Association of metabolic comorbidity with myocardial infarction in individuals with a family history of cardiovascular disease: a prospective cohort study

Background The association between metabolic comorbidity and myocardial infarction (MI) among individuals with a family history of cardiovascular disease (CVD) is yet to be elucidated. We aimed to examine the combined effects of metabolic comorbidities, including diabetes mellitus, hypertension, and dyslipidemia, with a family history of CVD in first-degree on the risk of incident MI. Methods This cohort study consisted of 81,803 participants aged 40–89 years without a previous history of MI at baseline from the Korean Genome and Epidemiology Study. We performed Cox proportional hazard regression analysis to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for MI and early-onset MI risk associated with metabolic comorbidity in individuals with a family history of CVD. Results During a median follow-up of 5 years, 1,075 and 479 cases of total and early-onset MI were reported, respectively. According to the disease score, among individuals who had a positive family history of CVD, the HRs for MI were 1.92 (95% CI: 1.47–2.51) in individuals with one disease, 2.75 (95% CI: 2.09–3.61) in those with two diseases, and 3.74 (95% CI: 2.45–5.71) in those with three diseases at baseline compared to individuals without a family history of CVD and metabolic diseases. Similarly, an increase of the disease score among individuals with a positive family history of CVD was associated with an increase in early-onset MI risk. Conclusion Metabolic comorbidity was significantly associated with an increased risk of MI among individuals with a family history of CVD.This research was funded by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI16C1127)

Association between use of hydrochlorothiazide and nonmelanoma skin cancer: Common data model cohort study in Asian population

Although hydrochlorothiazide (HCTZ) has been suggested to increase skin cancer risk in white Westerners, there is scant evidence for the same in Asians. We analyzed the association between the use of hydrochlorothiazide and non-melanoma in the Asian population using the common data model. METHODS: A retrospective multicenter observational study was conducted using a distributed research network to analyze the effect of HCTZ on skin cancer from 2004 to 2018. We performed Cox regression to evaluate the effects by comparing the use of HCTZ with other antihypertensive drugs. All analyses were re-evaluated using matched data using the propensity score matching (PSM). Then, the overall effects were evaluated by combining results with the meta-analysis. RESULTS: Positive associations were observed in the use of HCTZ with high cumulative dose for non-melanoma skin cancer (NMSC) in univariate analysis prior to the use of PSM. Some negative associations were observed in the use of low and medium cumulative doses. CONCLUSION: Although many findings in our study were inconclusive, there was a non-significant association of a dose-response pattern with estimates increasing in cumulative dose of HCTZ. In particular, a trend with a non-significant positive association was observed with the high cumulative dose of HCTZ

Multidimensional fragmentomic profiling of cell-free DNA released from patient-derived organoids

Background Fragmentomics, the investigation of fragmentation patterns of cell-free DNA (cfDNA), has emerged as a promising strategy for the early detection of multiple cancers in the field of liquid biopsy. However, the clinical application of this approach has been hindered by a limited understanding of cfDNA biology. Furthermore, the prevalence of hematopoietic cell-derived cfDNA in plasma complicates the in vivo investigation of tissue-specific cfDNA other than that of hematopoietic origin. While conventional two-dimensional cell lines have contributed to research on cfDNA biology, their limited representation of in vivo tissue contexts underscores the need for more robust models. In this study, we propose three-dimensional organoids as a novel in vitro model for studying cfDNA biology, focusing on multifaceted fragmentomic analyses. Results We established nine patient-derived organoid lines from normal lung airway, normal gastric, and gastric cancer tissues. We then extracted cfDNA from the culture medium of these organoids in both proliferative and apoptotic states. Using whole-genome sequencing data from cfDNA, we analyzed various fragmentomic features, including fragment size, footprints, end motifs, and repeat types at the end. The distribution of cfDNA fragment sizes in organoids, especially in apoptosis samples, was similar to that found in plasma, implying occupancy by mononucleosomes. The footprints determined by sequencing depth exhibited distinct patterns depending on fragment sizes, reflecting occupancy by a variety of DNA-binding proteins. Notably, we discovered that short fragments (< 118 bp) were exclusively enriched in the proliferative state and exhibited distinct fragmentomic profiles, characterized by 3 bp palindromic end motifs and specific repeats. Conclusions In conclusion, our results highlight the utility of in vitro organoid models as a valuable tool for studying cfDNA biology and its associated fragmentation patterns. This, in turn, will pave the way for further enhancements in noninvasive cancer detection methodologies based on fragmentomics.This research was supported by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI14C1277); the Basic Science Research Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Education (2020R1A6A1A03047972); a Korea Basic Science Institute (National Research Facilities and Equipment Center) grant funded by the Ministry of Education (2021R1A6C101A445); and an MD-PhD/Medical Scientist Training Program grant through the KHIDI, funded by the Ministry of Health & Welfare, Republic of Korea

