD1, BRCA1, BRCA2, CDKN1A, CDKN2A, CHEK1, CHEK2, FANCA, FANCD2, FANCG, FANCI, FANCL, KDR, MUTYH, PALB2, POLE, POLQ, RAD50, RAD51, RAD51D, RAD54L, and TP53. Mismatch-repair genes were MLH1, MSH2, and MSH6. Clinical data were analyzed with cox proportional hazard models and survival analyses. RESULTS: Fifty-five Korean breast cancer patients with known gBRCA1/2 mutations and qualified targeted NGS data were analyzed. Ethnically distinct mutations in gBRCA1/2 genes were noted, with higher frequencies of Val1833Ser (14.8%), Glu1210Arg (11.1%), and Tyr130Ter (11.1%) in gBRCA1 and Arg2494Ter (25.0%) and Lys467Ter (14.3%) in gBRCA2. Considering subtypes, gBRCA1 mutations were associated with triple-negative breast cancers (TNBC), while gBRCA2 mutations were more likely hormone receptor-positive breast cancers. At least one missense mutation of HR-related genes was observed in 44 cases (80.0%). The most frequently co-mutated gene was TP53 (38.1%). In patients with gBRCA1/2 mutations, however, genetic variations of TP53 occurred in locations different from the known hotspots of those with sporadic breast cancers. The patients with both gBRCA1/2 and TP53 mutations were more likely to have TNBC, high Ki-67 values, and increased genetic mutations, especially of HR-related genes. Survival benefit was observed in the TP53 mutants of patients with gBRCA2 mutations, compared to those with TP53 wild types. CONCLUSION: Our study showed genetic heterogeneity of breast cancer patients with gBRCA1 and gBRCA2 mutations in the Korean populations. Further studies on precision medicine are needed for tailored treatments of patients with genetic diversity among different ethnic groups.

KRT18 as a Novel Biomarker of Urothelial Papilloma while Evaluating Low-Grade Papillary Urothelial Neoplasms: Bi-Center Analysis.

INTRODUCTION: Although urothelial papilloma (UP) is an indolent papillary neoplasm that can mimic the morphology of low-grade papillary urothelial carcinoma (PUC), there is no immunomarker to differentiate reliably these two entities. In addition, the molecular characteristics of UP are not fully understood. METHODS: We conducted an in-depth proteomic analysis of papillary urothelial lesions (n = 31), including UP and PUC along with normal urothelium. Protein markers distinguishing UP and PUC were selected with machine learning analysis, followed by internal and external validation using immunohistochemistry. RESULTS: In the proteomic analysis, UP and PUC showed overlapping proteomic profiles. We identified EHD4 and KRT18 as candidate diagnostic biomarkers of UP. Through immunohistochemical validation in two independent cohorts (n = 120), KRT18 was suggested as a novel UP diagnostic marker, able to differentiate UP from low-grade PUC. We also found that 3.5% of patients with UP developed urothelial carcinoma in subsequent resections, supporting the malignant potential of UP. KRT18 downregulation was significantly associated with UPs subsequently progressing to urothelial carcinoma, following their initial diagnosis. CONCLUSION: This is the first study that successfully revealed UPs comprehensive proteomic landscape, while it also identified KRT18 as a potential diagnostic biomarker of UP.

Essential role for TRPC5 in amygdala function and fear-related behavior.

The transient receptor potential channel 5 (TRPC5) is predominantly expressed in the brain where it can form heterotetrameric complexes with TRPC1 and TRPC4 channel subunits. These excitatory, nonselective cationic channels are regulated by G protein, phospholipase C-coupled receptors. Here, we show that TRPC5(-/-) mice exhibit diminished innate fear levels in response to innately aversive stimuli. Moreover, mutant mice exhibited significant reductions in responses mediated by synaptic activation of Group I metabotropic glutamate and cholecystokinin 2 receptors in neurons of the amygdala. Synaptic strength at afferent inputs to the amygdala was diminished in P10-P13 null mice. In contrast, baseline synaptic transmission, membrane excitability, and spike timing-dependent long-term potentiation at cortical and thalamic inputs to the amygdala were largely normal in older null mice. These experiments provide genetic evidence that TRPC5, activated via G protein-coupled neuronal receptors, has an essential function in innate fear.

Primary sclerosing cholangitis causally affects kidney function decline: A Mendelian randomization study.