S100A9 Knockout Decreases the Memory Impairment and Neuropathology in Crossbreed Mice of Tg2576 and S100A9 Knockout Mice Model

Our previous study presented evidence that the inflammation-related S100A9 gene is significantly upregulated in the brains of Alzheimer&apos;s disease (AD) animal models and human AD patients. In addition, experiments have shown that knockdown of S100A9 expression improves cognition function in AD model mice (Tg2576), and these animals exhibit reduced amyloid plaque burden. In this study, we established a new transgenic animal model of AD by crossbreeding the Tg2576 mouse with the S100A9 knockout (KO) mouse. We observed that S100A9KO/Tg2576 (KO/Tg) mice displayed an increased spatial reference memory in the Morris water maze task and Y-maze task as well as decreased amyloid beta peptide (Aβ) neuropathology because of reduced levels of Aβ, C-terminal fragments of amyloid precursor protein (APP-CT) and phosphorylated tau and increased expression of anti-inflammatory IL-10 and also decreased expression of inflammatory IL-6 and tumor neurosis factor (TNF)-α when compared with age-matched S100A9WT/Tg2576 (WT/Tg) mice. Overall, these results suggest that S100A9 is responsible for the neurodegeneration and cognitive deficits in Tg2576 mice. The mechanism of S100A9 is able to coincide with the inflammatory process. These findings indicate that knockout of S100A9 is a potential target for the pharmacological therapy of AD. © 2014 Kim et al.1

Projection of Cancer Incidence and Mortality From 2020 to 2035 in the Korean Population Aged 20 Years and Older

Objectives: This study aimed to identify the current patterns of cancer incidence and estimate the projected cancer incidence and mortality between 2020 and 2035 in Korea. Methods: Data on cancer incidence cases were extracted from the Korean Statistical Information Service from 2000 to 2017, and data on cancer-related deaths were extracted from the National Cancer Center from 2000 to 2018. Cancer cases and deaths were classified according to the International Classification of Diseases, 10th edition. For the current patterns of cancer incidence, age-standardized incidence rates (ASIRs) and age-standardized mortality rates were investigated using the 2000 mid-year estimated population aged over 20 years and older. A joinpoint regression model was used to determine the 2020 to 2035 trends in cancer. Results: Overall, cancer cases were predicted to increase from 265 299 in 2020 to 474 085 in 2035 (growth rate: 1.8%). The greatest increase in the ASIR was projected for prostate cancer among male (7.84 vs. 189.53 per 100 000 people) and breast cancer among female (34.17 vs. 238.45 per 100 000 people) from 2000 to 2035. Overall cancer deaths were projected to increase from 81 717 in 2020 to 95 845 in 2035 (average annual growth rate: 1.2%). Although most cancer mortality rates were projected to decrease, those of breast, pancreatic, and ovarian cancer among female were projected to increase until 2035. Conclusions: These up-to-date projections of cancer incidence and mortality in the Korean population may be a significant resource for implementing cancer-related regulations or developing cancer treatments

Verification of De-Identification Techniques for Personal Information Using Tree-Based Methods with Shapley Values

With the development of big data and cloud computing technologies, the importance of pseudonym information has grown. However, the tools for verifying whether the de-identification methodology is correctly applied to ensure data confidentiality and usability are insufficient. This paper proposes a verification of de-identification techniques for personal healthcare information by considering data confidentiality and usability. Data are generated and preprocessed by considering the actual statistical data, personal information datasets, and de-identification datasets based on medical data to represent the de-identification technique as a numeric dataset. Five tree-based regression models (i.e., decision tree, random forest, gradient boosting machine, extreme gradient boosting, and light gradient boosting machine) are constructed using the de-identification dataset to effectively discover nonlinear relationships between dependent and independent variables in numerical datasets. Then, the most effective model is selected from personal information data in which pseudonym processing is essential for data utilization. The Shapley additive explanation, an explainable artificial intelligence technique, is applied to the most effective model to establish pseudonym processing policies and machine learning to present a machine-learning process that selects an appropriate de-identification methodology

Individualized Biological Age as a Predictor of Disease: Korean Genome and Epidemiology Study (KoGES) Cohort

Chronological age (CA) predicts health status but its impact on health varies with anthropometry, socioeconomic status (SES), and lifestyle behaviors. Biological age (BA) is, therefore, considered a more precise predictor of health status. We aimed to develop a BA prediction model from self-assessed risk factors and validate it as an indicator for predicting the risk of chronic disease. A total of 101,980 healthy participants from the Korean Genome and Epidemiology Study were included in this study. BA was computed based on body measurements, SES, lifestyle behaviors, and presence of comorbidities using elastic net regression analysis. The effects of BA on diabetes mellitus (DM), hypertension (HT), combination of DM and HT, and chronic kidney disease were analyzed using Cox proportional hazards regression. A younger BA was associated with a lower risk of DM (HR = 0.63, 95% CI: 0.55&ndash;0.72), hypertension (HR = 0.74, 95% CI: 0.68&ndash;0.81), and combination of DM and HT (HR = 0.65, 95% CI: 0.47&ndash;0.91). The largest risk of disease was seen in those with a BA higher than their CA. A consistent association was also observed within the 5-year follow-up. BA, therefore, is an effective tool for detecting high-risk groups and preventing further risk of chronic diseases through individual and population-level interventions