BACKGROUND AND AIM: The causal linkage between primary sclerosing cholangitis (PSC) and kidney function is unexplored despite their potential for long-term detrimental effects on kidney function. METHODS: Two-sample summary-level Mendelian randomization (MR) study was conducted to identify the association between PSC and kidney function. The genetic variants were extracted from the PSC-specific multi-trait analyzed genome-wide association study (GWAS) of European ancestry. Summary-level data for kidney function traits, including estimated glomerular filtration rate (eGFR), annual eGFR decline, and chronic kidney disease (CKD), were obtained from the CKDGen consortium. Multiplicative random-effects inverse-variance weighted (MR-IVW), and a series of pleiotropy-robust analyses were performed to investigate the causal effects and ascertain their robustness. RESULTS: Significant causal associations between genetically predicted PSC and kidney function traits were identified. Genetically predicted PSC was associated with decreased log-transformed eGFR (MR-IVW; beta = -0.41%; standard error [SE] = 0.02%; P < 0.001), increased rate of annual eGFR decline (MR-IVW; beta = 2.43%; SE = 0.18%; P < 0.001), and higher risk of CKD (MR-IVW; odds ratio = 1.07; 95% confidence interval = 1.06-1.08; P < 0.001). The main findings were supported by pleiotropy-robust analysis, including MR-Egger with bootstrapped error and weighted median. CONCLUSIONS: Our study demonstrates that genetically predicted PSC is causally associated with kidney function impairment. Further studies are warranted to identify the underlying mechanisms.

Non-invasive prediction of massive transfusion during surgery using intraoperative hemodynamic monitoring data.

OBJECTIVE: Failure to receive prompt blood transfusion leads to severe complications if massive bleeding occurs during surgery. For the timely preparation of blood products, predicting the possibility of massive transfusion (MT) is essential to decrease morbidity and mortality. This study aimed to develop a model for predicting MT 10 min in advance using non-invasive bio-signal waveforms that change in real-time. METHODS: In this retrospective study, we developed a deep learning-based algorithm (DLA) to predict intraoperative MT within 10 min. MT was defined as the transfusion of 3 or more units of red blood cells within an hour. The datasets consisted of 18,135 patients who underwent surgery at Seoul National University Hospital (SNUH) for model development and internal validation and 621 patients who underwent surgery at the Boramae Medical Center (BMC) for external validation. We constructed the DLA by using features extracted from plethysmography (collected at 500 Hz) and hematocrit measured during surgery. RESULTS: Among 18,135 patients in SNUH and 621 patients in BMC, 265 patients (1.46%) and 14 patients (2.25%) received MT during surgery, respectively. The area under the receiver operating characteristic curve (AUROC) of DLA predicting intraoperative MT before 10 min was 0.962 (95% confidence interval [CI], 0.948-0.974) in internal validation and 0.922 (95% CI, 0.882-0.959) in external validation, respectively. CONCLUSION: The DLA can successfully predict intraoperative MT using non-invasive bio-signal waveforms.

Healthcare burden changes by restricted physical activities in lumbar spinal stenosis and spondylolisthesis: a retrospective large cohort study during the COVID-19 pandemic.

BACKGROUND: Lumbar spinal stenosis (LSS) and spondylolisthesis (SPL) are characterized as degenerative spinal pathologies and share considerable similarities. However, opinions vary on whether to recommend exercise or restrict it for these diseases. Few studies have objectively compared the effects of daily physical activity on LSS and SPL because it is impossible to restrict activities ethnically and practically. We investigated the effect of restricting physical activity due to social distancing (SoD) on LSS and SPL, focusing on the aspect of healthcare burden changes during the pandemic period. METHODS: We included first-visit patients diagnosed exclusively with LSS and SPL in 2017 and followed them up for two years before and after the implementation of the SoD policy. As controls, patients who first visited in 2015 and were followed for four years without SoD were analyzed. The common data model was employed to analyze each patient's diagnostic codes and treatments. Hospital visits and medical costs were analyzed by regression discontinuity in time to control for temporal effects on dependent variables. RESULTS: Among 33,484 patients, 2,615 with LSS and 446 with SPL were included. A significant decrease in hospital visits was observed in the LSS (difference, -3.94 times/month·100 patients; p = 0.023) and SPL (difference, -3.44 times/month·100 patients; p = 0.026) groups after SoD. This decrease was not observed in the data from the control group. Concerning medical costs, the LSS group showed a statistically significant reduction in median copayment (difference, -$45/month·patient; p < 0.001) after SoD, whereas a significant change was not observed in the SPL group (difference, -$19/month·patient; p = 0.160). CONCLUSION: Restricted physical activity during the SoD period decreased the healthcare burden for patients with LSS or, conversely, it did not significantly affect patients with SPL. Under circumstances of physical inactivity, patients with LSS may underrate their symptoms, while maintaining an appropriate activity level may be beneficial for patients with SPL.

Aicardi-Goutières syndrome-associated gene SAMHD1 preserves genome integrity by preventing R-loop formation at transcription-replication conflict regions.

The comorbid association of autoimmune diseases with cancers has been a major obstacle to successful anti-cancer treatment. Cancer survival rate decreases significantly in patients with preexisting autoimmunity. However, to date, the molecular and cellular profiles of such comorbidities are poorly understood. We used Aicardi-Goutières syndrome (AGS) as a model autoimmune disease and explored the underlying mechanisms of genome instability in AGS-associated-gene-deficient patient cells. We found that R-loops are highly enriched at transcription-replication conflict regions of the genome in fibroblast of patients bearing SAMHD1 mutation, which is the AGS-associated-gene mutation most frequently reported with tumor and malignancies. In SAMHD1-depleted cells, R-loops accumulated with the concomitant activation of DNA damage responses. Removal of R-loops in SAMHD1 deficiency reduced cellular responses to genome instability. Furthermore, downregulation of SAMHD1 expression is associated with various types of cancer and poor survival rate. Our findings suggest that SAMHD1 functions as a tumor suppressor by resolving R-loops, and thus, SAMHD1 and R-loop may be novel diagnostic markers and targets for patient stratification in anti-cancer therapy.

Continual learning framework for a multicenter study with an application to electrocardiogram.

Deep learning has been increasingly utilized in the medical field and achieved many goals. Since the size of data dominates the performance of deep learning, several medical institutions are conducting joint research to obtain as much data as possible. However, sharing data is usually prohibited owing to the risk of privacy invasion. Federated learning is a reasonable idea to train distributed multicenter data without direct access; however, a central server to merge and distribute models is needed, which is expensive and hardly approved due to various legal regulations. This paper proposes a continual learning framework for a multicenter study, which does not require a central server and can prevent catastrophic forgetting of previously trained knowledge. The proposed framework contains the continual learning method selection process, assuming that a single method is not omnipotent for all involved datasets in a real-world setting and that there could be a proper method to be selected for specific data. We utilized the fake data based on a generative adversarial network to evaluate methods prospectively, not ex post facto. We used four independent electrocardiogram datasets for a multicenter study and trained the arrhythmia detection model. Our proposed framework was evaluated against supervised and federated learning methods, as well as finetuning approaches that do not include any regulation to preserve previous knowledge. Even without a central server and access to the past data, our framework achieved stable performance (AUROC 0.897) across all involved datasets, achieving comparable performance to federated learning (AUROC 0.901).

The Risk of COVID-19 and Its Outcomes in Korean Patients With Gout: A Multicenter, Retrospective, Observational Study.

This retrospective cohort study aimed to compare coronavirus disease 2019 (COVID-19)-related clinical outcomes between patients with and without gout. Electronic health record-based data from two centers (Seoul National University Hospital [SNUH] and Boramae Medical Center [BMC]), from January 2021 to April 2022, were mapped to a common data model. Patients with and without gout were matched using a large-scale propensity-score algorithm based on population-level estimation methods. At the SNUH, the risk for COVID-19 diagnosis was not significantly different between patients with and without gout (hazard ratio [HR], 1.07; 95% confidence interval [CI], 0.59-1.84). Within 30 days after COVID-19 diagnosis, no significant difference was observed in terms of hospitalization (HR, 0.57; 95% CI, 0.03-3.90), severe outcomes (HR, 2.90; 95% CI, 0.54-13.71), or mortality (HR, 1.35; 95% CI, 0.06-16.24). Similar results were obtained from the BMC database, suggesting that gout does not increase the risk for COVID-19 diagnosis or severe outcomes.

The prognostic value of a combined immune score in tumor and immune cells assessed by immunohistochemistry in triple-negative breast cancer.