Indoor Tanning and the Risk of Overall and Early-Onset Melanoma and Non-Melanoma Skin Cancer: Systematic Review and Meta-Analysis

The aim of this study was to examine the association between indoor tanning use and the risk of overall and early-onset (age &lt; 50) melanoma and non-melanoma skin cancer (NMSC). To evaluate the association between indoor tanning and skin cancer, a systematic review of the literature published until July 2021 was performed using PubMed, EMBASE, and MEDLINE. Summary relative risk (RR) from 18 studies with 10,406 NMSC cases and 36 studies with 14,583 melanoma cases showed significant association between skin cancer and indoor tanning (melanoma, RR= 1.27, 95% CI 1.16&ndash;1.39; NMSC, RR = 1.40, 95% CI 1.18&ndash;1.65; squamous cell carcinoma (SCC), RR = 1.58, 95% CI 1.38&ndash;1.81; basal cell carcinoma (BCC), RR = 1.24, 95% CI 1.00&ndash;1.55). The risk was more pronounced in early-onset skin cancer (melanoma, RR = 1.75, 95% CI 1.14&ndash;2.69; NMSC, RR = 1.99, 95% CI 1.48&ndash;2.68; SCC, RR = 1.81, 95% CI 1.38&ndash;2.37; BCC, RR = 1.75, 95% CI 1.15&ndash;2.77). Moreover, first exposure at an early age (age &le; 20 years) and higher exposure (annual frequency &ge; 10 times) to indoor tanning showed increasing risk for melanoma (RR = 1.47, 95% CI 1.16&ndash;1.85; RR = 1.52, 1.22&ndash;1.89) and NMSC (RR = 2.02, 95% CI 1.44&ndash;2.83; RR = 1.56, 95% CI 1.31&ndash;1.86). These findings provide evidence supporting primary prevention policies regulating modifiable behaviors to reduce the additional risk of skin cancer among younger adults

Identifying Genetic Variants and Metabolites Associated with Rapid Estimated Glomerular Filtration Rate Decline in Korea Based on Genome&ndash;Metabolomic Integrative Analysis

Identifying the predisposing factors to chronic or end-stage kidney disease is essential to preventing or slowing kidney function decline. Therefore, here, we investigated the genetic variants related to a rapid decline in the estimated glomerular filtration rate (eGFR) (i.e., a loss of &gt;5 mL/min/1.73 m2 per year) and verified the relationships between variant-related diseases and metabolic pathway signaling in patients with chronic kidney disease. We conducted a genome-wide association study that included participants with diabetes, hypertension, and rapid eGFR decline from two Korean data sources (N = 115 and 69 for the discovery and the validation cohorts, respectively). We identified a novel susceptibility locus: 4q32.3 (rs10009742 in the MARCHF1 gene, beta = &minus;3.540, P = 4.11 &times; 10&minus;8). Fine-mapping revealed 19 credible, causal single-nucleotide polymorphisms, including rs10009742. The pimelylcarnitine and octadecenoyl carnitine serum concentrations were associated with rs10009742 (beta = 0.030, P = 7.10 &times; 10&minus;5, false discovery rate (FDR) = 0.01; beta = 0.167, P = 8.11 &times; 10&minus;4, FDR = 0.08). Our results suggest that MARCHF1 is associated with a rapid eGFR decline in patients with hypertension and diabetes. Furthermore, MARCHF1 affects the pimelylcarnitine metabolite concentration, which may mediate chronic kidney disease progression by inducing oxidative stress in the endoplasmic reticulum

Association of coffee drinking with all-cause and cause-specific mortality in over 190,000 individuals: data from two prospective studies

We examined the association of coffee drinking with all-cause and cause-specific mortality in a pooled analysis of two Korean prospective cohort studies: The Korea National Health and Nutrition Examination Survey and the Korean Genome and Epidemiology Study. We included 192,222 participants, and a total of 6057 deaths were documented. Cox proportional hazards model was used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs), and the HRs were combined using a random-effects model. Coffee drinking was associated with a lower risk of all-cause mortality [HR (95% CI) = 0.84 (0.77-0.92), for &gt;= 3 cups/day of coffee drinking versus non-drinkers; p for trend = 0.004]. We observed the potential benefit of coffee drinking for mortality due to cardiovascular disease, respiratory disease, and diabetes, but not for cancer mortality. Overall, we found that moderate coffee drinking was associated with a lower risk of death in population-based cohort analysis of Korean adults.N