BACKGROUND: This study aimed to develop a novel combined immune score (CIS)-based model assessing prognosis in triple-negative breast cancer (TNBC). METHODS: The expression of eight immune markers (PD-1, PD-L1, PD-L2, IDO, TIM3, OX40, OX40L, and H7-H2) was assessed with immunohistochemistry on the tumor cells (TCs) and immune cells (ICs) of 227 TNBC cases, respectively, and subsequently associated with selected clinicopathological parameters and survival. Data retrieved from The Cancer Genome Atlas (TCGA) were further examined to validate our findings. RESULTS: All immune markers were often expressed in TCs and ICs, except for PD-1 which was not expressed in TCs. In ICs, the expression of all immune markers was positively correlated between one another, except between PD-L1 and OX40, also TIM3 and OX40. In ICs, PD-1, PD-L1, and OX40L positive expression was associated with a longer progression-free survival (PFS; p = 0.040, p = 0.020, and p = 0.020, respectively). In TCs, OX40 positive expression was associated with a shorter PFS (p = 0.025). Subsequently, the TNBC patients were classified into high and low combined immune score groups (CIS-H and CIS-L), based on the expression levels of a selection of biomarkers in TCs (TCIS-H or TCIS-L) and ICs (ICIS-H or ICIS-L). The TCIS-H group was significantly associated with a longer PFS (p < 0.001). Furthermore, the ICIS-H group was additionally associated with a longer PFS (p < 0.001) and overall survival (OS; p = 0.001), at significant levels. In the multivariate analysis, both TCIS-H and ICIS-H groups were identified as independent predictors of favorable PFS (p = 0.012 and p = 0.001, respectively). ICIS-H was also shown to be an independent predictor of favorable OS (p = 0.003). The analysis of the mRNA expression data from TCGA also validated our findings regarding TNBC. CONCLUSION: Our novel TCIS and ICIS exhibited a significant prognostic value in TNBC. Additional research would be needed to strengthen our findings and identify the most efficient prognostic and predictive biomarkers for TNBC patients.

Quantitative proteomics identifies TUBB6 as a biomarker of muscle-invasion and poor prognosis in bladder cancer.

Muscle-invasive urothelial carcinoma (MIUC) of the bladder shows highly aggressive tumor behavior, which has prompted the quest for robust biomarkers predicting invasion. To discover such biomarkers, we first employed high-throughput proteomic method and analyzed tissue biopsy cohorts from patients with bladder urothelial carcinoma (BUC), stratifying them according to their pT stage. Candidate biomarkers were selected through bioinformatic analysis, followed by validation. The latter comprised 2D and 3D invasion and migration assays, also a selection of external public datasets to evaluate mRNA expression and an in-house patient-derived tissue microarray (TMA) cohort to evaluate protein expression with immunohistochemistry (IHC). Our multilayered platform-based analysis identified tubulin beta 6 class V (TUBB6) as a promising prognostic biomarker predicting MIUC of the bladder. The in vitro 2D and 3D migration and invasion assays consistently showed that inhibition of TUBB6 mRNA significantly reduced cell migration and invasion ability in two BUC cell lines with aggressive phenotype (TUBB6 migration, P = .0509 and P < .0001; invasion, P = .0002 and P = .0044; TGFBI migration, P = .0214 and P = .0026; invasion, P < .0001 and P = .0001; T24 and J82, respectively). Validation through multiple public datasets, including The Cancer Genome Atlas (TCGA) and selected GSE (Genomic Spatial Event) databases, confirmed TUBB6 as a potential biomarker predicting MIUC. Further protein-based validation with our TMA cohort revealed concordant results, highlighting the clinical implication of TUBB6 expression in BUC patients (overall survival: P < .001). We propose TUBB6 as a novel IHC biomarker to predict invasion and poor prognosis, also select the optimal treatment in BUC patients.

Personalized iPSC-Derived Dopamine Progenitor Cells for Parkinson's Disease.

We report the implantation of patient-derived midbrain dopaminergic progenitor cells, differentiated in vitro from autologous induced pluripotent stem cells (iPSCs), in a patient with idiopathic Parkinson's disease. The patient-specific progenitor cells were produced under Good Manufacturing Practice conditions and characterized as having the phenotypic properties of substantia nigra pars compacta neurons; testing in a humanized mouse model (involving peripheral-blood mononuclear cells) indicated an absence of immunogenicity to these cells. The cells were implanted into the putamen (left hemisphere followed by right hemisphere, 6 months apart) of a patient with Parkinson's disease, without the need for immunosuppression. Positron-emission tomography with the use of fluorine-18-L-dihydroxyphenylalanine suggested graft survival. Clinical measures of symptoms of Parkinson's disease after surgery stabilized or improved at 18 to 24 months after implantation. (Funded by the National Institutes of Health and others.).

Causal effects from tobacco smoking initiation on obesity-related traits: a Mendelian randomization study.

BACKGROUND: There is a widespread notion that tobacco smoking controls weight based on the appetite suppressive effect of nicotine. However, the causal relationship between smoking initiation and obesity-related traits in the general population are unclear. METHODS: This Mendelian randomization analysis utilized 378 genetic variants associated with tobacco smoking initiation (usually in adolescence or young adulthood) identified in a genome-wide association study (meta-analysis) of 1.2 million individuals. Outcome data for body mass index, waist circumference, hip circumference, and waist-to-hip ratio were extracted from the 337,138 white British-ancestry UK Biobank participants aged 40-69 years. Replication analyses were performed for genome-wide association study meta-analysis for body mass index, including the GERA/GIANT data including 364,487 samples from mostly European individuals. In addition, summary-level Mendelian randomization by inverse variance weighted method and pleiotropy-robust Mendelian randomization methods, including median-based and MR-Egger regression, was performed. RESULTS: Summary-level Mendelian randomization analysis indicated that genetically predicted smoking initiation is causally linked to higher body mass index [+0.28 (0.18-0.38) kg/m2], waist circumference [+0.88 (0.66-1.10) cm], hip circumference [+0.40 (0.23-0.57) cm], and waist-to-hip ratio [+0.006 (0.005-0.007)]. These results were consistent with those of the pleiotropy-robust Mendelian randomization analysis. Additionally, in replication analysis, genetically predicted smoking initiation was significantly associated with a higher body mass index [+0.03 (0.01, 0.05] kg/m2). CONCLUSION: Tobacco initiation may lead to worse obesity-related traits in the general 40- to 69-year-old individuals. Therefore, tobacco-use initiation as a long-term weight-control measure should be discouraged.

Development and validation of common data model-based fracture prediction model using machine learning algorithm.

The need for an accurate country-specific real-world-based fracture prediction model is increasing. Thus, we developed scoring systems for osteoporotic fractures from hospital-based cohorts and validated them in an independent cohort in Korea. The model includes history of fracture, age, lumbar spine and total hip T-score, and cardiovascular disease. PURPOSE: Osteoporotic fractures are substantial health and economic burden. Therefore, the need for an accurate real-world-based fracture prediction model is increasing. We aimed to develop and validate an accurate and user-friendly model to predict major osteoporotic and hip fractures using a common data model database. METHODS: The study included 20,107 and 13,353 participants aged ≥ 50 years with data on bone mineral density using dual-energy X-ray absorptiometry from the CDM database between 2008 and 2011 from the discovery and validation cohort, respectively. The main outcomes were major osteoporotic and hip fracture events. DeepHit and Cox proportional hazard models were used to identify predictors of fractures and to build scoring systems, respectively. RESULTS: The mean age was 64.5 years, and 84.3% were women. During a mean of 7.6 years of follow-up, 1990 major osteoporotic and 309 hip fracture events were observed. In the final scoring model, history of fracture, age, lumbar spine T-score, total hip T-score, and cardiovascular disease were selected as predictors for major osteoporotic fractures. For hip fractures, history of fracture, age, total hip T-score, cerebrovascular disease, and diabetes mellitus were selected. Harrell's C-index for osteoporotic and hip fractures were 0.789 and 0.860 in the discovery cohort and 0.762 and 0.773 in the validation cohort, respectively. The estimated 10-year risks of major osteoporotic and hip fractures were 2.0%, 0.2% at score 0 and 68.8%, 18.8% at their maximum scores, respectively. CONCLUSION: We developed scoring systems for osteoporotic fractures from hospital-based cohorts and validated them in an independent cohort. These simple scoring models may help predict fracture risks in real-world practice.

Analysis of random mutations in Salmonella Gallinarum dihydropteroate synthase conferring sulfonamide resistance.

In bacteria and primitive eukaryotes, sulfonamide antibiotics block the folate pathway by inhibiting dihydropteroate synthase (FolP) that combines para-aminobenzoic acid (pABA) and dihydropterin pyrophosphate (DHPP) to form dihydropteroic acid (DHP), a precursor for tetrahydrofolate synthesis. However, the emergence of resistant strains has severely compromised the use of pABA mimetics as sulfonamide drugs. Salmonella enterica serovar Gallinarum (S. Gallinarum) is a significant source of antibiotic-resistant infections in poultry. Here, a sulfonamide-resistant FolP mutant library of S. Gallinarum was generated through random mutagenesis. Among resistant strains, substitution of amino acid Arginine 171 with Proline (R171P) in the FolP protein conferred the highest resistance against sulfonamide. Substitution of Phe28 with Leu or Ile (F28L/I) led to modest sulfonamide resistance. Structural modeling indicates that R171P and Phenylalanine 28 with leucine or isoleucine (F28L/I) substitution mutations are located far from the substrate-binding site and cause insignificant conformational changes in the FolP protein. Rather, in silico studies suggest that the mutations altered the stability of the protein, potentially resulting in sulfonamide resistance. Identification of specific mutations in FolP that confer resistance to sulfonamide would contribute to our understanding of the molecular mechanisms of antibiotic resistance.

Application of the Khorana score for cancer-associated thrombosis prediction in patients of East Asian ethnicity undergoing ambulatory chemotherapy.

BACKGROUND: The Khorana score (KS) has not been well studied in East Asian cancer patients, who have different genetic backgrounds for inherited thrombophilia, body metabolism, and cancer epidemiology. METHODS: By using the Common Data Model, we retrospectively collected deidentified data from 11,714 consecutive newly diagnosed cancer patients who underwent first-line chemotherapy from December 2015 to December 2021 at a single institution in Korea, and we applied the KS for cancer-associated thrombosis (CAT) prediction. Age at diagnosis, sex, and use of highly thrombogenic chemotherapeutics were additionally investigated as potential risk factors for CAT development. RESULTS: By 6 months after chemotherapy initiation, 207 patients (1.77%) experienced CAT. Only 0.4% had a body mass index (BMI) ≥ 35 kg/m2 and changing the cutoff to 25 kg/m2 improved the prediction of CAT. Age ≥ 65 years and the use of highly thrombogenic chemotherapeutics were independently associated with CAT development. KS values of 1 ~ 2 and ≥ 3 accounted for 52.3% and 7.6% of all patients, respectively, and the incidence of CAT in these groups was 2.16% and 4.16%, respectively, suggesting a lower incidence of CAT in the study population than in Westerners. The KS component regarding the site of cancer showed a good association with CAT development but needed some improvement. CONCLUSION: The KS was partially validated to predict CAT in Korean cancer patients undergoing modern chemotherapy. Modifying the BMI cutoff, adding other risk variables, and refining the use of cancer-site data for CAT risk prediction may improve the performance of the KS for CAT prediction in East Asian patients.

Investigation of hepatic adverse events due to quetiapine by using the common data model.

PURPOSE: Quetiapine is a drug used to treat schizophrenia, bipolar disorder, and major depressive disorder. However, it can cause mild or severe hepatic adverse events and rarely fatal liver damage. This study was aimed at investigating hepatic toxicity caused by quetiapine use by analyzing the information captured from hospital electronic health records by using the Observational Medical Outcomes Partnership common data model (CDM). METHODS: This was a retrospective observational study involving a nested case-control method. A CDM based on an electronic health record database from five hospitals between January 2009 and May 2020 was used. We analyzed the status of quetiapine use, adverse events, and hepatic impairment. RESULTS: The numbers of patients with non-serious and severe hepatic adverse reactions were 2566 (5.05%) and 835 (1.64%) out of 50 766 patients, respectively. After adjusting for covariates, the odds ratio of hepatic adverse events was 2.35 (95% CI: 2.03-2.72), and the odds ratio of severe hepatic adverse events was 1.76 (95% CI: 1.16-2.66). CONCLUSION: Our findings suggest that quetiapine should be cautiously used, and hepatic function should be monitored in patients using quetiapine because it can cause mild or severe hepatic adverse events, complications, and in rare cases, fatal liver damage.